Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Technological challenges >> Metrology
138 proposition(s).

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Safety/Security Modeling for Security Characterization of Industrial Control Systems

Département Systèmes (LETI)

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-10-2021

SL-DRT-21-0031

Cyber security : hardware and sofware (.pdf)

Industrial systems are often used to monitor and control a physical process such as energy production and distribution, water cleaning or transport systems. They are often simply called Supervisory Control And Data Acquisition (SCADA) systems. Due to their interaction with the real world, the safety of these systems is critical and any incident can potentially harm humans and the environment. Since the Stuxnet worm in 2010, such systems increasingly face cyberattacks caused by various intruders, including terrorists or enemy governments [1]. As the frequency of such attacks is increasing, the security of SCADA systems becomes a priority for governmental agencies [2]. One of the main research axis in cybersecurity of industrial systems deals with combination of safety and security properties. Safety relates to applicative properties of the system (e.g. chemical properties for a chemical factory); while security properties take into account how an intruder can harm the system. As show in [3], combining safety and security is a challenging topic as these properties can be either dependent, strengthening, antagonist or independent. As show in [4], combining both safety and security in a common modeling is challenging as both come with sources of combinatorial explosion. Moreover, there are tools used either for security or safety analyzes but currently no tool is able to handle both aspects at the same time. In this context, we propose a Ph.D thesis revolving around modeling of industrial systems taking into account both safety properties of the physical process and security properties. Besides the definition of an accurate, yet automatically analyzable modeling framework/language, many aspects can be part of the subject. For instance, programmable automata (PLC) configuration files could be generated from this model in order to only deploy programs validated beforehand. PLC vulnerabilities could be studied (firmware reverse engineering, protocol fuzzing) in order to test the technical feasibility of found attacks. Finally, in a certification context, security analyzes on the model could include requirements from standards such as IEC 62443 [5] to help evaluation process. Références [1] J. Weiss, Protecting industrial control systems from electronic, Momentum Press, 2010. [2] ANSSI, Managing cybersecurity for ICS, ANSSI, 2012. [3] L. Piètre-Cambacédès, Des relations entre sûreté et sécurité, Paris: Télécom ParisTech, 2010. [4] M. P. a. A. K. M. Puys, Generation of applicative attacks scenarios against industrial systems, Nancy: FPS'17, 2017. [5] IEC-62443, Industrial communication networks - Network and, International Electrotechnical Commission, 2010.

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embedded elapsed-time attestation

Département Systèmes (LETI)

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-10-2021

SL-DRT-21-0089

christine.hennebert@cea.fr

Cyber security : hardware and sofware (.pdf)

With the emergence of a protocol that secures a history of transactions on a peer-to-peer network, Bitcoin introduced the first decentralized digital currency in 2009. The security of the Bitcoin protocol is based on the proof of work and common rules and procedures among peers in the network who participate in the consensus, i.e. the choice of the next block of data to be added to the shared and replicated ledger. The proof of work has two major drawbacks. On the one hand, it ensures security by design by requiring nodes participating in the consensus to work with a computing intensity corresponding to the maximum of Moore's law, which is obviously very energy consuming. On the other hand, the parallelization of this proof process with an implementation in ASICs makes the system vulnerable to Sybil-type attacks by recentralizing resources. The mining pools exploit this vulnerability. The present thesis topic aims at building a proof for embedded and resource constrained objects, which ensures the security of a transaction history at low power. The work will focus on the embedded implementation of the proof mechanism on a system-on-module platform using a TPM 2.0 (Trusted Platform Module) security hardware component as root-of-trust. The solution introduced will have to be robust to the above-mentioned drawbacks and vulnerabilities.

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Fault injection and integrity of edge neural networks: attacks, protections, evaluation

Département Systèmes (LETI)

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-02-2021

SL-DRT-21-0159

pierre-alain.moellic@cea.fr

Artificial intelligence & Data intelligence (.pdf)

One of the major trends of Artificial Intelligence is the large-scale deployment of Machine Learning systems to a large variety of embedded platforms. A lot of semi-conductor practioners propose "A.I. suitable" products, majoritarely with neural networks for inference purpose. The security of the embedded models is a major issue for the deployment of these systems. Several works raised threats such as the adversarial examples or the membership inference attacks with disastrous impact. These works consider the ML aglorithms through a pure algorithmic point of view without taking into consideration the specificities of their physical implementation. Moreover, advanced works are compulsory for physical attacks (i.e., side-channel and fault injection analysis). By considering a overall attack surface gathering the theoretical (i.e. algorithmic) and physical facets, this subject propose to analyze Fault Injection Analysis threats (FIA) targeting the integrity of the model (fooling a prediction) of embedded machine learning systems and the development of appropriate protections. Several works have studied physical attacks for embedded neural networks but with usually naive model architecture on 'simple' 8-bit microcontrolers, or FPGA or at a pure simulation level. These works do not try to link the fault models or the leakages with well-known algorithmic threats. Being based on the experience on other critical systems (e.g., cryptographic primitive), the main idea of this PhD subject will be to jointly analysis the algorithmic and physical world in order to better understand the complexity of the threats and develop efficient defense schemes. The works will answer the following scientific challenges: (1) Caracterization and exploitation of fault models: how to exploit fault injection mechanisms (laser, EM, glitching) to fool the prediction of a model with minimal perturbations. (2) Evaluation of the relevance of classical countermeasures (such as redundancy-based techniques) for this kind of systems and threats. (3) Develop new protections suitable to embedded neural networks.

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Autonomous network management solution for deterministic networks using Artificial Intelligence (AI) techniques

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire Systèmes Communiquants

01-02-2021

SL-DRT-21-0178

siwar.benhadjsaid@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

The objective of the thesis is to explore and evaluate the gain that could bring the Artificial Intelligence (AI) techniques to the network management solutions for deterministic networks. The goal is to help deterministic networks to ensure the preservation of the quality of service (QoS) during the routing of end-to-end data flow no matter what changes are made to the network. This will allow to design an autonomous network management solution that is able to configure deterministic networks in the most appropriate way and adapt the configuration when needed (e.g. new terminal connecting to the network, unexpected high latency for certain critical flows, change of the topology caused by the reorganization / reconfiguration of components of the production chain in the factory etc.). This solution will use artificial intelligence methods to learn from experience the conditions that lead to non-compliance with application flow requirements (high latency, low bandwidth, etc.). Learning takes place to recognize, upstream, the situations that may lead to non-compliance with the constraints of application flows and also to predict the effects of changes in input data (new terminal, reorganization of the plant, etc.) on the level of QoS provided to flows in transit. Based on such knowledge, the solution will anticipate QoS degradation situations and, consequently, will decide and push the adequate network reconfiguration which will make it possible to respect the constraints associated with each application flow.

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Distributed resource allocation for meshed networks of mobile users in shared spectrum

Département Systèmes (LETI)

Laboratoire Sans fils Haut Débit

01-09-2021

SL-DRT-21-0186

mickael.maman@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

In future 5G wireless networks, it is imperative to easily deploy and manage a private network of mobile users such as a fleet of vehicles or UAVs. The objective of this thesis is to define a distributed resource allocation for mesh networks of mobile users in the shared spectrum through resource pooling (time/frequency) and efficient management of directional antenna beams. While existing studies focus on maximizing the performance of static backhaul multi-beam mesh networks, we are interested in collaborative local/distributed learning between mobile users. The first step of this thesis will be to integrate a realistic model of sub 6-GHz and/or mmW directional antennas in a network simulator. A trade off between the spatiality of the directivity, the antenna efficiency and the complexity of the algorithm will be made for point-to-point and point-to-multipoint communications. Moreover the antenna configurations will be contextualized between the communication, discovery or tracking phases. The second step of this thesis will concern the design of the distributed resource allocation protocol during different stages of the network life: deployment, self-optimization and self-healing. A trade-off will be made between the type and latency of antenna (re)configuration, the accuracy of beam alignment, the channel coherence time for mobile users (volatile connectivity) and the convergence time of the scheduling.

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Automatic design of secure hardware architectures

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Environnement de Conception et Architecture

01-10-2021

SL-DRT-21-0190

caaliph.andriamisaina@cea.fr

Cyber security : hardware and sofware (.pdf)

Embedded systems are more and more ubiquitous and interconnected; they are an attractive target for security attacks. The security aspect is thus becoming more and more important when designing these systems, as a vulnerability in one system can compromise an entire infrastructure of connected systems. Thus, each system contributes to the construction of a global chain of trust. Moreover, given the increasing complexity of the applications running on these systems, it is becoming increasingly difficult to meet all security criteria (for instance application isolation, system authentication, secret and private data protection, communications protection). The design of these systems therefore requires an in-depth analysis of the various security constraints to which they are subject, based on a threat model associated with the potential attacker. While extra-functional design objectives such as performance, power consumption and area are generally well taken into account during the very early stages of embedded system design, security is still generally considered afterwards, leading to security solutions seen as an addition to the initial system. This design approach needs to be reconsidered in order to develop solutions that integrate security by construction and no longer as an additional element. The objective of this thesis is thus to take into account the security constraints in addition to the performance, power consumption and area constraints during the design space exploration (DSE) of hardware architectures in order to automatically generate an architecture optimized with respect to all these constraints. This study will begin with an analysis of the threat models in particular with respect to hardware attacks and existing countermeasures at the hardware level. Then, the security modeling and quantifying in the context of DSE will be carried out, as it will be essential to clearly characterize the techniques and approaches for taking into account the security needs of the systems. From this step, the candidate will propose a DSE flow of hardware architectures taking into account security constraints, in addition to power consumption, performance and area constraints. The goal is to be able to analyze the security, area, power consumption and performance trade-offs according to the designers' specifications at both functional and non-functional levels. This flow will then be applied to a practical case of hardware architecture design in order to validate the developed DSE approach. The developed solutions will have to demonstrate their level of robustness with respect to the security constraint in order to guarantee the security of the systems while respecting and optimizing the other design constraints.

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Proof of functional equivalence of binary codes in the context of programs hardening

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Fonctions Innovantes pour circuits Mixtes

01-10-2021

SL-DRT-21-0192

damien.courousse@cea.fr

Cyber security : hardware and sofware (.pdf)

The general context of this thesis is the cyber-security of embedded systems. The research background of this thesis is tied to the automatic application of counter-measures against the so-called physical attacks, which encompass observation attacks (side-channel attacks) and perturbation attacks (fault-injection attacks). The CEA List is working on COGITO, a compiler toolchain based on LLVM for the automatic application of software counter-measures against physical attacks. Given a source-level implementation of an unprotected program, our toolchain produces an optimised binary program including targeted counter-measures, such that the compiled program is hardened against a specified threat model. Two key points are today crucial to trust the compiled programs: 1. the proof of robustness of programs produced by our toolchain, 2. the proof that adding counter-measures does not alter the functionality of the target programs. This thesis will target the second point: bringing formal guarantees about the functional correctness of the secured programs. We will use sound and exhaustive symbolic reasoning, supported by BINSEC (). BINSEC is an open-source toolset developed at CEA List to help improve software security at the binary level. It relies on cutting-edge research in binary code analysis, at the intersection of formal methods, program analysis, security and software engineering. The PhD thesis will be hosted at the CEA in Grenoble, in a multidisciplinary environment including experts in embedded software, cyber-security, hardware design, and machine learning. Short-term stays at the DILS at the CEA in Saclay will be planned throughout the three years of the thesis to collaborate with experts and developers of BINSEC.

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Innovative flexible piezoelectric sensors for tactile and acoustic interface ? Multifunction sensors

Département Systèmes (LETI)

Laboratoire Autonomie et Intégration des Capteurs

01-09-2021

SL-DRT-21-0205

elise.saoutieff@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

The aim of the PhD thesis is to implement a matrix of flexible piezoelectric nanosensors, which enable the 3D reconstruction of a force or deformation field. The nanosensors based on GaN nanowires obtained by directed growth are fabricated and assembled at CEA. The candidate will tackle experimental aspects, which include the fabrication and the assembly of sensors and sensor networks (matrix) via controlled growth and deposition processes, first-level flexible electronic layers (interconnects), system integration on an object (mechatronics) and finally signal collection and processing through a dedicated reading electronics, to be designed based on the competences present in our laboratory. In parallel, the candidate will carry out studies at the fundamental level, such as investigating the mechanical transfer between the nanowire and its environment and its effect on the generated signal under deformation, or the study of the piezoelectric / pyroelectric coupling intrinsic to GaN nanowires. For this purpose, the candidate will have access to multi-physics simulation tools. Finally, investigations on the choice of materials and the characterisation thereof (structural, mechanical, thermal, optical, electrical) will be pertinent and may pursued. More generally, this PhD thesis will also provide the opportunity to develop applicable solutions in various fields such as deformation and impacts detectors for predictive maintenance, sensitive surfaces or electronic skin.

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Wideband mmW receiver architectures based on innovative modulation schemes

Département Systèmes (LETI)

Laboratoire Architectures Intégrées Radiofréquences

01-03-2021

SL-DRT-21-0216

joseluis.gonzalezjimenez@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

Existing telecommunication and data communication networks are evolving towards extremely high capacity and data-rate connections that will require innovative transceiver architectures. For wireless data links, beyond 5G and 6G and systems will be required in the next 5 to 10 years able to provide 100Gb/s or higher data rates by efficiently using the wide spectrum available at millimeter-wave (mmW) or sub-THz frequencies. Traditional transceiver architecture that have been used in the past may result too power consuming or simply not performant enough to respond to this challenge. The LETI research institute has been conducting research during the lasts year in the field of innovative modulations schemes and transceiver architectures trying to respond to the above-mentioned high data-rate in wireless environments considering the limitation imposed by existing electronic devices required to build the transceivers. This thesis subject will explore the practical implementation of circuits based on innovative modulation schemes and architectures for high-speed, large-bandwidth, imperfection resilient mmW receivers for beyond 5G and 6G telecommunication applications and other high data-rate wireless communications applications.

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Single address space for massively parallel computers

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Systèmes-sur-puce et Technologies Avancées

01-09-2021

SL-DRT-21-0248

christian.fabre1@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

The generalization of a hierarchical organization of HPC machines into nodes of several dozen computing cores interconnected by a high-performance communication network has fragmented operating systems and greatly complicated the writing of applications. The proposal of a 128 bit processor architecture by the RISC-V community offers the possibility of reinterpreting the fundamental concepts in view of these fundamental changes in the structure of the machines. In particular, this proposal offers the opportunity to rethink memory addressing at the scale of the entire machine, and not locally at the level of each node. The purpose of this thesis will be to study the opportunities thus offered, to propose strategies for managing a 128-bit addressing space on the scale of the machine, and to evaluate its technical feasibility, hardware and software and expected performance. The Research Director for the PhD student will be Prof. Frédéric Pétrot, from Grenoble-INP/ENSIMAG. Christian Fabre (software) & Cesar Fuguet Tortorelo (hardware) from CEA LIST, will supervise the day-to-day work.

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Millimeter Wave Short Range RadCom

Département Systèmes (LETI)

Laboratoire Architectures Intégrées Radiofréquences

01-09-2021

SL-DRT-21-0258

cedric.dehos@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

Mmw transceiver chips for high data rate, short range communication should be integrated soon in most mobile devices as contacless connectors. The wide bandwidth of these mmw transceiver may be used for fine resolution proximity radar, gesture recognition, biometric identification or Human Machine Interface. The thesis will investigate the possibility of slightly modifying the RF transceiver architecture to get the double feature of radar and communication in the same low cost and low power chip. The non-coherent communication architecture may evolve towards IR-UWB or FM-CW radar, with impact on the receiver complexity and radar performance. The PHD will evaluate the different alternatives, considering integrated low power radar processing and Artificial Intelligence embedded in MCU for analysis and classification.

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Formal verification of hardware micro-architectures to analyze the influence of faults injection and the robustness of countermeasures

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Environnement de Conception et Architecture

01-10-2021

SL-DRT-21-0276

Mathieu.Jan@cea.fr

Cyber security : hardware and sofware (.pdf)

The never race towards higher average performance for numerical systems leads to increase the complexity of modern hardware architectures. This threatens the design of secure embedded systems as it opens new attack vectors. For example, the Spectre family of attacks exemplifies the issues that speculative execution mechanisms can raise in modern processor architectures. In the context of this PhD proposal, the more complex a processor architecture is, the larger is the attack surface exploitable by fault injection attacks. Such attacks, performed by the means of a physical perturbation of the circuit, aim at exploiting a logical perturbation in the computing for various purposes: leaking secrets, bypassing authentication procedures, escalation of privileges, etc. The modeling of the logical effects of a physical perturbation over numerical systems has been studied extensively, but it is still challenging to model precisely. Furthermore, recent research work has shown that inducing faults in the processor microarchitecture can lead to subtle effects, opening interesting research questions about the modeling and the analysis of such effects, and possible mitigations. The objective of this PhD thesis is to investigate formal approaches on the hardware side to better understand the consequences of fault injections, as well as to verify the efficiency of countermeasures shipped in secure embedded systems.

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DC/DC converter based on piezoelectric material

Département Systèmes (LETI)

Laboratoire Electronique Energie et Puissance

01-10-2020

SL-DRT-21-0277

ghislain.despesse@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

The aim of this thesis is to design high-efficiency power converters based on resonating piezoelectric transducers. A large part of the work is to develop the electrical cycle able to energetically maintain the piezoelectric resonator in resonance and ensure zero-voltage switching, for electrical energy transfer from the source to the piezoelectric resonator or from the piezoelectric resonator to the output, in order to minimize the losses. An electronic power management circuit will be designed to enable this ideal energetic cycle. This electronic circuit will include several regulation loops to ensure the system stability and regulate the electrical output power. Finally, a study of the piezoelectric transducer size reduction will be done in view of a MEMS (Micro Electro Mechanical System) integration.

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Robustness and performances of improved electrodes for solid oxide cells application

Département Thermique Conversion et Hydrogène (LITEN)

Laboratoire essais et systèmes

01-10-2021

SL-DRT-21-0289

maxime.hubert@cea.fr

Advanced hydrogen and fuel-cells solutions for energy transition (.pdf)

Solid oxide cells (SOCs) are electrochemical devices operating at high temperature that can directly convert fuel into electricity (fuel cell mode ? SOFC) or electricity into fuel (electrolysis mode ? SOEC). In recent years, the interest on SOCs has grown significantly thanks to their wide range of technological applications that could offer innovative solutions for the transition toward a renewable energy market. However, despite of all their advantages, the SOCs lifetime is still insufficient to envisage the industrial deployment of this technology. Indeed, the SOCs durability remains limited by various degradation phenomena including a mechanical damage in the electrodes. For instance, the formation of micro-cracks in the so-called ?hydrogen' electrode is a major source of degradation. However, the precise mechanism and the full impact of the micro-cracks on the electrode performances are still unknown. By a multi-physic modelling approach, it is proposed in this thesis to establish the link between the loss of performances and the mechanical damage in the hydrogen electrode. Once the model validated on dedicated experiments, a sensitivity analysis will be conducted to provide relevant guidelines for the manufacturing of improved robust and performant electrodes. One or two solutions will be selected and evaluated after manufacturing for final validation.

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Passive radar

Département Systèmes (LETI)

Laboratoire Sans fils Haut Débit

01-09-2021

SL-DRT-21-0301

patrick.rosson@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

The principle of passive radars is to use non-cooperative transmitters whose position is known in order to detect and locate targets in the scanned zone. The Army knows how to use the powerful signal transmitted by the FM stations or the DVD-T stations. With their antennas array, they know how to monitor large rural areas thanks to a single powerful enough non-cooperative transmitter. In our urban or suburban context, we propose to use the signals transmitted by the cellular network. Nowadays, cellular base stations cover a large part of the territory. They also transmit in several frequency bands from 700 MHz to 3500 MHz. The objective is to use the transmit diversity offered by these base stations to detect and locate our targets thanks to a reception system less complex in terms of hardware. Techniques based on transmit diversities (i.e. polarization, frequency, and space) will be studied at the theoretical level before being evaluated on real signals in an urban context.

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Sensor network and low-power Edge AI for predictive maintenance

Département Systèmes (LETI)

Laboratoire Autonomie et Intégration des Capteurs

01-10-2021

SL-DRT-21-0312

vincent.heiries@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Predictive maintenance is a major issue for the industry of the future (Industry 4.0), allowing to maximize the use time of parts, increase the machines service lifes, reduce failures and equipment downtime, with economic and environmental gains for the company. Predictive maintenance relies on sensor networks placed on the equipment to be monitored and on learning mechanisms using artificial intelligence (Machine Learning). These sensors are today essentially wired, which makes their installation complex: cables installation, walls, rotating environments, ... The ideal solution would be to have wireless communicating sensors; then the question of their energy autonomy arises, which is the issue of this PhD thesis. This topic, which is part of the "Cyber-Physical Systems" roadmap of the Systems Department of CEA-LETI (Grenoble), will aim to develop a network of low-power wireless sensors to monitor industrial equipments and anticipate their failure. The PhD work will be based on advanced technological solutions using embedded artificial intelligence (edge AI), data fusion processing from different sensors (audio, vibration) and low-power electronics (hardware and firmware) in particular for the signals processing and communication aspects. Artificial intelligence is booming, with major challenges for health, transport, environmental protection and industry. At present, computations are mainly carried out on servers (commonly referred to as the cloud), which requires the complete transmission of data measured by sensors (e.g. an audio signal for a microphone, or vibrations for an accelerometer). This architecture is simple to deploy but not very energy efficient with oversized computing servers for the most part, and not very resilient in case of data transmission failure. The trend is therefore to implement processing algorithms as close as possible to the sensors in order to reduce the utilization rates of communication systems, offload the computational servers by reducing their energy consumption, and improve the resilience of these sensor networks. Based on this observation, it remains to be understood how a data processing task initially carried out by servers with no power and computing power constraints can be offloaded onto a local sensor network with limited available energy and reduced computing power (e.g. low-power microcontrollers). To this end, methods used in the field of compressive sensing and machine learning algorithms can be applied in the compressed space. The core of the thesis will thus focus on the minimization of hardware and firmware energy consumption of embedded electronic systems implementing artificial intelligence and aiming at the application "predictive maintenance for industry". Research questions and associated innovations will be targeted: (i) the development of low-power electronic architectures (wake-up functions, adjustment of measurement frequency, ...), (ii) the development and implementation on microcontrollers of Machine Learning algorithms for sensor functions (audio, vibration, temperature) and (iii) the development and implementation on microcontrollers of predictive Machine Learning algorithms for the optimization of energy and autonomy. A complete electronic device (hardware + firmware) implementing these innovations and deployed in a real environment is expected by the end of the thesis.

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SOI vertical diodes for LWIR detection

Département d'Optronique (LETI)

Laboratoire d'Imagerie thermique et THz

01-09-2021

SL-DRT-21-0313

patrick.leduc@cea.fr

Photonics, Imaging and displays (.pdf)

Uncooled thermal detectors absorb the infrared flux in wavelength range from 7µm to 14µm. This corresponds to an atmospheric transmission window and to the maximum emission of a blackbody at 300K, which enables to measure temperature variations of less than 100mK. The operating principle of microbolometers is based on the temperature measurement of a suspended membrane absorbing the infrared flux. The thermal transducer is the sensitive element of the microbolomètre, which determines its signal-to-noise ratio and therefore the performance of the bolometric pixel. Most commercial microbolometers use a thermistor with amorphous silicon or vanadium oxide for its high temperature coefficient (TCR = 2-4% / K) and low flicker noise (1/f noise). The thesis proposal deals with a breakthrough technology for microbolometers. Unlike conventional thermistor detectors, the student will examine the use of SOI vertical diodes as transductor. The topic will focus on characterizing and modeling the performance of such a device.

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Design and fabrication of GeSn based components for environmental detection

Département d'Optronique (LETI)

Laboratoire des Capteurs Optiques

01-10-2020

SL-DRT-21-0315

vincent.reboud@cea.fr

Photonics, Imaging and displays (.pdf)

One of the main challenges for silicon photonics is an integrated laser technologically compatible with microelectronic foundries. Traditional, standalone semiconductor lasers use III-V semiconductors that are not accepted in the silicon foundries, contrary to the group-IV semiconductors. CEA Grenoble is among only few labs that already demonstrated mid-infrared optically pumped lasing in group-IV semiconductors, both in Ge and GeSn. With fully relaxed or tensile-strained heterostructures and quantum wells made of silicon-germanium-tin alloys (Si)GeSn, today we target continuous lasing at room temperature and efficient photodetectors in 200 mm wafers. To reach room temerature lasing, we need to improve the optical gain and optimize the carrier confinement. The improvements will require a redesign of the quantum wells and heterojunctions in germanium tin, through playing with atomic compositions and the mechanical strain at the micro-nanoscopic scale. Like the lasers we already demonstrated, the designed (Si)GeSn layers will be epitaxially grown at the main 200 mm CMOS fab facility of CEA Leti, and further fab-processed by the PhD candidate in smaller-scale clean rooms. Laser developments will be used to realize efficient GeSn photodetectors. The objectives of the research will be: (i) to reduce the number of crystalline defects in the GeSn gain regions, (ii) to design efficient (Si)GeSn stacks that confine both electrons and holes, while providing strong optical gain (iii) to apply and control tensile strain in germanium tin layers, (iv) to evaluate the optical gain under optical pumping and electrical injection, at different strains and doping levels, (v) to design and fabricate laser cavities with strong optical confinement (vi) to obtain germanium-based group-IV lasers that are tunable and lase continuously. (vii) to test fabricated devices (light sources and photodetectors) in gas detection cells On a longer term, such lasers will be widely used in ubiquitous miniaturized, low-power devices for optical gas sensing and environmental monitoring. This work will imply contacts with foreign labs working on the same vibrant topic.

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Study and Integration of Monolithic GaN Cascode Transistor

Département Composants Silicium (LETI)

Laboratoire Composants Electroniques pour l'Energie

01-10-2021

SL-DRT-21-0326

julien.buckley@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

LETI is currently transferring an AlGaN/GaN power electronics technology on 200mm silicon wafers to a renowned industrial partner in the field of power electronics devices (silicon, SiC). Gallium nitride-based (GaN) power electronics transistors can have either a normally-off (e-mode) or normally-on (d-mode) operation mechanism. For security reasons, there is a preference for e-mode devices. There are three main types of methods to obtain such functionality: either by using a p-type GaN gate, a conduction channel that includes a MOS stack (metal, oxide, semiconductor) or a cascode architecture (by assembling an e-mode and a d-mode device). The cascode architecture for GaN-based devices is today highly successful as it can be driven with similar strategies than the ones used for more traditional silicon parts and because of its good reliability. The work of this PhD will consist in conducting a study aiming to optimize the design of the device and identify its key technological steps (epitaxy, deposition, lithography, implantation...) necessary to its fabrication, followed by the coordination of the tasks necessary to its processing in LETI clean rooms. An analysis and interpretation of the obtained electrical measurements will be performed by using finished element simulations (TCAD using Synopsys environment).

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Diagnostic and prognostic tools for inverters and PV modules using machine-learning approaches

Département des Technologies Solaires (LITEN)

Laboratoire des Systèmes PV Appliqués

01-09-2021

SL-DRT-21-0347

sylvain.lespinats@cea.fr

Solar energy for energy transition (.pdf)

Framework: In the current context of climate change, the issue of energy is central from a societal point of view and from a political or economic point of view. Solar production, which is a renewable alternative to carbon-based energies, is growing exponentially and this rise in power will probably continue in the years to come. One of the best ways to lower the financial and environmental cost of solar power plants is automatic diagnostics, which can detect and correct plant failures and thus increase their performance. Basically, photovoltaic power plants are made up of modules connected to an inverter. The modules produce direct current which is converted into alternating current by the inverter for transport on the distribution network. The failures and aging of these devices are the main source of non-trivial failures. For example, the lifetime of a power plant is generally estimated at 20 or 30 years, to be compared to only 10 years for an inverter. It is very common for the current and voltage upstream and downstream of the inverter to be monitored. These data are generally supplemented by meteorological measurements (irradiance and temperature in particular). These data are however under-exploited. In the case of the behavior of the modules, it is mostly due to the strong correlation with various factors including daily and seasonal phenomena, weather conditions, relative position of the sun, non-linear interactions between the different modules, aging continue, break, etc. In the case of inverters, the difficulties are mainly due to the strong dependence on the operating conditions and on the noise level of the measurement largely higher than the signal (as encountered in the context of the detection of gravitational waves by the LIGO project). Objective: From these data we want to provide a close monitoring of photovoltaic plants, diagnose failures and anticipate them. In that goal, based, on the one hand, on the very large amount of data which can counter the signal-to-noise problem, and on machine-learning on the other hand, we will isolate the different explanatory components. Firstly, the modules and inverters will be considered separately. Secondly, we will consider the system as a whole. In the past, the LSPV (CEA) and LAMA UMR 5127 (Savoie Mont Blanc University) laboratories have collaborated on the development of dimensionality reduction methods. These methods (probably to be adapted) make it possible to explore the datasets in order to extract behaviors that can be linked to various modes of operation and aging. This step will allow definoing classes for regression / classification methods. The final goal is a diagnostic tools deployable onto power plant monitoring systems. Desired profile: We are looking for a student in mathematics interested in applications in the field of renewable energy and electronics or a student in engineering sciences passionate about mathematics. Experience in electronics is not necessary, but the candidate may operate measurements in laboratory under the supervision of electronics and photovoltaic engineers to produce data or confirm behavior. The tools used may include dimension reduction methods, statistics (descriptions and tests), time series analysis, SVMs, neural networks or tensor methods.

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Optomechanical reference oscillators

Département Composants Silicium (LETI)

Laboratoire Composants Micro-Capteurs

01-09-2021

SL-DRT-21-0351

marc.sansaperna@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

Reference ocillators (clocks) are devices that generate signals with a very precise frequency, generally defined by the vibration of a mechanical element at resonance. Nowadays, they are ubiquitous elements in electronic circuits: for example, a smartphone or tablet can contain up to seven reference oscillators. However, the appearance of new technologies such as 5G or autonomous vehicles requires a level of performance that is not attainable by commercial clock technologies. One of the most promising routes to improve performance is the development of clocks based on micro-electromechanical (MEMS) resonators at high frequency (1-5 GHz, tens of GHz in the future). However, building high-performance MEMS resonators in the GHz range is highly challenging, mainly due to the difficulty of detecting their minuscule vibration amplitudes. One promising solution is to use optomechanical detection, using the same principle as gravitational wave detectors but integrated at nanometric scale. This technology, now well mastered at Leti, can be combined with the integration with piezoelectric materials to increase the attainable signal levels. This principle, recently demonstrated by several fundamental research groups, is now mature enough to evolve towards applications, and solves many of the difficulties involved in the implementation of MEMS clocks in the GHz range. The objective of the thesis is to develop a MEMS clock based on this novel optomechanical technology. The thesis will take place in the Microsensors Laboratory of the CEA-Leti, in collaboration with the RF Components Laboratory. The Leti is a pioneer in the implementation of on-chip optomechanical and piezoelectric resonators. The PhD student will work in collaboration with Leti researchers to design the MEMS resonators and their fabrication process, based on an analytical study and finite-element simulations. Then, the student will have the opportunity to contribute to the fabrication of the devices in clean room. Finally, the student will characterize them in the Leti's laboratories, to extract their performance and implement a first demonstrator of optomechanical MEMS clock. The candidate will have a M.Sc. or equivalent degree, with a formation as a generalist engineer or physics, and a specialization on semi-conductor physics, nanotechnology, optics or a closely related field.

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Scaling evaluation of ultra-low power BEOL integrated HfO2-based ferroelectric memory arrays towards 28nm node

Département Composants Silicium (LETI)

Laboratoire de Composants Mémoires

01-10-2021

SL-DRT-21-0362

laurent.grenouillet@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

The recent discovery of ferroelectricity in HfO2 thin films generates a strong interest in integrating this CMOS-compatible and scalable material in ultra-low power ferroelectric memories and neuromorphic circuits. Within the last 6 months excellent results were reported on HfO2-based ferroelectric capacitors integrated in the Back-End Of Line of 130nm CMOS, confirming their potential for non-volatile memory applications. In this context, HfO2-based ferroelectric capacitors will be fabricated and electrically characterized to assess their potential to be scaled towards 28nm node. The candidate will perform advanced electrical characterization on state-of-the-art TiN/doped HfO2/TiN single capacitors with different areas, as well as 16kbit FeRAM arrays. Remanent polarization, coercive field, and imprint values will be extracted as a function of cycling (endurance) and temperature (data retention) for various pulse voltages/durations. Based on array characterization where large statistics is available, the physical mechanisms responsible for the reliability issues will be investigated. The results will be used to optimize the capacitor electrical properties to further design low voltage, ultra fast, scaled FeRAM memory arrays integrated within 28nm FDSOI node.

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Improving Side-channel based instruction disassembling

Département Systèmes (LETI)

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-09-2021

SL-DRT-21-0375

thomas.hiscock@cea.fr

Cyber security : hardware and sofware (.pdf)

Side-channel based disassembling is a family of side-channel attacks that strive to recover instructions executed by a processor from some of its physical emanations. Power consumption or electro-magnetic (EM) field are the most widely exploited sources of leakage. From a security designer perspective, knowing the best possible attacks is mandatory to secure a product. Le LSOSP laboratory is very active of this topic. In 2019 it proposed a new approach for performing side-channel based disassembling called mono-bit reconstruction, which was proved to be very effective on small microcontrolers. The main goal of this PhD is to study whether (or not) such attacks are possible on complex cores, such as processors found on smartphones. We will study how the complex microarchitecture of recent processors affect the leakages (Power or EM)? And how can we still extract some information from it? The latter will require to develop machine Learning Tools to recover information from very noisy measurements. At the end of the PhD, we hope to have a better understanding of the side-channel disassembling and some reflexion on countermeasures that would mitigate them.

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Advanced carrier recombination characterization for AlGaN/GaN HEMT, stack understanding from epitaxy to etching

Département des Plateformes Technologiques (LETI)

Laboratoire Analyses de Surfaces et Interfaces

01-09-2021

SL-DRT-21-0377

lukasz.borowik@cea.fr

Advanced nano characterization (.pdf)

To penetrate into the power electronics market, the main challenges for GaN remains the development of a reliable normally-off HEMT solution. CEA-LETI has chosen to develop recessed hybrid MISHEMT, fabricating normally-off devices which give functionality similar to a classic silicon based MOS. Since etching of AlGaN/GaN MISHEMT heterostructure can induce defects, it is critical to be able to characterize them in order to optimize gate processing and therefore overall device performance. Work will consist of: (1) CL and KPFM characterization realized and interpreted in term of radiative/non radiative carrier recombination for understanding of integration processes impact. Already optimized during previous internship sample preparation for correlated characterization will be refined for MISHEMT samples. (2) KPFM-CL correlation for a deep understanding of carrier dynamic in the gate stack (3) Correlation with electrical performances of theses devices will be performed. Instrumentation, besoins spécifiques: LETI owns all necessary equipment (CL and KPFM under illumination) for this thesis. Additionally, time-resolved CL is currently in PFNC investment road map and could be an interesting improvement during the third year of this PhD thesis.

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Near-field focusing techniques in inhomogenous media at millimiter wave

Département Systèmes (LETI)

Laboratoire Antennes, Propagation, Couplage Inductif

01-10-2021

SL-DRT-21-0378

antonio.clemente@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

In a huge number of applications such as wireless power transfer (WPT), microwave imaging, industrial control, etc., it is required to collimate, form or focus the electromagnetic radiation in a specific region of the space. Sometimes, this region could be located in the near-field region of the radiating element or surface. In this case, it is referred to as a near-field focused system. With the development of the future ?Beyond 5G? and 6G communication systems, the necessity to focus the radiating beam in the near-field region could be also required in the case of the reconfigurable intelligent surfaces (RIS). These kind of devices, when composed of reconfigurable elements, can be deployed to manipulate the electromagnetic waves and dynamically control and adjust the properties of the propagation channel. Eventually, near-field focusing could be also applied to future medical imaging systems at microwaves. These devices require focusing and collimating the electromagnetic energy in the human body tissues in order to diagnose, monitor and/or treat specific pathologies. In this context, near-field focusing can be used to improve the resolution of the imaging system by optimizing the energy transfer/transmission. The first objective of this thesis is to develop specific numerical tools for the synthesis, design and optimization of near-field focused systems in non-homogeneous media. These techniques will be developed by considering the electromagnetic properties of the media. The synthesis of the aperture field will be done considering modal expansion of the field and the potential vectors theory. After this phase, the synthesis and optimization procedures will be used to design a near-field focused antenna system operating at millimeter and/or sub-THz frequencies (30 - 300 GHz). These antennas will be manufactured and characterized in near-field test ranges. Measurements will validate the developed models for flat radiating apertures in specific scenarios. The possibility to perform measurements in a real applicative context (e.g. cancer detection) will be also considered.

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Lensless imaging and artificial intelligence for rapid diagnosis of infections

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Systèmes d'Imagerie pour le Vivant

01-10-2020

SL-DRT-21-0380

caroline.paulus@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The objective of the thesis is to develop a portable technology for pathogen identification. Indeed, in a context of spread of medical deserts and resurgence of antibiotic-resistant infections, it is urgent to develop innovative techniques for rapid diagnosis of infections in isolated regions. Among optical techniques for pathogen identification, lens free imaging methods draws attention because they are the only ones currently able to offer simultaneous characterization of a large number of colonies, all with low-cost, portable and energy-efficient technology. The objective of the thesis is to explore the potential of lensless imaging combined with artificial intelligence algorithms to identify bacterial colonies present in a biological fluid. The thesis will aim to optimize the sizing of the imaging system (sources, sensors) and to study image processing and machine learning algorithms necessary for colony identification. Two cases of clinical applications will be studied.

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Multiphysical design of high-voltage power semiconductor modules for renewable energy conversion

Département des Technologies Solaires (LITEN)

Laboratoire Systèmes PV

01-09-2021

SL-DRT-21-0387

jeremy.martin@cea.fr

Solar energy for energy transition (.pdf)

Research and development around silicon carbide (SiC) power semiconductors provides samples that can withstand voltages up to 15kV. These devices switch at very high speeds (e.g. 120kV / µs for a 10kV SiC MOSFET or 180kV / µs for a 15kV SiC IGBT). Overall, the performances of these semiconductors are exceptional, and drastically reduces the switching losses compared to Silicon equivalents. The implementation of these switches is on the other hand very delicate and calls upon methodologies of multiphysics design in transversal disciplinary fields. It is, from the scientific literature addressed a number of scientific and technological obstacles that we can list: -Minimization of parasitic inductors of power modules (<5nH) -Integration of EMC shielding to collect disturbing impulse currents -Cooling of SiC chips so the size is very small compared to a Si equivalent -Management of partial discharges and dielectric materials -Influence of dV / dt on the aging of materials (in DC, at 50Hz, and in pulse) -Reflection phenomena (electromagnetic wave) The proposed work consists of studying and proposing a power module architecture integrating innovations making it possible to address the implementation of SiC chips up to 10kV. The teams from the CEA in Toulouse specialists in high power 3D packaging will provide their skills in assembly technologies for the production of complex power modules. The CEA teams at INES campus (Nat. Inst. of Solar Energy)located at the Bourget du Lac (Savoy) will provide their high voltage measurement and prototyping means as well as their knowledge in power module design (finite element simulation). Researchers from G2ELAB in Grenoble in cooling of power modules and dielectric science will use their knowledge as well as their experimental platforms.

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Oscillating neurons for computational optimization and associative memory

Département Composants Silicium (LETI)

Laboratoire d'Intégration des Composants pour la Logique

01-10-2021

SL-DRT-21-0393

louis.hutin@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Hopfield networks are a type of recurring neural network particularly well-suited to content-addressable associative memory functions. By giving its elements the ability to fluctuate at will, they can be adapted to efficiently solving NP-hard combinatorial optimization problems. Such problems, for which finding exact solutions in polynomial time is out of reach for deterministic Turing machines, find many applications in diverse fields such as logistic operations, circuit design, medical diagnosis, Smart Grid management etc. The frame of the proposed project is the search for hardware accelerators for Artificial Intelligence. In particular, we consider the use of injection-locked oscillators as neurons (ILO). The goals will be the design, fabrication and demonstration of such networks, featuring binary phase-encoded neurons coupled by adjustable synaptic weights, to carry out associative memory (e.g. pattern recognition) or combinatorial optimization tasks (ex: max cut, graph coloring,...).

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Synthesis and study of chiral organic materials for charge transport in organic semiconductors

Département d'Optronique (LETI)

Laboratoire des Composants Emissifs

01-10-2021

SL-DRT-21-0395

benoit.racine@cea.fr

Photonics, Imaging and displays (.pdf)

The detection and manipulation of the polarized light is very attractive, in particular because of the interest in using circularly polarized light (LCP) in many areas of societal importance such as technologies display, information transmission, cryptography, bio-medical imaging or even the detection of chiral molecules of pharmaceutical interest. Due to their ability to interact specifically with an LCP and to modulate its polarization, chiral molecular materials stand out as an element of choice for exploring these innovative applications and considering new potential in organic electronics. In addition, the specific property of chiral molecules to induce electronic spin selectivity in the conduction of electric current (CISS effect for Chiral Induced Spin Selectivity) also opens up opportunities in the field of organic spintronics. Consequently, the synthesis of innovative pi conjugated chiral semiconductors, presenting an easy modulation of their physicochemical properties and the integration of these materials in optoelectronic devices of the OLEDs, OPDs or OFETs type is of interest both fundamental and 'application. The thesis project will be done in collaboration with a CNRS chemistry laboratory in Rennes, France, and the LCEM laboratory (at CEA / LETI, Grenoble, France) specialized in organic semiconductors. The objectives of the thesis student will be to synthesize new chiral organic charge transporters and to characterize their photophysical (absorption and emission) and opto-electronic properties. The most promising molecules will be integrated into OLEDs and OPDs devices. The photophysical synthesis and characterization part (circular dichroism spectrometer, non-polarized and circularly polarized luminescence spectrometer, PER, etc.) will be carried out at the CNRS chemistry laboratory. The integration of molecules in OLEDs and OPDs devices will be done in the LCEM laboratory where the deposition equipment (PVD chamber for organic materials) and the opto-electronic characterization means (IVL, C (V), TLM, Photocurrent, hall effect, etc.).

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Study, evaluation and validation of the performance of a boron measurement system using neutron absorption

Département Métrologie Instrumentation et Information (LIST)

Laboratoire Capteurs et Architectures Electroniques

01-10-2021

SL-DRT-21-0397

adrien.sari@cea.fr

The concentration of boron in the primary-circuit fluid of a nuclear reactor must be finely controlled in order to guarantee its safety. Indeed, an excursion of the boron concentration could lead to a risk of criticality. An online nuclear-measurement system is therefore required to monitor the boron concentration in the primary reactor fluid. Such a system is commonly referred to as a "boronmeter". The proposed thesis subject is made up of three lines of research. The first line aims to study by Monte Carlo simulation, and then conceptualise and theoretically formalise the behaviour of the two main performance criteria (counting rate and contrast) of the boronmeter under the influence of its different characteristics. The second line of research aims at evaluating and experimentally validating the interpretation of the effects brought into play within the boronmeter and the theoretical concepts formulated. This experimental work will be carried out in close collaboration with the Laboratoire National Henri Becquerel (LNHB). The third line of this thesis aims to conceive an innovative boronmeter designed to measure the boron concentration in the primary fluid as close as possible to the core of the nuclear reactor. Such a system would make it possible to identify as quickly as possible an anomaly in the boron-concentration value at the reactor core. However, the constraints imposed by such a measurement environment will have to be taken into account, and a suitable measurement methodology will be developed. Different approaches to temperature and fluid-flow compensation will be the subject of in-depth investigations.

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Deep Wireless Localization based on Artificial Intelligence for Challenging Environments

Département Systèmes (LETI)

Laboratoire Communication des Objets Intelligents

01-10-2021

SL-DRT-21-0398

benoit.denis@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

Various low-cost wireless localization technologies ans standards have emerged in recent years (e.g. UWB/IEEE802.15.4z standard, GPS RTK, cellular radio in millimeter wave bands...), fulfilling the needs of a variety of location-based applications and services (e.g., sustainable mobility and intelligent transport systems, smart cities, industry 4.0, cyber-security, etc.). However, despite the good theoretical performances of these systems, radio obstructions and multipath propagation degrade in practice both localization accuracy and continuity (e.g. vehicular navigation in urban canyons, indoor assets or pedestrians localization in dense industrial environments...). In the frame of these new PhD investigations, we propose to evaluate and demonstrate the promising potential of Artificial Intelligence, and more specifically, of advanced (deep) machine learning tools, to assess the richness and the complexity of received radio signals from a specific localization standpoint. Typically, one aim would be to benefit from the « hidden » location-dependent information contained in received mulitpath multi-link signals under user mobility. In constrast to conventional correction approaches based on a priori parametric models, which are most often too simplistic and hard to calibrate, we will thus consider learning and generalizing the fundamental non-linear relationships linking key location-dependent features (i.e., extracted out of high-dimension input received signals) and localization descriptors (e.g., relative/absolute position, speed, orientation, visibility conditions?). Accordingly, so-called « deep » localization strategies will then be developped, enabling the prediction, detection and/or completion of erroneous/missing location attributes, directly in terms of positioning and tracking at the system level (i.e., without requiring intermediary and independent link-wise correction steps). The designed learning architectures and localization approaches will be fed and validated by means of large radio databases, including both field measurements collected with real radio devices and synthetic data based on determinsitic prediction tools (e.g., ray-tracing).

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Quantum computing for optimization on NISQ computers

Département Systèmes et Circuits Intégrés Numériques

Laboratoire pour la Confiance des sYstèmes de calcuL

01-10-2021

SL-DRT-21-0400

stephane.louise@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

Today's quantum computers are still far from the ideal case scenario that where though of by the first contributors of quantum computing: they are still tiny (a few dozens of qubits at best), noisy, imperfect. These are now known as NISQ computers or Noisy Intermediate Scale Quantum devices. Being tiny and noisy however does not mean they are worthless, and as they will be the dominant kind of quantum computing devices for the foreseeable future, it is of great value to investigate what would be possible to implement on these new kind of computer in the case of optimization problems, especially in the case of so-called "hybrid algorithm" for which the NISQ computer is considered as a quantum accelerator within a more standard processing implemented otherwise on a standard computer. In this PhD thesis we will investigate the limits of the first NISQ computers publicly available (either real hardware or simulators) and how to use despite their limitations within an optimization algorithm.

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High-effiency power hub for energy transition

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Electronique avancée, Energie et Puissance

01-10-2021

SL-DRT-21-0403

xavier.maynard@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

This subject addresses the scientific developments needed to design a power hub allowing, in a single stage of power electronics, to manage all the household energy flows: photovoltaic supply (...) , storage including the battery of electric vehicles (V2G), connection to the network (smart grid), etc. Previous works at CEA have already dealt with advanced high-efficiency high-frequency converter topologies, in particular using GaN components. We propose to go further, by studying the coupling of various energy sources and receivers using a single-stage converter. The design of the converter should take into account all parasitic components, and as far as possible minimize them. This approach is based on simulation (LTspice and / or Ansys Q3D) and testing tools allowing the development of a system with high efficiency. The purpose of the study will be the realization of the complete system integrating as far as possible an active filter for EMC.

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Lithography process for 3D high-resolution patterning

Département des Plateformes Technologiques (LETI)

Laboratoire

01-09-2021

SL-DRT-21-0409

jerome.reche@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Since 1960 the CEA-LETI (laboratory of electronics and information technology) is ones of main contributor of French innovation is electronics and new technologies. Its different entities are a real bridge between research and industry. One of them, the DPFT (technological platform department), includes the resources of manufacturing, the control and the associated environment, which allows to set up and to mature new processesto develop the future of electronics. Use of 3D structures to replace planar structures is one way to achieve this plan. Nevertheless, the current 3D structures, which are made and replicated, as microlens used in photonic field, use process scale for micrometer size and the new needs target sub-micronics size. The replication technology as high-resolution nanoimprint could adress this scaling challenge with yield improvement (time and cost reduction). The nanoimprint technology allows replication of 3D structure in one process step inside a functional material, this mean that the material imprint is the final use for application and not an intermediate one. The final aim of the thesis is the realization of 3D structures on a sub-micrometric scale (100 nm to 1 µm) and their replication. This involves firstly the creation of such structures using known but slow technology such as electron beam lithography associated with the transfer techniques in hard materials. Moreover, it will be necessary to characterize these structures at each stage in order to know their precise shape. In a second step, the candidate will be able to try to replicate these patterns with the laboratory nanoimprinting equipment and the various materials and processes already developed in the lab. The replicated structures will be finely characterize to evaluate morphological modification, defectivity obtained or possible non-uniformity. From these results, the candidate will have to implement a detailed analysis potentially associated with design of experiment (DOE) and the use of modeling to adapt the process and the starting structures to obtain the expected replication. The thesis contract will take place over 3 years with a gross monthly salary of 2 043.54? during the 1st and 2nd years, and 2 104.62? for the 3rd year. At the end, the skills developed by the PhD student enable him to work in many high technology sectors such as nano and microelectronics, materials chemistry or more generally data processing field.

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New physical layer on millimeter wave band for 5G-NR IoT

Département Systèmes (LETI)

Laboratoire Communication des Objets Intelligents

01-10-2021

SL-DRT-21-0410

valerian.mannoni@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

A new 5G air interface is to be designed, in order to address good reliability and acceptable latency service for IoT use cases not addressed yet by Cellular IoT technologies. This new 5G air interface is the subject of a study item in 3GPP release 17 and has been called NR_REDCAP (Reduced Capability NR devices). The ability to operate NR-Light on millimeter wave band is seen as required for Industry 4.0 applications and attractive for private networks due to its limited range and high spatial reuse. The objective of the PhD thesis is then to propose and investigate a new physical layer on millimeter wave band for 5G-NR IoT meeting the above challenges. The expected results are: - A better understanding of challenges and key enablers of 5G NR in millimeter wave band - Proposal of a new physical layer for 5G-NR IoT with the associated MIMO scheme - Proposal and study of the multiple access scheme based on MIMO - Identification and assessment of key NR-Light enablers in millimeter wave band to fulfill these requirements and reach the reduced complexity and cost target of NR-Light UEs while mitigating the performance degradation of such complexity reduction, for example coverage degradation.

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Superconductor Integration for thermal management of quantum computing and spatial multi-chip platforms

Département Composants Silicium (LETI)

Laboratoire Packaging et 3D

01-09-2021

SL-DRT-21-0411

jean.charbonnier@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

As part of Quantum Silicon Grenoble project, teams at CEA-LETI, CEA-IRIG and Néel Institute aim at building a quantum accelerator with silicon spin quantum bits (qubits). Compatible with large-scale production, existing integration processes on Si are a real advantage for the scalability of these qubits. The extreme qubit operating conditions (cryogenic temperatures =1K, high frequencies in the range of a few GHz, high signal density) require the development of adapted technological building blocks. To interconnect the qubits and the controlled circuits, integration of superconducting metals is promising. Indeed, their vanishing resistance at low temperatures and the low thermal conductivity of superconductors also enables to protect the qubits from the heat generated by the control electronics circuits integrated close-by. Note that these developments will also benefit spatial applications sharing similar operating constraints. The thesis will focus on: 1) Studying the superconducting properties of Nb, NbN, TiN, Al and any combination of these materials during integration processes to optimize them for a single level of routing and multilayers pads. Establishing low temperature compatible thermal conductivity measurement set-up, protocol and sample design. 2) Transferring the acquired knowledge in term of integration and thermal conductivities to develop the next generation of multi-chip platform hosting qubits and control electronics circuits. The PhD student will be part of the 3D integration and packaging lab of CEA-LETI (Grenoble) and will interact very closely with the Spectral-imaging laboratory for space science at CEA-IRFU (Saclay) for thermal conductivity measurements.

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Wearable dynamic fluidic chamber dedicated to transcutaneous monitoring of oxygen and carbon dioxide blood concentration

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Systèmes Pour la Personne

SL-DRT-21-0415

rodrigue.rousier@cea.fr

Health and environment technologies, medical devices (.pdf)

The development of wearable medical devices is a fundamental and essential in order to promote ambulatory medicine. So-called "conventional" as opposed to outpatient medicine commonly uses blood gas analysis to assess the efficiency of pulmonary exchanges and diagnose respiratory diseases. In particular, it detects an abnormal change in the oxygen and carbon dioxide concentrations in arterial blood going to the tissues. Since this analysis requires a blood test, it is therefore an invasive method and does not allow monitoring of concentrations in real time. An alternative to taking blood is a transcutaneous gas analysis, i.e. measuring the concentrations of gases that diffuse through the skin. This method is non-invasive and guarantees continuous monitoring of blood gases. The objective of this thesis is to study and develop an instrumented wearable dynamic fluidic chamber. This chamber will measure in real time the concentrations of oxygen and carbon dioxide which diffuse through the skin. The work will consist in modeling the gas exchanges between the skin and the fluidic chamber, then designing and instrumenting the chamber and finally testing it on a gas test bench. This subject requires a highly motivated person with skills in simulation, medical device design and instrumentation.

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Elastic wave sensors for field biological detection

Département Composants Silicium (LETI)

Laboratoire Composants Radiofréquences

01-09-2021

SL-DRT-21-0437

alexandre.reinhardt@cea.fr

Health and environment technologies, medical devices (.pdf)

Monitoring of the sanitary quality of water becomes increasingly a public health issue. In this context, CEA-LETI is developping sensors to detect bacteria in liquid samples. Among the technologies under investigation, electromechanical elastic wave sensors appear as particularly promissing. The aim of this PhD is to evaluate the use of such components, initially developped for radiofrequency signal processing, to biological detection in liquid samples. More precisely, the PhD subject proposed aims in a first stage at analysing the biological structures we want to detect, their possible interactions with a sensors and the associated detection mechanisms which could be exploited. This will allow the design of suitable sensors, by selecting the type of resonator, the vibration mode leading to the highest sensitivity and compatible with operation in liquids, and a scheme for the electronic readout of the sensor output. The candidate will then fabricate prototypes in the CEA-LETI clean rooms and will functionalize them and evaluate their performance in the laboratory. Ultimately, the sensors will be adapted so that they can be integrated in a multi-sensors detection platform developped in parallel by the CEA-LETI teams.

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Training and quantization of large-scale deep neural networks for transfer learning

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Intelligence Artificielle Embarquée

SL-DRT-21-0446

johannes.thiele@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Training and quantization of large-scale deep neural networks for transfer learning Transfer learning is today a common technique in Deep Learning that uses the learned parameters of a generic network (a feature extractor) to accelerate the training of another network on a more specific task. This specialized network is subsequently optimized for the hardware constraints of the specific use-case. However, given that the representations of the feature extractor are often rather generic, it might be possible to optimize the parameters before the transfer, to avoid that each end-user has to perform this optimization by herself. In this context, the thesis has the following scientific objectives: - Using several ?unsupervised? learning methods (self-supervised, weakly supervised, semi-supervised) to train feature extractors on large datasets - Studying how common optimization methods (in particular quantization) can be applied on these extractors in a ?task-agnostic? fashion - Quantifying the influence of these optimizations on the transfer learning capacity, by benchmarking and theoretical analysis (e.g. information compression theory) Required competences: Master degree (or equivalent), machine learning (in particular Deep Learning), programming (Python, Pytorch, Tensorflow, C++), good English (French knowledge is not required, but helpful)

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Preserving temporal properties while dynamic reconfiguration of Cyber Physical Systems

Département Systèmes et Circuits Intégrés Numériques

Laboratoire pour la Confiance des sYstèmes de calcuL

01-09-2021

SL-DRT-21-0454

selma.azaiez@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

A 3-year PhD position is available in the List Institute of CEA (the French Alternative Energies and Atomic Energy Commission) to explore dynamic reconfigurations in Cyber Physical Systems with the constraint of preserving temporal properties to insure system safety. Cyber Physical systems are distributed and highly heterogeneous systems used in modern applications for different domains such as autonomous automotive, smart manufacturing, aeronautic, energy, etc. Such systems must obey to temporal properties such as latency or throughput that shall guarantee a correct behavior. CEA LIST teams are using formal models based on MoCCs (Models of Computation and Communication) to specify, analyze and validate such systems while applying them in a wide variety of fields. A static analysis would generate the initial configuration of the system respecting a given latency or throughput. Real-time monitoring would validate these properties during system execution. If deviations are detected, a dynamic reconfiguration of the system will be proposed that would utilize artificial intelligence algorithms as bases. This subject is important in various fields of applications: the autonomous automobile where the respect of the deadlines takes an important part in guaranteeing the safety of the system but also in fields such smart manufacturing where the production lines are brought to be easily reconfigurable while respecting throughput properties. The position is available at CEA Saclay Nano-innov at Palaiseau (near Paris), in collaboration with the DiverSE team at IRISA (Rennes). It will be supervised by Stéphane Louise (thesis advisor) and Selma Azaiez (co-supervisor). This position is dedicated to motivated students seeking for an ambitious topic and wishing to acquire experience in technological research related to industry. You must have an equivalent level of Master 2 with preferably a specialty in software engineering and / or operational research. Knowledge of formal methods as well as scheduling algorithms will help you achieve expected goals. Finally, you will have to present a good capacity for personal work, the ability to work in a team and a motivation for technical challenges.

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Situation awareness and task planning for a mobile manipulator in uncertain logistic environment

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire de Contrôle et Supervision Robotique

01-03-2021

SL-DRT-21-0459

eric.lucet@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

The proposed research project concerns the autonomous evolution of a mobile robot in a logistic context, for example an automated forklift truck. Based on an analysis of the situation, the system will have to be able to autonomously find the sequence of actions allowing it to move towards an object of interest, grasp it and place it in a predefined region. This must be done while avoiding collisions and possibly clearing the path to make possible the movement of the mobile base and gripper. In case of failure, the replanning inherent in the method must be able to find a new sequence of actions. It will thus be necessary to implement a statistical model of the current and future navigation situation in the proximity of a mobile robot equipped with a gripper system, as well as a task planning algorithm based on this model. The Situation Awareness model will be based on contextual data from the perception modules, the process and task models, the agents (robots and humans) present in the environment and their states, the intrinsic data of the robot and the geometric model of the environment. The detection of particular situations (anomalies, etc.) can be handled by data analysis and automatic learning algorithms, possibly with a training phase based on feedback and a priori knowledge. In particular, the Hierarchical Planning in the Now (HPN) approach integrates task and motion planning and deals with uncertainty. It avoids trying to find optimal solutions for the POMDP (which is insoluble), by constructing a deterministic approximation of the dynamics (model of the situation), establishing a sequential plan, and executing this plan while observing possible changes in relation to the expected results, and re-planning it when deviations occur. In addition, to deal with uncertainty about the current state, planning must be done within the belief space, which is the probability of distributions over the states of the world. Thus, based on preliminary work on this subject, an improvement of the hierarchical plan, as well as a better understanding and formulation of models of the modification of belief states resulting from these actions, will be investigated.

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Embedded autonomous incremental learning

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Intelligence Intégrée Multi-capteurs

01-09-2021

SL-DRT-21-0465

carolynn.bernier@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The recent development of incremental learning algorithms for deep neural networks is an opportunity to imagine new intelligent sensor applications deployed in real environments. By being incrementally able to learn new tasks, the sensor will be able to personalize its behavior to its specific deployment milieu, allowing it to adapt to slow variations of its targeted tasks (e.g. the detection of different types of anomalies) or learn new tasks that were not initially anticipated. This possibility would make the service rendered by the autonomous sensor more and more relevant. The objective of this thesis is the exploration of the means by which the intelligent sensor can become fully autonomous in its evolution while taking into account the limited processing capability of the embedded system. Also, seeing the limited power consumption of the platform, the idea is to associate two embedded systems, a first which is ?Always-on? and executes the nominal task of the application (e.g. the detection of different classes of events or anomalies), and a second which is ?On-demand? which would be executed now and then, in order to retrain the model of the ?Always-on? part. For coherence, it is necessary that the power consumption ratio of the two platforms be in a ratio of 1:100 to 1:1000 approximately. The challenges facing the design of such a system are many : The first is the design of detection mechanisms able to find false negative examples (slowly changing classes) as well as novel examples (new classes). These mechanisms must be executed on the ?Always-on? platform, with the associated implementation constraints. A second difficulty concerns the retraining phase which is executed on the ?On-demand? platform. This phase must take into account the structure of the ?Always-on? model in order to be able to retrain it with new examples. This both in order to slowly learn the modifications of the existing detection task or to learn a new task without forgetting the old ones. Since this a new application space, the PhD candidate must be able to have a wide understanding of the subject and will necessarily have to address a wide number of domains including different incremental leaning algorithms, different deep learning training algorithms, and the hardware requirements necessary for running these algorithms in the embedded context.

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Interconnection of ultra-thin electronic components in stretchable flex for medical application

Département Composants Silicium (LETI)

Laboratoire Packaging et 3D

01-10-2021

SL-DRT-21-0466

jcsouriau@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Developments in flexible systems integrating ultra-thin silicon components and sensors offer new perspectives of application to the medical world. Indeed, it is conceivable to functionalize wearable patches, which allow the monitoring of vital and/ or physiological parameters such as heart rate, blood pressure, oxygenation of blood, body temperature etc... An important issue is the robustness of these systems under mechanical constraint. Depending on the location on the human body, the patch will have to endure more or less important stretches. The electrical interconnections in the flex with the silicon components, which are not stretchable will then be strongly stressed. The CEA-LETI has recently developed a generic wafer manufacturing process for flexible labels including thinned silicon components below 50 µm. However, the chosen flexible material was not stretchable. Within the framework of this thesis, new stretchable materials, robust and compatible with a wafer level integration will have to be identified. One of the objectives will also be the development of stretchable interconnection based on a biocompatible elastomer. This interconnection must be locally conductive and sufficiently adherent to support the patch manufacturing process and the maintenance of the chips throughout its use. The PhD student will take into account the developments of the CEA-Liten on an interconnection inspired by the structure of the legs of the gecko. Finally, with a view to reusing the added high-value components and improving the recyclability of the patch, this interconnection must also be repositionable and reusable.

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Hydrogenation of Liquid Organic Hydrogen Carrier by electrochemical reduction

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des technologies de valorisation des procédés et des matériaux pour les EnR

01-10-2021

SL-DRT-21-0471

vincent.faucheux@cea.fr

Advanced hydrogen and fuel-cells solutions for energy transition (.pdf)

Hydrogen is expected to be the energy carrier of tomorrow due to the versatility of its ways of production and use. Nevertheless, its storage remains a major technological and scientific challenge. An alternative to the compression or liquefaction of H2 - energy-intensive and expensive processes - consists in storing and transporting hydrogen at atmospheric pressure and at ambient temperature (via existing infrastructures) using Liquid Organic Hydrogen Carrier (LOHC). These molecules can undergo reversible hydrogenation / dehydrogenation cycles in the presence of a catalyst. This technology therefore makes it possible to transport hydrogen from its production site (via electrolysis) to its site of use thanks to the these liquid molecules. A hindrance to the commercial deployment of this technology is in the energy efficiency of the whole process and the cost of the hydrogenation / dehydrogenation reactors. Indeed, hydrogenation / dehydrogenation reactions are highly exothermic / endothermic and require relatively high temperatures and efficient catalysts, often based on platinum group metal (PGM). In addition, the hydrogenation step requires the prior generation of H2 by electrolysis. The implementation of a direct hydrogenation of LOHC molecules at room temperature and pressure by electroreduction, would minimize the energy needs associated with this hydrogenation step, and would open the field of application of this LOHC technology.

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Development of advanced etch processes for new CMOS gate patterning

Département des Plateformes Technologiques (LETI)

Laboratoire Gravure

01-10-2021

SL-DRT-21-0472

aurelien.sarrazin@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

With quantum technology emergence, device architectures such as active and gate transistor are deeply modified. These nested structures impose a very high etch control to meet new device requirements. New challenges should be overcome to keep sub-20 nm pattern dimensions and also to increase material etch selectivity . To do so, we propose to develop Atomic Layer Etching (ALE) approaches. Thanks to these techniques, we should be able to multiply etch selectivity and to promote pattern shape fidelity by passivation and etch behavior dissociation. Characterization and mechanism understanding will help study evolution. Thus, we could be supported by numerous ways of characterization proposed by LETI's plaforms and a last generation plasma reactor. These studies take part of quantum development proposed by LETI structures for the next decade. Challenges, human and material support allow to propose comfortable conditions to lead these PhD program and to investigate result valorisation.

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Development of biofunctionalized photonic circuits for the analysis of volatile organic compounds at very low concentrations for environmental and medical applications

Département d'Optronique (LETI)

Laboratoire des Capteurs Optiques

01-10-2021

SL-DRT-21-0473

loic.laplatine@cea.fr

Health and environment technologies, medical devices (.pdf)

The identification and quantification of volatile organic compounds (VOCs) in the air is a crucial issue in many fields. The analysis of outdoor air makes it possible, for example, to monitor and control pollution linked to industry or motorway traffic. Likewise, the analysis of exhaled air allows the diagnosis of certain pathologies. This requires the ability to measure dozens of different VOCs at very low concentrations (ppb) in complex gas matrices. CEA Grenoble recently developed sensors using integrated silicon photonic circuits chemically functionalized by biomolecules capable of specifically capturing certain VOCs, similar to human olfaction. They are currently used for measuring odors. These biomimetic photonic sensors offer great potential in terms of miniaturization, improvement in sensitivity, multiplexing for the measurement of complex mixtures, and can be manufactured at low cost by methods derived from microelectronics. In particular, they make it possible to consider gas analyzes in situ and in real time. The thesis is positioned at the frontier of electronic noses and analytical systems and will aim at the design and instrumentation of an experimental device to improve the detection limit and identification. The thesis will be highly multidisciplinary and will include the design and characterization of integrated photonic circuits on wafers and chips, the design and characterization of microfluidic circuits, surface chemistry and biofunctionalization, as well as data analysis (classification, modeling, learning, etc?). We will explore certain applications at the end of the thesis, in particular on the analysis of exhaled air and the detection of atmospheric pollutants.

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Modelling and optimization of Ge on Si Separated Absorption Single Photon Avalanche Diodes

Département d'Optronique (LETI)

Laboratoire d'Imagerie sur Silicium

01-01-2021

SL-DRT-21-0477

norbert.moussy@cea.fr

Photonics, Imaging and displays (.pdf)

Advanced optoelectronic devices such as the single-photon avalanche diode (SPAD) are now widely employed in the fields of 3D imaging, camera assist, laser ranging and proximity. Next generation of SPAD will be devoted to time-of-flight 3D ranging and fast movement detection, notably for long LiDaR used in autonomous driving cars. The PhD work will consist in developing and exploiting home-made simulators for optoelectronic devices and more specifically, Ge separated absorption SPAD. In this type of sensors infrared light is absorbed in germanium and photogenerated carriers are transported into the silicon avalanche zone for signal amplification. A close understanding of the transport between the two materials is fundamental for optimization of the device. This will be done through simulation and calibrations of the models. First, process simulations of doping implantation, but also residual strain in the epitaxial Ge layer will be used to extract realistic doping profiles and hence inserted in the Monte Carlo (MC) code. Second, by using 3D particle MC simulation for solving the Boltzmann transport equation, the time behavior of different designs of Si- and Ge-based SPAD devices will be statistically analyzed in order to reduce the jitter and to enhance the photon detection probability. The MC technique is a unique tool to analyze single particle trajectories as well as the time evolution of terminal currents and voltages.

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Recycling of fluorinated polymers contained in new technologies for energy (NTE)

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des technologies de valorisation des procédés et des matériaux pour les EnR

01-10-2021

SL-DRT-21-0502

emmanuel.billy@cea.fr

Green and decarbonated energy incl. bioprocesses and waste valorization (.pdf)

Fluoropolymers are today very widely used for their mechanical and chemical properties and their durability. Polymers are unavoidable in the field of NTEs such as proton exchange membrane fuel cells (Nafion membrane in PEMFCs), batteries (PVDF at electrodes), or photovoltaic panels (EVA at the glass cell interface). With the advent of carbon-free technologies, the issue of recycling has become central to bringing these technologies to market. Historically, recycling processes were designed for processing different technologies and large volumes. This has led to the establishment of pyrometallurgical processes (high temperature) that are robust, but destructive and non-selective. In a context constrained by strategic, legislative (recycling rate) and environmental issues, it is necessary to recycle "more" and "better". This thesis aims at finding new wet or dry ways for the treatment of fluorinated compounds. The use of ionic liquids for the solubilization of polymers will be a preferred route. Their intrinsic physicochemical properties (very low volatility and flammability) make them ideal candidates for overcoming safety and environmental issues. The thesis work will be divided into three parts. Firstly, a state of the art will be realized for the evaluation of conventional processes and media for the treatment of fluorinated compounds. The state of the art will be tightened on the fluorinated polymers used in the field of new technologies for energy (NTE). A second part will deal with the chemistry of polymers and solvents in which a polymer can be dissolved. A third part of a fundamental nature will aim at linking the macroscopic results to the structural evolutions of the polymers.

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New materials to decrease CO2 capture energetic cost

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire Micro-Sources d'Energie

01-10-2021

SL-DRT-21-0503

arthur.roussey@cea.fr

Green and decarbonated energy incl. bioprocesses and waste valorization (.pdf)

Reducing CO2 emission is the main challenge of our generation. The transition towards low carbon energy sources will take time and CO2 capture, either at emission sources or directly from the atmosphere, is a mitigation solution currently in fast development. CO2 capture is a cyclic process, with a first adsorption step who removes CO2 from a gas stream, followed by a thermal regeneration step, which yields highly concentrated CO2, which can be reused or stored. However, when directly captured from the atmosphere (~ 400 ppm), this process has a high cost ((100-400?/tCO2),[1],[2] due mainly to the energy needed during the regeneration step (~1500 kWh/tCO2). The PhD thesis candidate will synthesize new polyamines and study their interactions with CO2 and water with the objective of reducing the energetic cost of CO2 capture and to improe their thermal stability. [1] K. Z. House, A. C. Baclig, M. Ranjan, E. A. van Nierop, J. Wilcox, et H. J. Herzog, « Economic and energetic analysis of capturing CO2 from ambient air », Proc. Natl. Acad. Sci., vol. 108, no 51, p. 20428, déc. 2011. [2] M. Fasihi, O. Efimova, et C. Breyer, « Techno-economic assessment of CO2 direct air capture plants », J. Clean. Prod., vol. 224, p. 957-980, juill. 2019.

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Qualification and quantification of GaN, InGaN and AlGaN surface states :

Département d'Optronique (LETI)

Laboratoire des Composants Emissifs

01-09-2021

SL-DRT-21-0515

David.Vaufrey@cea.fr

Photonics, Imaging and displays (.pdf)

GaN-based µLEDs seem promising for augmented reality (AR) or virtual reality (VR) applications. Indeed, they would make it possible to produce screens with resolutions and luminances that had not yet been achieved. But these µLEDs suffer from a lower efficiency compared to their larger sibling. A commonly accepted explanation for this efficiency degradation lies in the existence of numerous surface defects induced by pixel singularization etching. The smaller the dimensions of the LED, the more important the surface defects play in the electro-optical behavior. Their presence, if they are shallow, can facilitate electrical injection, on the other hand if they are deep, they contribute to the degradation of the electro-optic performances of devices such as LED. This thesis aims to quantify and qualify the surface defects in GaN, InGaN and AlGaN that make up GaN-based µLEDs. The doctoral student will have to carry out by himself all the stages of realization of new components necessary for this study, starting with the design of the photolithography masks, the realization of all the technological steps and finally the electro-optical characterizations such as DLTS (Deep Level Transient Spectroscopy), DLOS (Deep Level Optical Spectroscopy) or photocurrent. At the end, the doctoral student will have to identify the surface defects that are the most limiting for the efficiency of LEDs and the most favorable to the injection of electrical carriers. The thesis will be carried out in close collaboration with Ph Ferrandis (thesis director) from Néel Institute (CNRS), N. Rochat (co-supervisor) from CEA Leti (PFNC Nano Characterization Platform) and David Vaufrey (supervisor) from CEA Leti (LCEM Emissive Device Laboratory). The thesis grant would be fully funded by the CEA Leti in Grenoble for a period of 3 years.

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Ammonia synthesis from N2 and H2O using an electrochemical-chemical lithium cycling

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des technologies de valorisation des procédés et des matériaux pour les EnR

01-10-2021

SL-DRT-21-0522

Parviz.HAJIYEV@cea.fr

Green and decarbonated energy incl. bioprocesses and waste valorization (.pdf)

Hydrogen is a promising energy carrier if it is produced from renewable energy and stored / transported safely and at low cost. Ammonia has undeniable advantages for the storage of H2 with high energy densities (17.8% wt H2) and existing infrastructure for its distribution. Ammonia is produced on a large scale using the Haber-Bosch process under severe operating conditions (?450 ° C, ?200 atm). The hydrogen required for this process is produced from natural gas, emitting 3% of anthropogenic CO2. An alternative is to synthesize ammonia directly from renewable electricity using a lithium-based electrochemical-chemical cycle. This cycle involves different stages including the nitridation of Li (formation of Li3N), the hydrolysis of Li3N to generate ammonia, and finally the electrolysis of LiOH to regenerate Li and thus close the cycle. Setting up this cycle under moderate temperature / pressure conditions involves optimizing each steps in terms of kinetics and efficiency. Generating ammonia under these moderate conditions would greatly limit the ecological impact linked to this molecule.

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Predictive analysis, synthesis and validation of PGM free catalysts for a relevant decomposition of NH3 at lower temperature

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des technologies de valorisation des procédés et des matériaux pour les EnR

01-10-2021

SL-DRT-21-0523

jerome.delmas@cea.fr

Advanced hydrogen and fuel-cells solutions for energy transition (.pdf)

Hydrogen is expected to be the energy carrier of tomorrow due to the versatility of its ways of production and use. However, conventional storage solutions (under pressure, liquid H2,...) have some drawbacks (cost, energy requirement, losses by diffusion or boiling). In this context, different alternatives exist like ammonia. Ammonia has undeniable advantages for the storage of H2 with high energy densities (108 kg H2/m3 NH3 at 20°C-8.6bar; 17.8% wt H2) and existing infrastructure for its distribution. Furthermore, its use either as NH3 or as H2 after decomposition makes it possible to consider ammonia for multiple applications. Its decomposition is endothermal and a high temperature (> 700 ° C) is mandatory to ensure its decomposition with high kinetics. This temperature implies the aging of the catalysts and has a strong impact on the mechanical strength of the reactors with time. Developing catalysts allowing the efficient decomposition (kinetics, cost) of NH3 at lower temperature, based on theoretical and experimental approach, would open the field of application of NH3 technologies.

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K-ion batteries, towards a full system without any critical raw materials

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Matériaux

01-09-2021

SL-DRT-21-0524

david.peralta@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

Classic Li-ion batteries are composed of a graphite anode and a cathode containing a lithiated layered oxide (formula LiNixMnyCozO2). The development and the generalization of the electric automobile market will generate stress on certain chemical elements source, especially for lithium, nickel and cobalt. In addition, the production method consumes a lot of energy (multiple calcinations) and several solvents/products used are not respectful of the environment (NMP, ammonia). The thesis aims to develop a battery technology based on potassium. We will pay attention not to use any critical element in order to significantly reduce the ecological footprint. In terms of performance, potassium has a potential close to lithium, which suggests that high-energy batteries can be manufactured. Some potassium cathode materials have theoretical capacities of 155 mAh/g at a potential close to 4 V, which makes the technology competitive with conventional Li-ion batteries. The final target of the PhD thesis is to optimize and validate the technology in a complete system. The student will optimize the synthesis of the cathode material, the anode, the electrolyte in order to obtain an efficient system.

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Perovskite materials: influence of nanocrystallization processes on the performances of PK cells for tandem integration

Département des Technologies Solaires (LITEN)

Laboratoire des Cellules Tandem

01-10-2021

SL-DRT-21-0526

noella.lemaitre@cea.fr

Solar energy for energy transition (.pdf)

After several decades of intense development, silicon-based PV is a well-established and mature technology that now nears its practical efficiency limit. One strategy to overcome this limit is to use multi-junctions solar cells coupling a silicon subcell with a topcell based on a higher band gap absorber (1,6 - 1,7 eV vs 1.12 eV for silicon) exhibiting high efficiency. Lead halide perovskites (with ABX3 structure) can fulfill these requirements. Such materials can be integrated via solution processing at low temperature and yield theoretical efficiencies well beyond 30% when combined in a tandem device with a silicon subcell. To this end, controlling perovskite crystallization from precursors solution is obviously of prime importance. Also, the development of upscalable techniques to process the perovskite is one of the main practical challenge still to be met to ensure a practical deployment of the technology. The strategy currently developed within CEA relies on a gas-quenching of the precursors wet film to trigger perovskite crystallization. The main goal of this PhD will be to study in-depth the perovskite crystallization when processed in such conditions, to pave the way towards successful integration in tandem devices.

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In-memory computing for sporadic applications in extreme environment

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Fonctions Innovantes pour circuits Mixtes

01-10-2020

SL-DRT-21-0529

jean-frederic.christmann@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

In the context of Internet of Thins, applications are mainly sporadic and operating conditions such as the energy budget might be extreme. Power consumption reduction allows to improve the lifetime of embedded platforms or to integrate enhanced features. This PhD subject thus tackles the design of a memory component which would be able to compute complex calculations directly within the memory. This would highly reduce data exchanges with the processor and reduce the associated power consumption. The computing memory component will be designed using asynchronous logic, which provides a natural solution for IoT applications and brings strong physical implementation opportunities to further reduce the power consumption. Architecture development, validation though digital simulations, physical implementation and characterization of the component's performances are the main steps of the PhD contributions. Fabricating a chip which integrates the proposed ideas would allow to demonstrate the quality of the chosen approach in a realistic context.

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On-Chip moniToring of Organoids using an oPtoflUidiC systEm

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie, Capteurs et Biomatériaux

01-10-2021

SL-DRT-21-0534

charlotte.parent@cea.fr

Health and environment technologies, medical devices (.pdf)

The thesis is positioned in the domain of organoids, which enable fundamental tissue mechanisms to be studied in-vitro. The project aims at developing a new microfluidic system with integrated simple, robust and compact optical reading, and allowing for in-situ monitoring of the secretome evolution during the cell culture. The chosen model system is the culture of islets of Langerhans responsible for the endocrine function of the pancreas and playing an important role in diabetes. To reach our objective, we propose to combine two approaches within a microfluidic chip: a chip with photonic-crystal sensors that are compatible with lens-less optical reading (LED + CMOS), and a microfluidics technology integrating the pneumatic actuation of an elastic membrane. The main challenges of the project are related to the sensors sensitivity, the optical chip integration in the microfluidic system and the sampling of aliquots without perturbation of the organoid. The thesis will be in collaboration between two complementary laboratory, CEA-LETI (microfluidics, technology), and INL (photonic biosensors).

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Study and development of thermoelectric materials by additive manufacturing

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire de Modélisation et Matériaux pour la Métallurgie

01-10-2021

SL-DRT-21-0536

guilhem.roux@cea.fr

Additive manufacturing, new routes for saving materials (.pdf)

For 15 years, the laboratory L3M has acquiered a big experience in thermoelectricity (TE), mainly in thin films and bulk technologies. Thermoelectricity converts thermal energy into electrical Energy (Seebeck effect), and reciprocally (Peltier effect). For 5 years, L3M has also acquiered a strong experience in additive manufacturing (AM), mainly for metallic materials. The use of AM for TE offers new perspectives, and enables to vreate new complex geometries (leading to an optimization of yield and/or a better integration), with less materials losses, a significant decrease of the integration and interface challenges, a faster manufacturing time, a lower cost and the possibility to manufacture TE devices very quickly compared to other technologies. The main barrier consists in obtaining materials with as good quality as with other technologies (in terms of density and microstructure), which will be possible thanks to a deep development of the process. Two families of TE materials will be studied: Bi2Te3 and MnSi/FeGe. The first one is the reference in the temperature range 300-500 K and the second one in the temperature range 500-700 K. The objective of this PhD study will be to study and optimize materials manufacturing processes obtained by AM (by the Laser Powder Bed Fusion (L-PBF) technology). This study will enable understanding and highlighting specifities of AM mechanisms on TE materials structural properties. This structural study will include measurement of mechanical properties, as well as microscopic analysis. This study will also correlated to experimental measurements of manufactured materials TE properties (Seebeck coefficient, electrical and thermal properties). Up to now, no thermoelectric device has been manufactured by this technology. TE device manufacturing needs to associate two TE materials and assemble together, by optimizing electrical contacts between these two materials. CEA-Liten has deposited a patent about the original manufacture of such device by AM. The realisation and electrical characterization of a first TE prototype will be also developed in he Framework of this study. It will enable highlighting advantages of this technique, such as manufacturing of complex geometries, less materials losses, a shorter manufacturing time, etc.

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Real-world data and AI for an innovative analytical approach to intonation and speech intelligibility in children with Cerebal Palsy

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire d'Interfaces Sensorielles & Ambiantes

01-10-2021

SL-DRT-21-0539

margarita.anastassova@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Cerebral palsy (CP) is a developmental motor disorder affecting an individual's ability to move, and maintain balance and posture. It affects 2 to 4 children in 1,000, making this lifelong, chronic condition the most common motor disability in childhood. In addition to motor problems, many children with CP have difficulties with speaking, which severely impacts their access to social and educational activities. The most frequent speech impairment in CP is developmental dysarthria, characterized by limited movement of the jaw, lips and tongue; imprecise articulation; slow speaking rate; reduced intonation with a limited variation in pitch, rhythm and volume, which results in impaired speech intelligibility. Despite the frequent occurrence of problems in intonation and speech intelligibility in children with CP, the heterogeneity of the profiles and the central role of intonation in communication, few studies have examined intonation patterns in this population in order to characterize and classify them. As a result, little is known about intonational difficulties and their relationship to intelligibility in children with CP. Knowledge on the relation of intonational patterns and expressions with motor activities in real-world tasks is even more scarce. The aim of the research project is to fill in the above-mentioned knowledge gaps. This will be done using a real-world data-driven approach, combined with innovative analytical approaches based on AI and machine learning.

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Fuzzing techniques to support static security analyses

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire pour la Sûreté du Logiciel

01-10-2021

SL-DRT-21-0557

michael.marcozzi@cea.fr

Cyber security : hardware and sofware (.pdf)

Guaranteeing digital security is a crucial issue. In this context, static analyses and fuzzing are popular approaches making it possible to detect software vulnerabilities directly at the binary level. The two approaches are complementary: static analyses can either provide guarantees that the program is safe, or report possibly unsafe program executions. On the contrary, fuzzing cannot provide any strict guarantee about program security, but is able to identify executions that exhibit a vulnerability for sure. In this thesis, we will thus take advantage of fuzzing to confirm vulnerability reports from static analysis. This will require us to develop a fuzzer able to target the possibly insecure executions identified by the static analyser. This is quite challenging as targeted fuzzing is a difficult and underresearched domain. In addition, static analysers provide rather loose descriptions of the possibly vulnerable executions, making the fuzzer's task even harder. To overcome these challenges, we will take advantage of tried and tested solutions from the fields of search-based testing and advanced coverage criteria, which have been underexploited in the field of fuzzing. The developed fuzzer will be evaluated at scale in real use cases and we will measure how much it enables a better prioritisation and a more precise elaboration of vulnerability reports. Finally, we will provide elements of generalisation, making targeted fuzzing more adaptable to problems sharing similarities with confirming vulnerability reports.

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Concentration and capture of pathogens under homogeneous conditions in a microsystem

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie, Capteurs et Biomatériaux

01-10-2021

SL-DRT-21-0558

jean-maxime.roux@cea.fr

Health and environment technologies, medical devices (.pdf)

The search for pathogens (toxins, viruses, bacteria, fungal spores), whether by immunological or biomolecular tests, is often limited by the preparation of samples. These are often too diluted and require a concentration step to detect quickly a contamination with a low level of pathogens. They can also contain interferents that may falsify the test results by leading to false positives or false negatives. These interferents must be neutralized or eliminated by washing, at the risk of diluting the samples; a concentration step is then necessary again. Innovations are required in the field to develop devices that may contribute to fast field diagnostic for non experts users. The proposed thesis subject is part of a study of uncommon flows within a microfluidic channel to improve the capture and concentration of pathogens, microorganisms and allergens and toxins. The process which will be studied aims on the one hand to circumvent the problems of clogging presented by filters and so-called pillar chips. It also aims to speed up biological analysis tests in a compact and autonomous system.

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Speculating About Low-level Security

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire pour la Sûreté du Logiciel

SL-DRT-21-0559

sebastien.bardin@cea.fr

Cyber security : hardware and sofware (.pdf)

We consider the general context of automated code-level security analysis. While standard attacks such as control-flow hijacking take advantage of programming flaws (typically, missing bound checks), recent micro-architectural attacks take advantage of subtle behaviours at the micro-architectural levels, typically speculative behaviours introduced in modern architectures for efficiency, in order to bypass protections and leak sensitive data. These vulnerabilities are extremely hard to find by a human expert, as they require to reason at a very low-level, on an exponential number of otherwise-hidden speculative behaviours, and on complex security properties (leaks and data interference, rather than standard memory corruptions). The goal of this doctoral work is to understand how automated symbolic verification and bug finding methods (especially but not limited to, symbolic execution) can be efficiently lifted to the case of speculative micro-architectural attacks, with the ultimate goal of securing essential security primitives in cryptographic libraries and OS kernels. This general objective raises challenges in terms of semantics of speculative behaviours, semantics of security properties and scalability of verification techniques. These techniques will be implemented in the binary-level code analysis framework BINSEC and their benefits assessed through rigorous experimental evaluation.

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Transfer Learning and Optimal Transport applied to the adaptation of models learnt on synthetic data

Département Métrologie Instrumentation et Information (LIST)

Laboratoire Science des Données et de la Décision

01-10-2021

SL-DRT-21-0563

fred-maurice.ngole-mboula@cea.fr

Artificial intelligence & Data intelligence (.pdf)

This PhD thesis aims at exploring possible contributions of optimal transportation field to transfer learning through the following directions: - building a knowledge transferability criterion between a source and a target task based on the regularity of the transportation plan between the source and the target data distributions; - integrating priors on the tasks similarity through the transportation ground metric; - applying Wasserstein barycenter to multi-task learning problems. These works might find multiple use-cases of interest in the lab, including adaptation of models learnt on synthetic data to real world systems. A more detailed presentation of this PhD thesis subject can be found via the following link: https://drive.google.com/file/d/13RAQEi0PdnkllM-MHxQS50WWUNUtGS07/view?usp=sharing

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High Energy Density Positive Electrode based on Glass Materials for Li-Ion and Na-Ion Cells

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Matériaux

01-10-2021

SL-DRT-21-0577

sebastien.martinet@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

This PhD subject will aim at developing new positive electrode materials based on glasses for high Energy Density Li-Ion and Na-Ion cells. These developments will be held jointly between the laboratory of materials for batteries from CEA-Grenoble and LDMC lab from CEA-Marcoule that is specialized in the formulation and characterization of glass materials. The work will be focused on the optimization of the complex formulation of the glass cathodes to solve the issues related to first cycle irreversible loss and low cycling performances. The main objective will be to obtain one composition without critical raw materials exhibiting more than 1000Wh/kg at active material level vs 700 for state-of-the-art materials. This target will be reached with the support of advanced characterization techniques such as X-Ray Diffraction and RAMAN and FTIR spectroscopies. A dedicated effort will concern the development of operando or in-situ measures to be able to explain the link between electrochemical performances and glass characteristics, what has never been reported in the litterature.

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Polarization sensitive pixels

Département d'Optronique (LETI)

Laboratoire d'Imagerie sur Silicium

01-10-2021

SL-DRT-21-0588

quentin.abadie@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

For certain mass productions markets (automotive, industrial control, depth mapping etc?), polarization pixels could be useful. PhD will address this domain and weight pros and cons of current solutions. Differentiating from current competitors polarization sensors with Metal grids, the thesis project aims to explore new design/process to improve performances.

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Shell finite elements for real time simulations in virtual reality

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire de Simulation Interactive

01-09-2021

SL-DRT-21-0594

anders.thorin@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

With growing interest in interactive simulation comes the need to simulate shells (i.e. volumes with a thickness smaller than the two other dimensions) in real time. The objective of this thesis is to simulate the dynamics of thin shells in small strains, in the context of large displacements (geometric non-linearity) in real time. The work will be carried out in three parts, i) provide criteria to determine what can be simulated in real time or not (with a given number of degrees of freedom and a given precision), ii) identify or develop finite elements that are both robust to handle different use cases and efficient in terms of computational cost, iii) provide an implementation and examples of simulations that cannot be simulated in real time to date, with equal hardware.

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Development of superconducting single photon detectors and receiver circuits for quantum communications

Département d'Optronique (LETI)

Laboratoire d'Intégration Photonique sur Silicium

01-10-2021

SL-DRT-21-0605

segolene.olivier@cea.fr

Photonics, Imaging and displays (.pdf)

Quantum information processing turns out to be a major challenge for our society with the development of quantum computers, able to solve complex problems much more rapidly than a classical computer, and of quantum communications providing absolute security for information transfer. The development of integrated technologies is essential for the future large-scale deployment of compact and low-cost quantum information systems. CEA-Leti has been developing for several years a silicon photonics platform, providing integrated components and circuits for various applications such as telecom/datacom, lidars and more recently quantum communications. The objective of this PhD is in a first step to design, fabricate in the Leti clean room and characterize a new generation of advanced superconducting quantum detectors on Silicon able to detect single photons with above 90% efficiency. In a second step, these detectors will be integrated into secure quantum communication circuits. This PhD will benefit from collaborations with academic laboratories in France and in Europe.

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Multiscale simulation for engineering and characterization of materials and quantum devices

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-10-2021

SL-DRT-21-0606

benoit.sklenard@cea.fr

Numerical simulation (.pdf)

Quantum devices open up new perspectives for information processing. The CEA is developing, in particular, silicon quantum bits. In this innovative field, the systematic exploration of the many possible options is prohibitive. The challenges posed by quantum technologies cannot therefore be met without advanced numerical simulation. The CEA has developped a multi-physics code, TB_Sim, for the modeling of quantum devices from the nano- to mesoscopic scales. However, a few obstacles prevent simulation from being sufficiently predictive on these devices. One of the most important issues is the description of surfaces, interfaces and defects, which play an essential role in the physics of spin-orbit coupling and "valleys" in silicon. This thesis aims, therefore, to introduce atomistic "ab initio" approaches in the chain of multiscale simulations of quantum devices. The candidate will focus on the interfaces of silicon with its encapsulation materials (SiGe, SiO2 ...) and on the defects at these interfaces (amorphization, Pb defects, ...). He / She will in particular address the connexion between the atomistic ab initio and the nano- and mesoscopic scales. The ambitious objective of this thesis is to integrate numerical simulation at all stages of the design, manufacture and characterization of the devices, and to make it sufficiently predictive even on uncharted grounds. Numerical experiments will be carried out for this purpose both upstream and during the characterization in order to confront the simulation with reality, to support the analysis of the data by providing the ?missing pieces of the puzzle? which cannot be measured directly, and to provide feedback to the design. This work will be carried out in close collaboration between CEA-Leti (ab initio methods) and IRIG (TB_Sim code).

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A new energy scale for X- and gamma-rays below 100 keV using high-resolution metallic magnetic calorimeters

Département Métrologie Instrumentation et Information (LIST)

Laboratoire de Métrologie de l'Activité

01-09-2021

SL-DRT-21-0608

matias.rodrigues@cea.fr

Advanced nano characterization (.pdf)

Currently, many physics experiments are probing exotic atoms (hydrogenic, pionic or kaonic) by X-ray spectrometry to study the structure of the nucleus and the nucleus-particle interaction or to test quantum chromodynamics (QCD) under extreme conditions. They are looking at electromagnetic transitions using very precise photon spectrometry. Other experiments aim at precisely measuring the weakest known isomeric transition, emitted by Th-229m, a candidate transition for the development of future nuclear clocks. New cryogenic detectors are being increasingly developed and used for these areas of research, but they require extremely precise energy calibration from reference lines. However, above 8 keV, the uncertainties of the evaluated and tabulated X and gamma lines increase sharply. The aim of the thesis is therefore to define a new scale in X and gamma-ray energy below 100 keV with a relative uncertainty of a few 10^-6. For this, two experimental set-ups will be developed and will integrate cryogenic detectors based on metallic magnetic calorimeters (MMC). These detectors, operating around 20 mK, offer an energy resolution one order of magnitude better than those of semiconductor detectors. An in-depth study of the whole measurement chain will have to identify and correct non-linearities and distortions. In addition, the MMCs will be pixelized to increase the counting rate and limit the statistical uncertainty. Once characterized and operational, the two cryogenic spectrometers will measure the X and gamma-ray energy spectra emitted by carefully selected radionuclides. The energies of the metrologically established lines will then be used as references, both for calibrating spectrometers used in fundamental physics and those used for materials analysis. Moreover, these energies will be a benchmark to validate complex theoretical calculations of radiative transitions.

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High-effiency power hub for energy transition

Département Systèmes (LETI)

Laboratoire Electronique Energie et Puissance

01-10-2021

SL-DRT-21-0609

sebastien.carcouet@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

This subject addresses the scientific developments needed to design a power hub allowing, in a single stage of power electronics, to manage all the household energy flows: photovoltaic supply (...) , storage including the battery of electric vehicles (V2G), connection to the network (smart grid), etc. Previous works at CEA have already dealt with advanced high-efficiency high-frequency converter topologies, in particular using GaN components. We propose to go further, by studying the coupling of various energy sources and receivers using a single-stage converter. The design of the converter and control policies will be carried out using a Model Based Design approach, involving numerical simulation and design tools in the same integrated development environment. The study will end with the implementation of control laws on a prototype elaborated in the laboratory.

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Blending intuition with reasoning - Deep learning augmented with algorithmic logic and abstraction

Département Ingénierie Logiciels et Systèmes (LIST)

Labo.conception des systèmes embarqués et autonomes

01-03-2021

SL-DRT-21-0617

shuai.li@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Within machine learning, deep learning, based on neural networks, is a subfield that has gained much traction since several high-profile success stories. Unlike classical computer reasoning, the statistical method by which a neural network solves a problem can be seen as a very primitive form of intuition, as opposite to classical computer reasoning. However, so far the only real success of deep learning has been its ability to self-tune its geometric logic that lets it transform data represented as points in n-dimension, to data represented as points in m-dimension, if we provide enough training data. Unlike a human being, a neural network does not have the ability to reason through algorithmic logic. Furthermore, although neural networks are tremendously powerful for a given task, since they have no ability to achieve global generalization, any deviation in the input data may give unpredicted results, which limits their reusability. Considering the significant cost associated with neural network development, integrating such systems is not always economically viable. It is therefore necessary to abstract, encapsulate, reuse and compose neural networks. Although lacking in deep learning, algorithmic logic and abstraction are today innate to classical software engineering, through programming primitives, software architecture paradigms, and mature methodological patterns like Model-Driven Engineering. Therefore, in this thesis, we propose to blend reusable algorithmic intelligence, providing the ability to reason, with reusable geometric intelligence, providing the ability of intuition. To achieve such an objective, we can explore some ideas like integrating programming control primitives in neural networks, applying software architecture paradigms in neural networks models, and assembling modular systems using libraries containing both algorithmic modules and geometric modules. The results of this thesis will be a stepping stone towards helping companies assemble AI systems for their specific problems, by limiting the costs in expertise, effort, time, and data necessary to integrate neural networks.

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Architecture and design of a room-temperature feedback loop between cryogenic Qubits measurement and control chains

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Systèmes-sur-puce et Technologies Avancées

01-09-2021

SL-DRT-21-0620

eric.guthmuller@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

A functional and useful Quantum Processing Unit (QPU) able to solve real problems on hundreds of Qubits will necessitate a way to correct errors introduced by quantum gates and Qubits decoherence. The foreseen way of doing this is to use error-correcting codes, such as surface codes for example. The common denominator to these error-correcting codes is the requirement to read regularly a subset of the Qubits and to apply operators to correct errors according to the measurement result. It is essential to reduce as much as possible the time between measurement and error correction, as in the meantime the Qubit error is still accumulating. The first objective of this PhD involves proposing an innovative low-latency (less than 1µs) digital architecture to correct errors in a real spin Qubits device. The second objective is to design this architecture on a FPGA board that is already used in Qubits measurement and control experiments. Finally, the student will do experiments on real Qubits devices placed in a cryostat to which the student will have access.

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Secure information sharing for material and product passports in support of the circular economy

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Intelligence Intégrée Multi-capteurs

01-10-2021

SL-DRT-21-0622

carolynn.bernier@cea.fr

Health and environment technologies, medical devices (.pdf)

The circular economy requires a continual reallocation of materials and components in usage loops including the phases of material extraction, production of components and finished products, reuse, refurbishment, upcyling, repair, maintenance and recycling. In addition, the political context tends towards an enlarged producer responsibility associated to an increased need to guarantee the origins of materials (e.g. conflict-free metals). The digital passport of a material or a product contains information on it constituents and their origins, but also potentially also information necessary for the environmental impact assessment surrounding its fabrication, use and transformation. However a great deal of this data is sensitive and sharing it between different actors poses obvious confidentiality issues. Many solutions for secure data sharing exist (International Data Spaces, blockchain, privacy by design, encryption, data minimization, Fully Homomorphic Encryption) and the purpose of this thesis is first to analyze the specific needs of the digital passport and then to model the coupling of different possible solutions while taking into account the environmental impact of the different solutions. Please send your application to oana.stan@cea.fr and sara.tucci@cea.fr

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Study of EBIC and cathodoluminescence applied to narrow gap photodiodes for cooled IR détection

Département d'Optronique (LETI)

Laboratoire d'Imagerie IR

01-10-2021

SL-DRT-21-0626

pierre.bleuet@cea.fr

Photonics, Imaging and displays (.pdf)

Since 40 years, CEA LETI is developing IR detection technologies using narrow gap semi-conductors. This led to the creation of the Lynred Company, formerly Known as Sofradir, now leader in the IR imaging market. In the frame of the collaborative work we have with Lynred for the development of new generations of IR imager, new characterisation needs appear. It addresses different issues, starting from the fine understanding of the photodiode operation when reducing its pixel pitch. It also addresses the understanding of the effects of the metallurgical and technological induced defects on the final IR detection performances. The proposal here is to study the behaviour of narrow gap IR photodiodes when excited with an electron beam within a scanning electron microscope (SEM). A mapping of the electron beam induced current (EBIC) brings important information about charge transport in the narrow gap, whereas the mapping of the associated induced IR luminescence (cathodo-luminescence) carries further and complementary information about radiative recombination of injected charges. This information is particularly interesting when interaction with defects occurs in the structure. In our characterisation group, the EBIC experiment is now operational at cryogenic temperatures. On the other hand, the cathodo-luminescence part of the experiment has to be developed to complete EBIC images. Once operational, the full picture EBIC+cathodo should be investigated using different samples from our fabrication line, focusing on small pixel pitches and high operation temperature structures, making the connection with all the other electro-optical characterisation benches available in our lab.

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Accounting for the Environmental Impact of Digital Systems during the Design Phase

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Systèmes-sur-puce et Technologies Avancées

01-09-2021

SL-DRT-21-0630

adrian.evans@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Currently, the green house gas emissions from digital systems are comparable to those from the aviation seector and unfortunately, they are following an exponential growth curve. This PhD thesis targets to realize a thorough analysis of the environmet impact due to the design phase et usage of large digital circuits. Following this analysis, the objective it to offer new tools and associated design methodologies to circuit designers, allowing to estimate et then reduce the environment impacts. During the design phase, it is targetted to reduce the amount of computing ressources, but the major gain will come from increasing the Energy efficiency and reduce the power enveloppe of digital system during its lifetime. This requires to analyse globally the system, from circuit level up to task delegation in the cloud. As a world leader in intelligent digital systems, the digital design departement targets to develop, through this PhD, a sober design flow that will be transfered to the industry. The PhD work will be using the overall design platform of the digital circuit and system departement, using different high performance computing systems as potential test-cases, and will define and optimize some cross layer optimization techniques.

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Innovative hydrogels for ?minibrain-on-chip ? development to study Alzeimer's disease

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie, Capteurs et Biomatériaux

01-10-2021

SL-DRT-21-0633

isabelle.texier-nogues@cea.fr

Health and environment technologies, medical devices (.pdf)

Organ-on-chip approaches tackle the limitations of two-dimensional (2D) classic cellular cultures and animal models of neurodegenerative diseases. DRF/JACOB/SEPIA has developed ?mini brains?, i.e. 3D cerebral organoids generated from iPSCs (induced pluripotent stem cells), presently cultivated using Matrigel, a commercial matrix derived from mouse tumor. The objective of the PhD thesis will be to investigate new 3D culture scaffolds, based on hyaluronic acid (HA) hydrogels presenting tunable stiffness and electrical conductivity, developed at DRT/LETI/DTBS. The cell-loaded hydrogels will additionally be formulated as bioinks for advanced printing technologies (extrusion combined with UV/visible photo-crosslinking). The expected outcome of the PhD is an improved ?mini brain? model to study the development of neurodegenerative diseases, which could be applied to therapeutic strategies.

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Multimodal characterization of therapeutic phages

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie, Capteurs et Biomatériaux

01-10-2021

SL-DRT-21-0634

pierre.marcoux@cea.fr

Health and environment technologies, medical devices (.pdf)

The rapid inexorable spread of antibiotic resistance is one of the critical challenges in health care for the coming decade. Patients increasingly encounter dead-ends, with no effective molecule. The quest for alternatives to antibiotic therapy is a major public health issue and should, according to the WHO, be given priority status. Phage therapy uses viruses known as bacteriophages, or ?phages? for short, that specifically infect and destroy bacteria without impact on human cells. They have been used for decades in some countries in Eastern Europe, but preparations from these countries cannot be imported in France or Western European countries as they fail to meet standard drug agency criteria (ANSM, EMEA). Some new techniques have to be developed and optimized for a better and faster characterization of these therapeutic viruses, during their amplification and purification, as well as during their storage or juste before dispensing medication. The study deals with innovative approaches based on microelectronics and nanotechnologies for rapid in-vitro quantification and characterization of therapeutic phages to facilitate selection of phages and QCs of phage therapeutic products: (i) a lensless imaging technique for fast phage titration based on the monitoring of lysis plaques (from 20-µm- to millimeter-size) over a wide field-of-view (up to at least 864 mm2), suited to continuous detection of phage plaque growth, (ii) a microsystem called SNR (Suspended Nanochannel Resonator) for phage purity assessment without culture/replication requirement based on rapid mass measurement of individual virions.

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Dispersion-engineered metalenses for high-performance low-profile antennas and extreme wave manipulation

Département Systèmes (LETI)

Laboratoire Antennes, Propagation, Couplage Inductif

01-10-2021

SL-DRT-21-0638

francesco.fogliamanzillo@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

The performance of conventional antenna architectures, e.g. phased arrays and reflectors, is limited by inherent trade-offs among bandwidth, efficiency, scan range and size. Disruptive concepts are necessary to address the demanding requirements arising in novel applications such as satellite and 5G communications, and high-resolution imaging. Metasurfaces (MSs) are electrically thin arrays of subwavelength scatterers and have recently emerged as a promising concept to attain unprecedented antenna performance and functionalities. The subwavelength periodicity of a MS offers an extremely fine control on the aperture fields and, by virtue of Huygens' principle, the possibility to perform a wide range of transformations of the incident field. However, there is a lack of advanced models and synthesis methods for the design of anisotropic MSs. Moreover, the bandwidth of most MS antennas is often too narrow due to frequency dispersion. This thesis aims to provide a mathematical framework for the analysis and design of MS lenses and to demonstrate groundbreaking ultralow-profile antenna systems comprising a primary source and a metalens realized with a few cascaded layers. The metalens will be modeled as an effective bianisotropic medium, exhibiting coupled responses to electric and magnetic fields. Specific synthesis procedures will be developed to engineer the frequency dispersion of a large metalens and to tailor its refractive index as a function of the incident angle of the impinging wave. These tools will be exploited for the design of two demonstrators at microwave frequencies: (i) a high-gain antenna achieving extremely high aperture efficiency (>70%) and large fractional bandwidth (>15%); (ii) a thin meta-radome for extending the scan range of a phased array beyond the state of the art (±75°) while preserving high broadside efficiency. At least one demonstrator will be prototyped using low-cost fabrication processes, such as printed circuit board and additive manufacturing, and experimentally characterized.

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Distributed data stream learning in a collaborative environment

Département Métrologie Instrumentation et Information (LIST)

Laboratoire Intelligence Artificielle et Apprentissage Automatique

01-09-2021

SL-DRT-21-0640

sandra.garciarodriguez@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The scope of this PhD mixes two very trendy machine-learning domains, as they are the federated learning and the data-stream learning. Data streams are defined as infinite streams of data integrated from both live and historical sources. In such scenarios, data-stream processing algorithms must satisfy requirements such as bounded storage, single pass (data is going to be processed just once), real time and concept drift. On the other hand, federated learning is a technique that trains an algorithm across multiple decentralized edge devices or servers holding local data samples, without exchanging them.

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Scalable and Precise Static Analysis of Memory for Low-Level Languages

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire pour la Sûreté du Logiciel

01-10-2021

SL-DRT-21-0641

matthieu.lemerre@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The goal of the thesis is to develop an automated static analysis (based on abstract interpretation) to verify, in large code base in low-level compiled languages (e.g. C, C++, assembly, Rust, Fortran), security properties that are related to memory, lke flow information properties and absence of memory corruption. This problem has many applications in cybersecurity, as most of the software-related cybersecurity issues, and those that have the highest severity, come from memory safety errors (e.g. (buffer overflows, use-after-free, null pointer dereferences, wrong type punning, wrong interfacing between several languages, etc). The three main issues when designing such an automated static analysis is to keep the verification effort low, to handle large and complex systems, and to be precise enough so that the analysis does not report a large amount of false alarms. The privileged approach in this thesis will draw on the success of a new method using abstract domains parameterized by type invariants, which found a sweet spot between precision (i.e. few false alarms), efficiency (in computing resources), and required effort (by the user). This method allowed in particular to fully automatically prove absence of privilege escalation and of memory corruptions of an existing industrial microkernel from its machine code, using only 58 lines of annotations. Many research questions remain, and we will explore how to extend the analyzer to improve scalability (using compositional analysis), how to improve its expressivity (to show complex security properties like non-interference), how to improve precision without degrading efficiency, or how to further reduce the amount of annotations (using automatic inference of more precise type invariants).

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Trajectory Prediction for Autonomous Navigation

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Intelligence Intégrée Multi-capteurs

01-09-2021

SL-DRT-21-0644

tiana.rakotovao@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

With the growing interest in Autonomous Vehicles (AV), perception systems play a central role in their navigation, with active developments from the research and automotive industry communities. Perception systems provide AVs with information about the driving situation. Basically, advanced algorithms model the vehicle environment using a map by processing past and present data from on-board sensors such as cameras, LiDARs, radars and ultrasounds. The future evolution of the driving environment is predicted in order to plan safe trajectory, avoid collisions and make navigational decisions. CEA has developed a patented on-board sensor fusion technology that exploits the occupancy grid paradigm to model the vehicle environment. This grid provides a probabilistic estimate of occupied and free regions. The estimation of obstacle movement is also under development. However, a prediction layer that estimates the likely future trajectories of moving obstacles is still missing. The objective of the PhD thesis is to develop an embedded trajectory prediction algorithm for autonomous navigation. Trajectory prediction is a spatio-temporal (4D) problem where uncertainty is essential to evaluate the probable short-term evolution of a driving scenario. The diversity of moving obstacles makes trajectory prediction very difficult when integrated within lightweight computing platforms. In fact, a moving car does not have the same degree of freedom as a pedestrian. Prediction models can take into account the nature of moving obstacles if this information is available (for example, provided by artificial intelligence). Otherwise, prediction models must adapt to the available data. During the thesis, the PhD student will first focus on the probabilistic modeling of motion and trajectory. Then, he/she will propose a low-complexity algorithmic solution that can run in real time on an embedded computing platform. The PhD student will be hosted in a team whose expertise is the development of advanced and lightweight perception solutions that can be integrated into embedded systems. The PhD student will collaborate with researchers, engineers and other PhD students from various scientific fields. The candidate must have a strong mathematical background in probability/statistics, computer science and software prototyping (matlab/python, C++). Knowledge and skills in artificial intelligence and data fusion will be a plus.

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Dynamic Mesh Reordering by Cache-aware Heuristics for scientific computing

Département Systèmes et Circuits Intégrés Numériques

Laboratoire pour la Confiance des sYstèmes de calcuL

01-10-2021

SL-DRT-21-0653

thierry.goubier@cea.fr

Numerical simulation (.pdf)

In the context of simulation codes on unstructured grids, two elements appears: the traversal of the mesh on a CPU appear as random, and the "unstructured" aspect of the mesh makes accelerators problematic. However, such meshes allow the simulation at multiple scales, replacing multiple nested regular grids by a single structure, for example in tsunami simulations, resulting in a more compact structure and decreasing the computational power needed. Additionally, in some contexts the mesh will evolve in time, making partionning for multiple compute units difficult with their associated caches. This thesis focuses on the development of cache-aware heuristics of traversal of unstructured meshes, so as to allow on-the-fly reordering, in particular when sending compute kernels and mesh data on accelerators, so as to start computing before the mesh transfert has ended. This thesis will rely on existing results on mesh partitionning with tools such as SCOTCH and Metis, on models of memory / cache hierarchies and transfert capabilities (accelerators), and space filling curves related work (Hilbert-Peano, Sierpinski). The focus will be on the TsunAWI and FESOM (Finite Element/volume Sea-Ocean Model) codes from AWI and OpenFOAM. The student may have the opportunity to spend time at AWI (Germany) during the PhD.

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Microfluidic bioreactor for in-situ analysis of extracellular vesicles secreted by organoids

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie, Capteurs et Biomatériaux

01-10-2021

SL-DRT-21-0654

vincent.agache@cea.fr

Health and environment technologies, medical devices (.pdf)

Extracellular vesicles (EVs) are widely recognized as vectors of biological material capable of transferring genetic/molecular content between cells and of contributing to intercellular communication mechanisms leading, for example, to the proliferation of tumors in cancer. However, most of the studies implemented today are conducted on cell populations with intrinsic heterogeneities that introduce bias into the analyzes. In addition, the sources of EVs are generally derived from two-dimensional cell culture poorly representative of the microenvironment of the in vivo extracellular matrix in tissues or organs. Conversely, organoids derived from patients have already been shown to accurately recapitulate many disease traits of patients, including genetic heterogeneity and response to treatment. In this thesis, we propose the development of a system enabling the isolation of one or more organoids in a microfluidic bioreactor, combined with means of collection, concentration, and nanomechanical sensors to allow the in-situ analysis of the secretion rate of EVs and collect their biophysical signature, with the perspective of new therapeutic approaches based on monitoring the kinetics of EV secretion on organoids derived from patients.

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Real Time Semantic extraction on sparse data for embedded perception

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Intelligence Artificielle Embarquée

01-10-2021

SL-DRT-21-0656

mehdi.darouich@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The thesis topic we propose is in the field of embedded architectures for the semantic analysis of sparse data in real-time. During the last decade, the analysis of image and videostreams has experienced a boom following the significant improvement of neural networks and the increased specialization of the associated processing architectures. Research has led to the development of more efficient networks, which are less memory-intensive and increasingly integrable into embedded hardware. Several works are currently in progress in the laboratory, around the N2D2 tool for the optimization and integration of neural networks on embedded hardware, as well as around the DNeuro embedded hardware architecture. Within embedded perception systems, the strong constraints on bandwidth and memory lead to the privileged use of sparse data (graphs, point clouds, etc.), reduced in quantity and containing particularly rich information on the environment to be analyzed. However, the non-contiguous and unpredictable structure of this sparse data is very different from a traditional image stream, making current hardware architectures unsuitable for their execution. However, these particular characteristics point to very interesting opportunities in terms of optimization and efficiency. This thesis work aims at exploring this class of algorithms and their capacity of integration under constraints in an embedded computing architecture. The scientific problems that arise here are how to perform efficient data management in a context of highly scattered computational distribution, the compatibility of sparse data analysis algorithms with execution on embedded targets, and the performances and precision achievable under these constraints.

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Contribution of machine learning and probabilistic modeling of uncertainties for the design and model-predictic control of distributed multi-energy systems

Département Thermique Conversion et Hydrogène (LITEN)

Laboratoire des systèmes énergétiques pour les territoires

01-09-2021

SL-DRT-21-0664

mathieu.vallee@cea.fr

Smart Energy grids (.pdf)

Taking uncertainties into account is key for model predictive control of distributed multi-energy systems (DMES), as well as for sizing these systems when optimal control is involved. Solutions exist for dealing with uncertainties in optimization problems. However, fast computation is often required to allow for probabilistic methods, typically based on a Monte-Carlo approach. Designing models for fast computation introduces new uncertainties, related to the accuracy of the model compared to the real system under study. This source of uncertainty is hard to quantify, and can have huge impact on results if they outweight other sources of uncertainties. In this PhD work, we propose to design, based on previous work at CEA, a method for simplifying optimization models in a way that is both appropriate for dealing with uncertainties and for using then in control and sizing of DMES. The key novelty in this work will be on model uncertainty quantification and comparison with other sources on uncertainties, using innovative methods related to Bayesian Neural Networks and Deep Learning, in relation to more traditional physics-based modeling.

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ab initio simulation for X-ray spectroscopy

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-10-2020

SL-DRT-21-0665

jing.li@cea.fr

Advanced nano characterization (.pdf)

Context: Photoemission Spectroscopy (PES) is the most powerful experimental technique to directly access the electronic structure of matter. X-ray Photoemission Spectroscopy (XPS) is common and useful to characterize the chemical composition of materials by detecting the energy level of core electron states. Recent XPS experiments performed at CEA-Leti show that the electron core levels in an alloy material with dopant are shifted systematically with the doping concentration and the alloy-mixing ratio. Such a fact suggests that XPS experiments may give more information on the local atomic structure other than the standard chemical composition. The XPS spectra can be simulated directly by ab initio methods, which helps to correlate the core-level shifts and local structures. Objectives and Tasks: This Ph.D. thesis is devoted to exploring the physical origin of the core-level shift by using a range from ab initio methods at different levels of theory, from density functional theory (DFT), many-body perturbation theories (GW), and quantum-chemistry approaches (coupled-cluster, configuration-interaction, and so on?). The second objective of the Ph.D. is to develop an efficient and reliable method to simulate XPS spectra, to interact with experimentalists internally in CEA-Leti. · Performing ab initio calculations. · Investigate and identify the physical origin of the core-level shift. · Propose and develop an efficient method to simulate XPS spectra. · Apply the developed method to the problems, the systems and experiments carried at CEA-Leti within a collaboration with experimentalists.

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Crystalline anisotropic diffusion model of Heavy Rare Earths in NdFeB permanent magnets

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire des Matériaux et Composants Magnétiques

01-10-2021

SL-DRT-21-0673

cyril.rado@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

Neodymium-iron-boron (Nd-Fe-B) permanent magnets are today's best performing magnets. They represent a strategic challenge for the development of more efficient engines and generators (hybrid vehicles, wind turbines). The major issue is the availability of temperature-stable permanent magnets in a context of limited resources in Heavy Rare Earths (HRE : Dy, Tb). They are used by manufacturers to obtain a high coercivity of NdFeB magnets, i.e. their capacity to maintain their initial magnetization in the demagnetizing field imposed by the application. The increasing demand for NdFeB requires a significant reduction in the content of Heavy Rare Earth while maintaining the high coercivity of these magnets. The development of new magnets must focus on localizing these elements at the periphery of the grains of the magnetic phase, where it is necessary to strengthen the resistance to demagnetization. The aim of the thesis is therefore to control the diffusion of heavy rare earths at the periphery of the magnetic phase. The PhD work will combine an advanced experimental approach (development of single crystals, characterization of diffusion profiles, manufacture of magnets) with a modeling of diffusion kinetics, to understand and define the optimal conditions of localization at the periphery of the grains of the magnetic phase.

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Deep learning for multi-modal and multi-resolution electron tomography reconstructions

Département des Plateformes Technologiques (LETI)

Laboratoire Microscopie Mesures et Défectivité

01-09-2021

SL-DRT-21-0674

zineb.saghi@cea.fr

Advanced nano characterization (.pdf)

With recent advances in instrumentation and numerical methods for inverse problems, electron tomography is becoming a key 3D characterization tool capable of addressing current challenges of miniaturisation of microelectronic devices. With ultra-fast spectrometers for electron energy loss spectroscopy (EELS) and multi-detector systems in energy dispersive X-ray spectroscopy (EDX), it is now possible to acquire several signals simultaneously to reconstruct in 3D the structure and morphology of an object with sub-nanometric resolution, as well as its chemical composition with a resolution of a few nanometres. In the framework of an interdisciplinary project, we have implemented compressed sensing approaches for EELS/EDX tomographic reconstruction from a very limited number of projections. The quality and resolution of the chemical reconstructions were greatly improved, but the volumes were reconstructed separately. The objective of this PhD thesis is to develop a deep learning based methodology to take advantage of the multi-modal and multi-resolution aspect of EELS/EDX tomography. This approach would allow: 1) A gain in execution time and signal-to-noise ratio, 2) Simultaneous reconstruction of the volumes from all signals, 3) An improvement in the resolution of chemical volumes by taking into account morphological information.

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Fast detection of AMR bacteria in water through mid-IR imaging and isotope probing

Département d'Optronique (LETI)

Laboratoire des Capteurs Optiques

01-10-2021

SL-DRT-21-0678

mathieu.dupoy@cea.fr

Health and environment technologies, medical devices (.pdf)

Currently the challenge is to develop automatic and non-invasive measurements to enhance early identification or diagnosis. The optical technologies are the label free methods to detect and identify the chemical composition of the sample. Infrared spectroscopy is a widespread and reliable method to obtain a spectral fingerprint of the sample based on absorption of Mid-IR light. An optical platform has been developed to measure the absorption of light through the sample, combining quantum cascade laser (QCL) and bolometer matrix. The objective of the thesis is to explore the potential of Mid-IR imaging and isotope probing to assess the bacteria antimicrobial resistance. The thesis will aim to create the biological protocol mixing the isotope probe and the constraints of infrared radiation, to carry out the images on several bacteria species, to implement the data processing algorithms in order to evaluate the relevance of this approach.

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Experimental and numerical study of heat storage with phase change material with two heat transfer circuits

Département Thermique Conversion et Hydrogène (LITEN)

Laboratoire des composants et systèmes thermiques

01-10-2021

SL-DRT-21-0684

jerome.pouvreau@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

Thermal storage is a key technological component to decorrelate heat production from its use. For steam, phase change material (PCM) storage technology is particularly relevant for many applications and is benefiting from many researches. However, to make the low carbon energy transition effective, two new needs are emerging, in particular for the production of hydrogen by high temperature electrolysis (EHT) and for "Carnot batteries": use two different fluids for the supply of energy and its restitution; simultaneously load and unload storage. The aim of the thesis is to experimentally study a MCP storage with two heat transfer fluids at a laboratory size. The tests aim to understand the dynamic and thermical behavior of this type of storage, made much more complex due to two heat transfer circuits. In addition, the management of such a storage will have to be redefined compare to the strategies used for a single coolant MCP storage. A modeling part will complete the experimental one in order to define of macroscopic modeling of the storage based on the experimental results.

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Gamification for empowering engineers collectives

Département Ingénierie Logiciels et Systèmes (LIST)

Lab.systèmes d'information de confiance, intelligents et auto-organisants

01-09-2021

SL-DRT-21-0692

sara.tucci@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Technologies, and in particular digital technologies, are part of the range of solutions proposed to address the many societal and environmental challenges, such as the 17 sustainable development goals listed by the United Nations. Faced with the complexity of the systems to be implemented, collective intelligence is a major key to success. Multidisciplinary and holistic, systems engineering practices as formalized by INCOSE, and more particularly in their model engineering based version, are similar to collective intelligence practices, and therefore its performance relies on the group's ability to communicate and therefore on the collaborative work tools shared by the team. However, users often consider the tools as complex and the resulting "misuse" becomes a hindrance to the performance of the collective instead of a stimulus. This thesis aims to explore the fields of serious games and game theory in order to reverse this trend and make software tools allies of development rather than enemies to be fought.

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Optical optimization of reception components in a 3D FMCW imaging system

Département d'Optronique (LETI)

Laboratoire Architecture Systèmes Photoniques

01-09-2021

SL-DRT-21-0697

laurent.frey@cea.fr

Photonics, Imaging and displays (.pdf)

Capturing distance information from a scene is becoming a major asset for certain new applications. A typical example being facial recognition by a cell phone. Different techniques already exist with varying degrees of advantages and disadvantages. Within LETI / DOPT we are interested in several techniques and in particular that based on optical frequency modulation (FMCW). The suggested thesis is articulated around the optimization of the reception module of a miniaturized 3D FMCW imaging prototype. The work will be carried out on 3 optical components to be designed/ simulated and optimized in order to improve the final 3D imaging system. The candidate should have extensive knowledge in optics / simulation / instrumentation and laser interferometry.

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Numerical twins of strained interfaces involving MoS2, III-N and SiC obtained by combining experiments and simulations

Département des Plateformes Technologiques (LETI)

Laboratoire

01-10-2021

SL-DRT-21-0699

cyril.guedj@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

This transversal thesis aims at developing realistic and predictive atomic scale simulations to analyze the interfaces between a substrate and the deposited thin film in relationship with the STM and STEM measurements. This numerical tools will be useful to describe the behavior of atoms at the interfaces to understand and optimize the growth processes. To achieve this goal, an approach mixing the speed of machine learning force fields and the precision of ab-initio DFT calculations will be performed. It is necessary to use several level of descriptions adapted to the physical scale: ab-initio methods for electronic effects at the interface and empirical potentials to describe long-scale elasticity. The coupling between scales will enable a faster or deeper atomistic modeling of realistic systems. Two types of growth will be explored to develop this general methodology: a direct growth on MoS2 or a remote epitaxy on SiC. The use of a recently patended methodology will permit the extraction of the atomic positions from experimental data with the best available precision, which constitutes a major advantage in the verification and validation of all simulations by direct comparison with experiment. Ultimately, this thesis will provide numerical twins of materials and interfaces which should be predictive enough to enable realistic in-silico experiments. Hence, these numerical tools will be very useful to rapidly optimize the technology with maximum precision and confidence.

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Département des Plateformes Technologiques (LETI)

Laboratoire Gravure

01-10-2021

SL-DRT-21-0702

aurelien.tavernier@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

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Methods and digital twins for the implementation of eco conception in R&D from prototypes to pilot lines

Département des Plateformes Technologiques (LETI)

Labo Support et Interface Techno

01-10-2021

SL-DRT-21-0721

olivier.girard@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

The analysis of environmental impact in an industrial context consists in the anticipation of the environmental impact for each phase in the life cycle of a product. This is often not taken into account when new technologies or processes are developed, even though the choices made can have a significant impact later on. You will work towards making the processes involved in making nanodevices the most eco-efficient as possible. This will start at the prototype stage by defining all the potential impacts, including those due to production up-scaling. For this you will need to consider 1) how to measure the environmental impacts 2) how to collect the data on energy and material use in pilot lines, 3) develop an understanding of impact transfer, 4) create tools to adapt the analysis of a pilot line to full scale industrial production. You will have access to data from the CEA pilot lines that will be used to develop digital twins for the pilot lines to test the effects of modifications on the eco-efficiency. You will also work closely with a team of multidisciplinary experts at CEA.

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Optimization of acquisition parameters in measurement and X-ray imaging through simulation

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Electro-magnétisme

01-10-2021

SL-DRT-21-0723

anthony.touron@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

The objective of the thesis is to set up a numerical method for optimizing acquisition parameters in X-ray control (XR). The DISC is developing a simulation software for Non Destructive Testing which integrates a module for X-ray imaging. This module, which corresponds to a digital twin of the testing, allows the operator to reproduce an experimental configuration (source, detector, geometry and material of the object, defects, ...) in order to estimate the result he would observe on a real acquisition and thus evaluate the sensitivity of the method, the limit of detectability of defects or the impact of different parameters (tension and filtration of the tube, acquisition geometry). To define these configurations, the operator has to rely on his own experience, which results in the realization of potentially non-optimal acquisitions. This limitation related to user dependency is particularly critical in cases where the signal sought is very weak, for example in the identification of a small quantity of element in X-ray fluorescence or for X-ray tomography which involves a large number of acquisition parameters. The objective is to make the experimental measurements more robust, by adding intelligence to the existing simulation tool, which would then integrate a functionality to optimize the acquisition parameters. The PhD student will have to propose a numerical method allowing to define, from a set of simulations, the parameters maximizing a given quality criterion. This criterion will be defined as a function of the targeted testing (typically the amplitude of the fluorescence peak or the transmission rate of the X-ray signal) and validated experimentally.

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Additive manufacturing of biocompatible and bioresorbable microfluidic scaffolds for the development of implantable organ-on-chip (OoC) systems

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire de Formulation des Matériaux

01-10-2021

SL-DRT-21-0728

sebastien.rolere@cea.fr

Health and environment technologies, medical devices (.pdf)

The technical and biological benefits of several additive manufacturing (AM) processes, for the elaboration and production of microfluidic scaffolds used in the development of implantable organ-on-chip, will be investigated during this PhD project. AM technics should lead to the development of new complex 3D microphysiological systems, more representative of the in vivo environment. Furthermore, the PhD student will also focus on the development of new transparent biocompatible and bioresorbable polymer materials compatible with the selected AM technics, for the substitution of currently used polydimethylsiloxane (PDMS). Finally, the model microfluidic chips, based on the components developed in DRF and DRT labs, will be included in biological assessment campaigns.

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Eco-Innovation methodogy

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire Micro-Sources d'Energie

01-10-2021

SL-DRT-21-0729

elise.monnier@cea.fr

Health and environment technologies, medical devices (.pdf)

With Grean Deal and Circular Economy Action plan, European and French strategies need innovation methodologies drastically different from actual practices. Research mindset is expected to change from pure technological breakthrough to final purpose, sustainable impact for the economy, the environment and the society. In other words, form Innovation to Eco-Innovation. This paradigm shift is a new challenge that CEA must take up for competitiveness reasons for industrial partnerships, success to institutional programs and young talents attractively. The objective of this thesis is to define the Eco-Innovation methodology that will suit the best CEA?s research and development activities. She'll need to be easily shared, understandable and practiced by CEA's researchers. This research will be conducted with academic specialists of eco-design, societal aspects and with internal CEA's entities for innovation, eco-design and economy aspects. This thesis falls within a PTC Materiaux project called M.U.E. (for Unified Methology of Eco-Innovation).

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Modelization and characterization of nano-compliant effects for localized epiaxial growth of GaN on Si substrates.

Département des Plateformes Technologiques (LETI)

Laboratoire des Matériaux pour la photonique

01-09-2021

SL-DRT-21-0730

guy.feuillet@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

In order to decrease the dislocation density induced by the different crystalline structures between the nitride semiconductor layers and the Si substrates they are grown onto, one often uses localised epitaxy methods. However, these result in the formation of other defects arising between the adjacent nucleation centers. We have developed an original localised epitaxy method by which the crystallites are deposited onto deformable nano-pilars, allowing these crystallites to join without creating any defect. The PhD work we propose aims at a better understanding, for a better control, of the mechanical and thermo-mechanical processes at pla during this process of nano-pendeo compliant epitaxy. This will be dealt with using finite element models so as to predict the mechanical behaviour of these complex nano-structured systems and by using an ensemble of structural nano-characterization tools for assessing the defect and strain distribution in the materials. From the reduction of defects in the epitaxial layers, we expect to address some of the main issues for a number of important applications related to these nitride materials in the opto- and micro-electronic domains.

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Architectured materials for heat exchangers applied to the energy transition

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire de Modélisation et Matériaux pour la Métallurgie

01-09-2021

SL-DRT-21-0731

guilhem.roux@cea.fr

Additive manufacturing, new routes for saving materials (.pdf)

This project concerns the eco-innovation of multi-scale 3D printed architectured structures for innovative reactor-exchangers. The ambition is to improve the performance in terms of kinetics, stability and selectivity of chemical reactions used in the field of hydrogen production or recovery. The structures developed will be optimized by thermal simulation in order to maximize their efficiency by taking advantage of additive manufacturing geometric possibilities. The targeted applications are the production of synthesis gas by catalytic processes: CO2 methanation [1], Fischer-Tropsch reactions, LOHC technology or even the decomposition of NH3. As part of the thesis, it is proposed that one of these applications be treated as a priority. Scientific challenges considered during this thesis will be the development of reliable thermo-fluidic simulation tools at the scale of elementary cells (Representative Elementary Volume) by coupling thermal simulation for the solid part and lattice Boltzmann method for the fluid part. Using an upscaling strategy, modeling at the representative scale of the useful reactors sections (mesoscopic calculation) as well as full scale reactors will be carried out using finite element method (Comsol). A screening of elementary structures will be carried out beforehand in order to identify the most suitable structures for each application, using a design tool for elementary structures. Final expectations will feed several circular economy action levers to reduce economic (competitiveness with more compact, more selective exchangers) and environmental impacts (low in energy and material): increase the process efficiency, increase catalyst lifetimes and decrease in ecological impact through a comparative environmental impact analysis (LCA). This thesis will be a collaboration between DAM/Le Ripault and DRT /Liten. The first year of the thesis will be conducted at Le Ripault (Tours) and the last two years in Grenoble.

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Simulation-assisted imaging for SHM by elastic guided waves: tomography and shape derivative

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Méthodes CND

01-10-2021

SL-DRT-21-0738

tom.druet@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

Structural health monitoring (SHM) consists of monitoring the health of a structure using integrated sensors. In this context, the LIST is working on innovative elastic guided wave tomography methods to image corroded areas on simple geometries: plates and pipes. The subject of the thesis is to adapt to our dynamic problems the so-called "shape derivative" method, mostly used on static data, to develop iterative imaging based on a digital twin. This method allows a high quality reconstruction for complex geometries but implies the resolution of an expensive numerical problem. The quality of the image is also highly dependent of the initialization, often based on the perfect structure, potentially far from the current state. We propose to address these two points as follows: the initialization of the shape derivative will be obtained from existing tomography methods, thus improving convergence by limiting the number of iterations and the effect of local minima. The numerical problem will be solved using transient high-order spectral finite elements, allowing fast and inexpensive computations. The definition of metrics suitable for the comparison of simulated and experimental signals will also be part of the study. The performances will be validated on experimental data representative of complex cases of interest for the industry (corrosion under support, etc.).

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Deep learning based approach for sparse view Computed Tomography

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Electro-magnétisme

01-10-2021

SL-DRT-21-0739

caroline.vienne@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

X-ray Computed Tomography (CT) is a well-established contactless and non-destructive inspection technique for various industrial parts. With its roots in the medical field, it evolved to industry as a key tool for three dimensional (3D) characterization and inspection. Industrial progress brings the need for verification of various objects on the production line and in some cases only the X-ray CT can fit the requirements. However, CT scans take a long time, often up to several hours, to achieve reasonable data quality. This long scanning time is an obstacle preventing integration of CT into production lines. In-line tomography implies strong constraints on the acquisition geometry, such as limited angle and sparse views configuration. Due to missing data, reconstructed images suffer from important artifacts that make the inspection task difficult. Many approaches have been investigated to reduce such artifacts. Among them, those based on deep learning seem promising. Convolutive neural network such as U-Net and generative adversarial networks will be studied for recovering missing projection data. The considered framework consists in creating a first version of the sinogram by projecting the initial reconstruction obtained by a FDK algorithm applied to the original incomplete projections and using the complete sinogram as target. Following the previous training of the neural network on simulated data, a second step will consist in using a transfer learning approach and experimental data sets to train a model able to deal with real data.

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Hardware vulnerability exploitation for FORENSIC's use-cases on mobile devices.

Département Systèmes (LETI)

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-09-2021

SL-DRT-21-0742

driss.aboulkassimi@cea.fr

Cyber security : hardware and sofware (.pdf)

The smartphones as convergent single device have diverse functions and features such as calling, Internet surfing, game playing, banking, storage of personal and professional data. Therefore, it is seems to be a favorite target for data attacker. These targets often include security applications such as software or hardware implementations of encryption functions, or security mechanism such as secure boot, TEE (Trusted Execution Environment), etc. The security features of these recent devices present a real challenge for LEA (Law Enforcement Agencies) within Forensic context. However, state of the art of hardware vulnerability exploitation have shown a potential again this type of security mechanism. There are two main categories of physical attacks: the observation of side channel such as correlation power analysis, and perturbation based especially on fault injection. For example, in [1] authors show that by using Electro-Magnetic Analysis some secret related to TEE can be retrieved. In [2], authors show how faults injection method based on Electromagnetic pulse, allow elevation of privilege achieved by authenticating with a wrong password. Within this framework, this thesis will study the opportunity that offer physical vulnerability to bypass the security functions or to extract secrets from Smartphones. First, the PhD student will explore new methods to resolve synchronization problem, especially, when it is required to synchronize attack bench and target execution time, in order to increase the success rate of attacks. The next topic that will be addressed by the PhD Student consist in applying a relevant scenarios for forensic applications, by developing an automatic tools, for example to define the OS instruction to be exploited by fault injection, or to ensure that the obtained results are the same when we change the target or switching set-up On/Off vice versa. In fact, this thesis is part of the H2020 EXFILES project. EXFILES consortium including academics, industry partners and law enforcement agencies from 7 European countries. The work to be achieved within the framework of this thesis, will allow completing the existing Forensic analysis tools.

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Multi-architecture programming for high performance passive tomography reconstruction

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Développement Informatique

01-03-2021

SL-DRT-21-0745

hamza.chouh@cea.fr

Factory of the future incl. robotics and non destructive testing (.pdf)

Structural Health Monitoring is a set of non-destructive testing methods that aim to be directly integrated within the structures to control. This allows for continuous structural testing without disabling any equipment or involving additional human resources or testing hardware. Passive ultrasonic tomography uses structural noise of specimens to monitor their thickness. This method is dedicated to specimens that can be described as wave-guides. It is particularly useful to detect corrosion and erosion defects. The testing process implies dealing with large amount of numerical signals and applying various algorithms to them. In order to embed SHM controls into lightweight and low energy equipment, this thesis aims the development of a full passive ultrasonic tomography toolchain. This will require the evaluation of several hardware architectures (GPU, Low power GPU, FPGA) to find the best-suited ones. To this end, the student will produce high performance implementations of the tomography algorithms on the selected architectures and compare them with the performance obtained via a generic approach like Sycl. The development process should be flexible enough to provide maintainable and scalable software in order to ease the integration of future evolutions of the passive ultrasonic tomography method.

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New approach for advanced logic devices contact plasma etching

Département des Plateformes Technologiques (LETI)

Laboratoire Gravure

01-10-2021

SL-DRT-21-0747

francois.boulard@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

CEA-Leti and partners are actively developing quantum computing based on silicon platform. While the interest of such technology is to be compatible with industry, some processes require improvements to achieve sub nanometer control. Among them contact etching is challenging. On billions of contacts etch simultaneously, the lateral critical dimension and the over etch of the stop layer should be mastered to reach dispersion below 1nm and less than 1nm consumption, respectively. To answer to these challenges, we propose to implement gas pulsing on fluorocarbon based plasma etch chemistry. Such approach cycles deposition of a reactive layer and its activation. While it allows theoretically to reach contact etching requirements, its practical demonstration should be done. The work will be mainly experimental and will take place on a 300mm clean room facility. First, experiments on silicon oxide and nitride blanket wafers will be carried out in order to understand the impact of gas pulsing on etch rates. The fluorocarbon reactive layer composition will be characterized by X-ray photoelectrons spectroscopy in order to improve the plasma surface understanding and to optimize the pulsing strategy. Second, learnings will be applied on contact patterned wafers. Cross section scanning electron microscopy and transmission microscopy will be use to evaluate the amount of aspect ratio dependent etching and stop layer consumption. These informations should confirm or reverse proposed mechanisms. Also, an exploratory study will target to quantify charged particles trapped at the contact bottom by capacitance voltage measurements. The final output of the work will be to implement contact plasma etch processes with gas pulsing on real qu-bits demonstrator wafers.

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Characterisation of microstructural effects related to the smartcut of SiC

Département Composants Silicium (LETI)

Laboratoire Intégration et Transfert de Film

01-11-2020

SL-DRT-21-0749

christelle.navone@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

The automotive industry, with the recent expansion of the electric vehicles market, requires wide band gap devices, like SiC, that are more powerful and robust than the Si equivalent devices. However, SiC substrates are still very expensive and their supply is limited by the American and Asian monopoly of SiC wafer fabrication. The aim of this thesis is to create an innovative SiC substrate based on Smart Cut? technology : transfer of a thin SiC monocristalline layer on a cheaper substrate, typically SiC polycristalline wafer. The objectives of this research work are : - To deepen the understanding of SiC surface phenomena as function of the heat treatment of the wafers. This study will be based on annealing tests coupled with substrate surface analysis (AFM, PEEM, Raman, XPS) allowing the surface reconstruction mechanisms to be determined as function of the process parameters. The conditions of Graphene formation on the surface of the substrate should be particularly investigated in order to identify the solutions allowing to limit the SiC topological modification. - To understand the nature of SiC defects induced by the Smart-Cut technology step. The determination of the defects will be based on physico-chemical analysis such as photoluminescence, cathodoluminescence, etc. Chemical analyses based on KOH can also be used to reveal the defects on a larger scale. The propagation kinetics of these defects and their impact on the electrical conductivity will be investigated.

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Multi-functional material for catalytic hydrogenation of CO2 to methanol and dimethyl-ether

Département Thermique Conversion et Hydrogène (LITEN)

Laboratoire réacteurs et procédés

01-09-2021

SL-DRT-21-0750

albin.chaise@cea.fr

Additive manufacturing, new routes for saving materials (.pdf)

Hydrogen production by water electrolysis coupled to catalytic hydrogenation of CO2 into hydrocarbon or oxygenates of high energetic Density (methanol, DME) can contribute to the decarbonation of transportations (sea, air transportation) and provide products for a sustainable chemistry. However, these reactions are limited thermodynamically. The current PhD proposal aims at developing a coupled system of catalytic reaction (CuZnO/Al2O3 and zeolites), de-hydratation by separation and/or adsorption of water (ZSM5 and LTA zeolites) for direct synthesis of methanol and DME form CO2. Non-critical and recyclable material (Cu, Zn, Al) and low environmental footprint processes (supercritical CO2, hydrothermal, micro-waves) or bio-templates. One essential goal will be to obtain 3D oriented zeolites with limited defaults, first on planes surfaces then on 3D structures (ceramics or metal). The intrinsic material performances will first be tested on samples. Then the material will be integrated in a 3D reactor with catalysts at the scale of a few L/min of reactants.

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Modelisation and optimization of 3D micro-fabrication processes for optical applications

Département des Plateformes Technologiques (LETI)

Laboratoire

01-10-2021

SL-DRT-21-0751

SEBASTIEN.BERARDBERGERY@cea.fr

Numerical simulation (.pdf)

The realization of 3D micro-structures is needed to build key functional microelectronics elements such as micro-lenses for optical imagers. These lenses can be done in particular by resist reflow or grey levels (grayscale) lithography. Grayscale lithography has the advantage of building structures of different topographies within one single process step. Its success will depend on the process modelling accuracy and on the lithography mask optimization strategy. Grayscale lithography was developed and pushed these past three years at CEA-LETI by a CIFRE PhD thesis in collaboration with ST-Microelectronics. The objective is to pursue 3D fabrication opportunities opened towards optical applications (Imagers, diffractive components) but also augmented reality. The thesis work will focus on different methodologies of design and data preparation for the optical mask realization. Especially, in order to maximize the lithography fidelity, non regular pixelization on mask or neural-network based inverse problems will be investigated. The resist process modelization during the 300 mm grayscale lithography will be also crucial and essential for the thesis.

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Numerical simulation for processing powder bed additive manufacturing

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire de Modélisation et Matériaux pour la Métallurgie

01-09-2021

SL-DRT-21-0752

guilhem.roux@cea.fr

Additive manufacturing, new routes for saving materials (.pdf)

The project concerns the study of powder spreading in the context of powder bed additive manufacturing processes, in particular L-PBF (Laser-, Powder Bed Fusion) and MBJ (Metal Binder Jetting) processes. The ambition is to give CEA a reliable simulation tool making it possible to reproduce what happens during this process key stage, when the real powder bed (intended to be melted or agglomerated depending on the technologies) is spread out. This project will be fed by results from a dedicated instrumented spreading set-up as well as by elementary experiments. The simulation will be based on DEM method (discrete element method, [1]), benefiting from developments acquired by the partners (DES/IRESNE) in powder transitics and from first developments in progress at DRT / LITEN. The particle interaction behavior models will be fed by a wide range of real characterizations under elementary flow conditions. The models will then be initially compared on these elementary tests, then ultimately on real full-scale results obtained on the specific DRT/LITEN spreading set-up. Today, several works are carried out on this subject ([2] [3] [4] [5]), but they take into account idealized, spherical and mainly monodisperse powders. The originality of this work compared to the state of the art is to investigate beyond the behavior of model powders by taking into account real morpho-physico-chemical state of various powders (surface roughness, sphericity, charge electrostatic effect, effect of humidity, effect of oxidation state,?) of powders. In particular, one objective will be to understand the mechanisms powders ageing and their consequence on flowability, a real industrial issue. In addition, this study will show the consequences on the flowability of composite powders developed at CEA ([6] [7]). This thesis will be a collaboration between DES/IRESNE and DRT/LITEN.

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Integration of RF switches based on chalcogenide phase change materials

Département Composants Silicium (LETI)

Laboratoire Composants Radiofréquences

01-10-2021

SL-DRT-21-0754

bruno.reig@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

In order to meet the future needs of 5 / 6G cellular networks and SATCOM satellites, It is necessary to develop RF systems with higher performances and agility. In this context, new RF switch technologies based on chalcogenide phase change materials have gain strong attention as they promise to offer disruptive solutions to realize miniature and high speed reconfigurable RF circuits with low power consumption and that can be easily integrated with CMOS circuits. The objective of the PhD thesis is therefore to develop a new RF switch technology based on chalcogenide materials for future wireless telecommunications systems. The requested work is multidisciplinary and will be carried out in close collaboration between three division of the CEA-LETI bringing their expertise on the synthesis of new materials, on the technological integration of innovative RF components and on the development of advanced electronic functions. The PhD student will define the main specifications of the switches for the targeted applications and will seek to identify the key properties required for the phase change material. He will evaluate various alloys of chalcogenide materials and will develop a technological flow for switches in order to optimize the reliability and the performance of the component. Finally, he will design innovative RF circuits and he will study the influence of design parameters on the overall system performance within an application demonstrator.

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DNA based 2D qbits network

Département des Plateformes Technologiques (LETI)

Laboratoire

01-10-2021

SL-DRT-21-0759

raluca.tiron@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

In nanotechnology in general and semiconductor industry in particular, there is an ever increasing need for smaller and more complex features at an ever lower cost. Some examples of applications are sub-10 nm features for creation of FinFETs, lateral (horizontal) and vertical gate-all around nanowires, single electron transistors and advanced non-volatile memories (STT-RAM, MRAM, OxRAM, etc.). To address the challenge of patterning at sub-10 nm features novel patterning approaches must be envisioned. DNA (deoxyribonucleic acid), by virtue of its inherent small diameter (2 nm), tendency to self-organize into various different morphologies and its possibilities for functionalization, offers the possibility to realize both two- and three dimensional structures at nanometer scale. The goal of this PhD work is to demonstrate the feasibility of nanostructuring the surface of a substrate using DNA origami as a mask, with an ultimate resolution of a few nanometer and with a density that is above the current state of the art in semiconductor industry. The focus of the thesis will lie on ever more complex features, while ensuring long-range order by conventional lithography guide patterns. The targeted demonstrator consists of manufacturing a 2D network of qbits based on DNA origami self-assembly.

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3D structuration by selective deposition

Département des Plateformes Technologiques (LETI)

Laboratoire

01-09-2021

SL-DRT-21-0760

guido.rademaker@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Traditionally, the industrial manufacturing of semiconductors consist of a loop of several process steps: deposition of materials - lithography - etching - stripping. This cycle is repeated multiple times to create a 3-dimensional structure. For applications of the type "More than Moore", a flexibility in the structuration is asked. For "More Moore" applications, the limits of the materials are found and innovative processes often consist of a combination of deposition - etching or lithography - deposition. This thesis is hosted at CEA-Leti's Advanced Lithography Laboratory, with access to traditionall photolithography, as well as self-organizing polymers such as block copolymers and DNA origamis. All of these materials have a capability to form 3D polymeric matrices. Instead of following the lithography by etching, we want to explore the hardening or functionalization by epitaxial growth, or a deposition step such as Chemical Vapour Deposition (CVD), Atomic Layer Deposition (ALD) or even Sequential Infiltration Synthesis (SIS). Depending on the application, a functionalization of the 3D surface by chemical treatment can be envisioned, to arrive at applications like biological sensors or meta-materials for optics and/or mechanics. The work in this thesis starts with a literature survey, followed by the evaluation of the feasability of integration at CEA-Leti. A 3D organic matrix will be created using the polymer and process chosen, followed by a step of growth or deposition, removal of the organic matrix, and 3D characterization and metrology of the structure, with as final result a morphological demonstrator. In case of promising results early in the thesis, in a collaboration with the applicative departments a functional demonstrator could be envisioned. The work finishes by the redaction of the thesis manuscript and its defence in front of a scientific jury.

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Use of polymers for the transfer of single-crystal thin films

Département des Plateformes Technologiques (LETI)

Laboratoire

01-04-2021

SL-DRT-21-0761

pierre.montmeat@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Organic polymers are versatile materials: they are good insulator, are easy to process for the elaboration of thin films and exhibit a high thermal resistance. For these reasons, they can be used for the elaboration of substrates for microelectronic purposes. In this field, the PhD work aims at the elaboration of innovative structures in which a single-cristal semi-conductor is attached to a polymer.

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development and characterization of conformable piezoelectric materials for medical application

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire Composants Organiques

01-10-2021

SL-DRT-21-0767

mohammed.benwadih@cea.fr

Health and environment technologies, medical devices (.pdf)

Recent advances in materials, manufacturing, biotechnology, and systems have favored many sensors and actuators based on flexible, biocompatible piezoelectric materials in medical fields.In this internship, the principles, the future opportunities and challenges in the development and characterization of conformable piezoelectric materials for medical use will be examined. An expandable piezoelectric sensor / actuator, made on a stretchable substrate, will be developed with materials (composites / polymers) deposited by printing methods. These developments will make it possible to study the feasibility of using such piezoelectric components in the field of medicine. The PhD student, with the teams in place, will develop a piezoelectric component on a stretchable substrate, via (i) the use of an intrinsically stretchable piezoelectric polymer or via (ii) the implementation of composite materials (inorganic piezoelectric particles in a matrix polymer). The intern will also have electrical characterization work to be carried out on these components. This internship will take place as part of a collaboration between the LGEF laboratory of INSA LYON for piezoelectric characterizations and CEA_Liten for material choice / process development aspects and material characterization.

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Ecodesign applied to battery systems

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Prototypage et Procédés Système

01-10-2021

SL-DRT-21-0772

remy.panariello@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

The environmental impact of an electric vehicle, when used in a country such as France, is dominated by the production of the battery packs it contains. Work is on-going to find more sustainable battery chemistries. But in the meantime, is it possible to substantially reduce the environmental impact of a battery pack, by only working on the parts and assemblies surrounding the cells such as: mechanical structure, thermal management system, or embedded electronics? In this project, we propose to identify and evaluate various alternative designs aiming to reduce the environmental impact of automotive battery packs, focusing on "climatic impact" and "mineral raw materials" criteria. We will rely on Life Cycle Assessment and eco-design methods to assess state-of-the-art packs, and identify promising ways of improvement: new thermal or electrical management strategies, new mechanical designs, material selection or new material development. The evaluation and research for trade-offs should be carried out with of the help of simulation tools. We will then assess the viability of some of the solutions by building physical demonstrator(s), especially with the help of additive manufacturing processes. The project will happen in Grenoble (France), in close collaboration between various research units: department for Energy applied to transports (DEHT), department for new materials (DTNM), Life Cycle Assessment and eco-design lab (G-SCOP). It will cover various scientific domains such as: Life Cycle Assessment, numerical simulation, materials sciences, mechanical design, or manufacturing processes.

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Multi-criteria thermo-economic analysis and optimisation of complementarities between CO2 (CCU), biomass (BE-CCS) and the electrical vector (H2 production, battery storage), within the framework of the French and European energy mixes.

Département Thermique Conversion et Hydrogène (LITEN)

Laboratoire des systèmes énergétiques pour les territoires

01-10-2021

SL-DRT-21-0778

guillaume.boissonnet@cea.fr

Green and decarbonated energy incl. bioprocesses and waste valorization (.pdf)

Within the framework of studies on the closing of the carbon cycle, it is essential to look at the complementarity between several sources of carbon (CO2 and biomass) and sources and vectors of decarbonated energy (electricity, H2). This constitutes a complex system including many variables and constraints, which it is necessary to study with means of optimization and multi-criteria analysis, in order to make the most of it. The thesis will be articulated around 3 axes - Elaboration, consolidation of a methodology for optimization and multi-criteria analysis of energy systems including non-fossil carbon as a material resource and decarbonated energies. - Development and consolidation of a database of technological solutions including non-fossil carbon as a material resource and decarbonated energies. - Study of several systems according to the philosophy of the scheme: coupling carbon and electricity, in particular through hydrogen.

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Area selective deposition of oxydes for microelectronic

Département des Plateformes Technologiques (LETI)

Laboratoire

01-10-2021

SL-DRT-21-0781

chloe.guerin@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

In order to reduce the manufacturing costs of integrated circuits and continue their miniaturization, disruptive approaches based on the use of selective deposition processes are now being considered in addition to photolithography. Recent developments are mostly linked to the use of atomic layer deposition (ALD) which is a very suitable technique for the development of a selective process due to its high sensitivity to surface chemistry. ALD is a thin film deposition method based on the self-limited adsorption on a surface of gas phase precursors and surface reactions between precursor molecules and a reagent, allowing atomic-scale control of the thickness and quality of the deposited material. The objective of this thesis concerns the development of a localized selective deposition (ASD for Area Selective Deposition) based on the use of an organic layer allowing the deactivation of surface chemical reactions in ALD. This organic layer should act as an inhibition layer of ALD which allows selective deposition by zone. In the literature, this approach generally uses self-assembled monolayers (SAM) which may have limitations in terms of density and thermal or chemical stability. In this project, we will focus on the development of inhibition thin films deposited by vapor-based processes with the aim of finding a versatile method to allow the selective deposition of metal oxides. In addition to the selectivity with ALD deposits, the selection criteria will be the thermochemical stability of the inhibition layer in order to support the ALD process conditions as well as the possibility of depositing thick oxide layers. During this thesis, the PhD student will have access to several deposition techniques (ALD, PECVD, iCVD) as well as to a rich nano-characterization platform (ellipsometry, FTIR, contact angle, AFM, XPS, Tof-SIMS). These surface analyzes and thin film characterizations will allow to identify the best approach in order to obtain the highest possible selectivities. Fine characterization of organic and inorganic films at the nanoscale will also be carried out on patterned structures. One objective of this work will be also to highlight the mechanisms at the origin of selectivity as well as defect formation. Finally, the ASD process will be implement for the realization of an (opto) electronic demonstrator.

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Integration of Teraherts III-V transistors on silicon substrate for submillimeter wave applications

Département Composants Silicium (LETI)

Laboratoire d'Intégration des Composants pour la Logique

01-10-2021

SL-DRT-21-0796

herve.boutry@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

Wireless technologies have advanced by leaps and bounds over the last several decades. Speeds have increased dramatically, connectivity has improved, and wireless network protocols, including Wi-fi and cellular, have become ubiquitous. Yet, despite a reasonnably fast, persitent wireless connection available in most parts of the world, today's wireless networks are still relatively limited in terms of how they can handle large volumes of data. The need for bandwith is growing and Terahertz communications, at frequencies of 300Ghz, could adress this problem. Multichip modules may present a possible solution to the mmW integration problem but at these frequencies, the lateral arrangement of chips on a carrier substrate comes at the cost of transmission line and contact losses. A preferred arrangement is the vertical 3D integration of mmW semiconductor devices or building blocs on top of the CMOS chip which could leverage the electrical specifications of the combined circuits.

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Quantum computing for logistics and industrial applications

Département Ingénierie Logiciels et Systèmes (LIST)

Labo. ingénierie des langages exécutables et optimisation

01-03-2020

SL-DRT-21-0797

florian.noyrit@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

Quantum computing sounds promising to solve computational problems that classical computing cannot address practically because of their complexity. However, despite its promises and the recent development of quantum technologies, industrial applications of quantum computing are so far limited. Nevertheless, recent developments of some quantum algorithms (e.g. Variational Quantum Eigensolver [1], Quantum Approximate Optimization Algorithm [2]), running on existing or upcoming quantum devices (NISQ - Noisy Intermediate-Scale Quantum) [3], suggest many opportunities for near/mid-term applications in solving some optimization problems. Logistics and industrial engineering are application fields that offer optimization problems (scheduling, planning, routing?) complex to solve with classical algorithmic. Some theoretical analysis and early experiments [4] already draft some viable applications for quantum computing techniques. However, because it is a living research topic, knowledge on these topics is scattered, unstable (new algorithms are proposed frequently), sometimes speculative, and not generalized yet. We therefore propose to explore the application of recent quantum computing techniques (notably hybrid algorithms and NISQ-applicable) on some optimization problems from our industrial projects. The objectives of this research work will be the followings: ? Select relevant optimization problems from our ongoing or past projects in fields of logistics and industrial engineering. ? Select quantum algorithms applicable to those problems from state of the art and state of the practice and implement them. ? Adopt or devise a benchmarking framework that can evolve along with the progresses in the field of quantum computing-based optimization. : computing time optimization, problems size, computer size ... ? Evaluation of the technical viability through concrete experiments. The evaluation will notably aim at analyzing the applicability factors such as the convergence properties of algorithms, the impact of the formulation of the problem on the effectiveness, the influence of the hardware architecture. More generally, the evaluation must give insights on the qualitative and quantitative thresholds (number of qubits [5], connectivity, noise?) that make the algorithm viable on NISQ devices (existing or upcoming). ? Propose and develop solutions to make the algorithms viable. For example, by adapting or extending the algorithms, proposing rewritings of the problem formulations, by implementing a particular compilation flows, by adapting the architecture of the execution platform... This work implies the access to actual or emulated quantum computing devices to run the experiments. Experiments are expected to be run on various platforms. This PhD will be carried out at Grenoble. [1] A variational eigenvalue solver on a photonic quantum processor, Peruzzo et Al., 2013 [2] A Quantum Approximate Optimization Algorithm, Edward Farhi and Jeffrey Goldstone and Sam Gutmann, 2014 [3] Quantum Computing in the NISQ era and beyond, John Preskill, 2018 [4] Quantum Computing Algorithms for optimised Planning & Scheduling (QCAPS), Dr Roberto Desimone et Al. 2019 [5] Guerreschi, G. G., & Matsuura, A. Y. (2019). QAOA for Max-Cut requires hundreds of qubits for quantum speed-up. Scientific reports, 9(1), 6903. The candidate should have good knowledege in one or more of the following topics : ? Quantum information and computation ? Combinatorial Optimisation ? Linear Algebra ? Algorithmic Complexity

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Tactile-based learning and classification methods for task planning and verification ? applications to multi-digital and bimanual robotic manipulation

Département Systèmes (LETI)

Laboratoire Signaux et Systèmes de Capteurs

01-09-2021

SL-DRT-21-0803

saifeddine.aloui@cea.fr

Artificial intelligence & Data intelligence (.pdf)

The robotic manipulation of objects first of all requires a grasp planning of these objects, which is a function of the characteristic parameters of the considered hardware tools and the task to be performed (such as the accessibility areas or the level and direction of the efforts that may be involved in the tasks of assembly, insertion, dexterous manipulation, etc.). In addition, during the execution of the task, it is necessary to be able to ensure the nominal progress of the planned task, by detecting the occurrence of certain critical events necessary for its completion (such as the interaction of objects with each other, the loss of stability of the object, etc.) and then validating the actual completion of the planned task (via the classification of data that characterizes the success or failure of tasks such as insertion or assembly). These detection and verification steps, which are crucial when it comes to robotizing certain critical tasks requiring a high level of traceability, can be based in particular on the analysis and monitoring of data or signals specific to the handling system in question. The work requested will exploit an experimental system consisting of a two-handed station, equipped in particular with two multi-digital grippers equipped with multimodal tactile sensors developed by the CEA. This thesis work is essentially divided into two parts. The first part consists in the use of learning methods, which are able to take into account the capacities of the pluridigital manipulators and the imperatives of the task, to plan the grasping of the objects. The second part of the thesis aims at exploiting some methods based on the classification of tactile and proprioceptive signals of the system to validate the accomplishment of the task.

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Charge-transfer complexes used as electrolyte for solid state lithium batteries

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Matériaux

01-10-2021

SL-DRT-21-0804

laurent.bernard3@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

While lithium-based batteries are already the energy storage technology of choice for small- and medium-scale devices, their widespread implementation in large-scale applications like, for instance, electric vehicles remains hampered in particular by safety concerns. These concerns are, in fact, basically related to the commonly employed liquid organic electrolyte, comprising toxic, corrosive, and unstable LiPF6 as conducting salt. Thus, one of the major targets of actual research activities is the replacement of such electrolytes by intrinsically safer alternatives, including solid inorganic and polymer-based systems, both providing intrinsic advantages and challenges. Solid-state electrolytes could resolve all of these problems. However, most candidate materials have much lower ionic conductivity compared to that of liquid electrolytes, which reduces the power density of the cell and limits their practical applications. PEO-based electrolyte have been widely studied and their implementation is still hindered by their low ionic conductivity at 20°C. A new class of polymer-based materials is studied and developed at CEA, they are showing higher ionic conductivities than standard liquid electrolyte at 20°C while having a high Tg ( >80°C), wide electrochemical stability window and they have be proven to be stable on Li metal. Moreover, due to their properties, these materials can easily be processed by hot melt extrusion allowing reducing the final cost of the electrolyte. The PhD aims at synthesizing these new materials and mainly characterizing the Li-ion mobility and mechanism in these new materials. After a step of synthesizing these new materials ( molecular or polymer based materials), the PhD candidate will have access to large panel of technique to fully characterize their properties : DSC, TGA, HPLC-MS, NMR, IR, UV-Vis spectroscopy, EIS, cycling, li transference number ? . More advances characterizations techniques such as PFG-NMR, Quasi-elastic neutron scattering and SAXS could be used to better characterize the Li-ion diffusion mechanism within these materials. The performance of the materials with the most promising ionic conductivity will then be tested in all-solid-state batteries.

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Edge-IA autonomous systems for biodiversity protection

Département Systèmes (LETI)

Laboratoire Autonomie et Intégration des Capteurs

01-10-2021

SL-DRT-21-0808

esteban.cabanillas@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

Within the framework of technological development for biodiversity protection, measurement tools to precisely quantify the impact of human activities (agriculture, wind turbines, antennas, urban sprawl, etc.) and strategies implemented for biodiversity protection have yet to be developed. The proposed thesis aims to overcome this lack by proposing to develop an autonomous and reliable on-board electronic system for monitoring and quantifying biodiversity. The thesis will be based on advanced technological solutions using edge artificial intelligence (edge AI), energy harvesting and energy management (photovoltaic modules, battery, energy management circuit), data processing from various sensors (audio, video) and low-power electronics (hardware and firmware), particularly for data processing and communication aspects. The core of the thesis will therefore focus on minimising the hardware and firmware energy consumption of embedded electronic systems implementing artificial intelligence for the application "monitoring and protection of biodiversity". A complete electronic device (hardware + firmware) implementing these innovations and deployed in real situations is expected by the end of the thesis.

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novel integrated circuit topologies using innovative capacitive components on silicon

Département Composants Silicium (LETI)

Laboratoire Stockage et Microsources d Energie

01-10-2021

SL-DRT-21-0814

sami.oukassi@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

The objective of this thesis is to assess the potentiel of hybrid silicon capacitors developed at LETI as components in novel architectures of integrated energy conversion circuits. The hybrid capacitors exhibit a combination of unique properties in terms of energy density (ionic storage of the order of 40 mJ / mm3) and frequency response (dielectric storage demonstrated up to 30 GHZ), in addition to a technological realization on 200 mm silicon wafers. Within the framework of this project, it is proposed to design energy conversion circuits (eg. DC-DC converters)exploiting the intrinsic properties of the hybrid capacitors developed at LETI.

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Development of an operando gas analysis setup for all-solid-state batteries and study of the impact of doping on electrolyte stability

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Analyse électrochimique et Post mortem

01-09-2021

SL-DRT-21-0815

irina.profatilova@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

Doctoral project will focus on the development of the characterization setup for all-solid-state batteries and conducting operando gas analysis for development of safer solid electrolytes. All-solid-state batteries represent a cutting-edge field of the development of modern batteries for electric transportation of the future. First precommercial batches of solid cells with sulfide electrolyte have been demonstrated by Samsung (cycle life: >1000 cycles). However, there is still a lot of issues to understand and solve for further wide commercialization of this type of batteries. The main obstacle for sulfide-based electrolytes is their instability vs humidity. Another problem is related to the possible gas evolution during cycling. Characterization methods for all-solid-state batteries are in the early stage of their development. There is a high demand for scientific tools and methods for investigation of various effects leading to gas generation inside the batteries and their degradation, which is directly related to their safety. The objectives of the present project are 1) development of the experimental setups for a precise study of reactions of solid electrolytes leading to gas generation in various conditions and 2) obtaining of improved electrolyte for solid batteries based on the deep understanding of its reactivity. There are three principal interconnected parts: construction and improvement of setups, conducting of fine analysis of electrolytes and synthesis of an improved solid electrolyte sample. The project will be done in French Commissary of Atomic and Alternative Energies (CEA) located in Grenoble. It is known for its excellent set of equipment and expertise in the research and development of greener energy, notably in batteries. This center offers an opportunity to join a dynamic team and to conduct a high-level research in a multidisciplinary environment. Grenoble area is a famous hiking and skiing resort. We are looking for a motivated and pro-active candidate for a Ph.D study starting in autumn 2021 for 3 years. There is a health insurance for the foreigners. Good oral and written English as well as capability to make literature reviews and write papers are essential. The experience acquired by the student during the Ph.D study will be undoubtedly of high interest for further employment.

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Qualitative reasonning and design of complex systems

Département Ingénierie Logiciels et Systèmes (LIST)

Labo. ingénierie des langages exécutables et optimisation

01-04-2021

SL-DRT-21-0823

jean-pierre.gallois@cea.fr

Numerical simulation (.pdf)

The design of complex systems is an activity that affects many industrial and research fields. This implies difficulties in modeling and simulating by the heterogeneous nature of the data involved, with discrete and continuous aspects. Two approaches are possible. Quantitative methods, whose analyzes are numerical, are the most used: their results are precise but they consume a lot of time and resources. Qualitative methods are based on a symbolic interpretation of the models, and can be used without knowing all the numerical parameters, by relying on dependency relationships between variables. They are less precise but they can be applied very early in the design phase and can be used to plan numerical simulations according to the objectives and to improve the results of analyzes (proofs, optimization, etc.). The work already carried out at the LIDEO laboratory of CEA LIST on modeling and qualitative simulation will be extended by the integration of concepts from naive physics and common sense reasoning to lead to an approach closer to engineering concepts. The results will be used for modeling, simulation but also for optimization on case studies representative of industrial examples.

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Exploring learning techniques for "Edge AI" taking advantage of Resistive RAM

Département Systèmes et Circuits Intégrés Numériques

Laboratoire Systèmes-sur-puce et Technologies Avancées

01-09-2021

SL-DRT-21-0825

Francois.RUMMENS@cea.fr

Artificial intelligence & Data intelligence (.pdf)

Today's computer architectures are inefficient in handling the simulation artificial neural networks, hindering their application in power-constrained environments, such as edge computing and the Internet of Thighs. Dedicated hardware implementations of neural networks that combine the advantages of mixed-signal neuromorphic circuits with those of emerging memory technologies have the potential of enabling ultra-low power processing suitable for edge computing. These new circuits and technologies have the potential to endow the system with the ability to learn at the edge. This breakthrough, which is unattainable using conventional approaches, can have many advantages, as it enables adaptation to changing input statistics, reduced network congestion, and increased privacy. However, current approaches often focus on learning algorithms that cannot be reconciled with the non-ideal physical behaviour of resistive memories. This thesis aims at exploring various algorithmic solutions for inference and learning in order to propose neural network architectures more adapted to the reality of the resistive memory technologies developed at LETI.

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Reliability of 3D avalanche photodetectors

Département Composants Silicium (LETI)

Laboratoire de Caractérisation et Test Electrique

01-10-2020

SL-DRT-21-0830

jean.coignus@cea.fr

Photonics, Imaging and displays (.pdf)

STMicroelectronics develops various CMOS-based technologies for imaging. The rise and democratization of image sensors is leading to a diversification of technological uses such as high-resolution imagery and telemetry for domestic and automotive use. One of the challenges is to meet market needs and adapt to the competition by constantly improving the performance and reliability of devices. The objective of this thesis is to study and model the reliability of avalanche photodetectors for single photon detection. The principle of this sensor lies in the ability to measure the transit time between an optical source and the detector, from a few centimeters to several tens of meters while being insensitive to the surrounding light. A matrix made up of thousands of pixels makes it possible to restore a faithful 3D image of the target. To date, first tests show that the detector degrades over time, leading to a loss of sensitivity and degradation of measurement precision. Quantifying these effects and understanding these drifts is absolutely necessary to improve the manufacturing process and develop a predictive model of reliability. The thesis will focus equally between the reliability of a single pixel and the reliability of a pixel matrix, in order to approach product reliability. The candidate will rely on a set of characterization and reliability measurement tools, as well as modeling and simulation tools developed at STMicroelectronics.

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Integrated circuits for electromechanical tuning of MEMS devices

Département Composants Silicium (LETI)

Laboratoire Gestion de l'Energie, Capteurs et Actionneurs

01-09-2021

SL-DRT-21-0837

gael.pillonnet@cea.fr

Cyber physical systems - sensors and actuators (.pdf)

The Phd objective is to explore electromechanical tuning techniques dynamically to modulate the resonant frequency and quality factor of electrically-coupled MEMS devices.

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Prediction of PEM water electrolyzer lifetime by multi-physics modeling

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Modélisation multi-échelle et suivi Performance

01-10-2021

SL-DRT-21-0838

pascal.schott@cea.fr

Advanced hydrogen and fuel-cells solutions for energy transition (.pdf)

The cost of proton exchange membrane water electrolyzer (PEMWE) remains the bottleneck for moving the technology to the market place. A tradeoff between the loading of the catalyst and the objective to reach 80 000 hours of lifetime with high efficiency is necessary. The future generation of MEA (Membrane electrode assembly) have a low loading of catalyst (0.4mg.cm² at the anode side) with a thin membrane. The effects of ageing phenomena become visible during the first thousand hours. Different strategies to improve the lifetime exist, from material improvement (catalyst loading, coating) to optimal operating strategies of the electrolyzer. The challenge is to estimate the gain of lifetime without running a full test (80000 hours). Some AST (Accelerating Stress Tests) are developed to evaluate the new developments on lifetime. The objectives of this PhD thesis is to improve the understanding of degradation mechanisms and predict the lifetime of PEMWE and in particular the catalyst and membrane degradations inside the MEA (Membrane Electrode Assembly). CEA's multi-physics and multi-scale modeling approach will be used, coupled with in-situ experimental data provided by or collected at NREL. In particular, the modeling of degradation mechanisms in MEA operation will be developed using CEA's strong background on fuel cell modeling, including degradation mechanisms that lead to catalyst and membrane degradation. The following focus areas will be addressed: ? Statistical analysis of experimental data to correlate the main degradation mechanism to the operating conditions ? Development of the catalyst and membrane degradation models, based on existing CEA model ? Validation of the degradation model based on existing experimental data. New tests will be defined and realized to better identified the model parameters The final objective is to propose new AST for PEMWE. The validation of the new AST on experimental data will be performed. The thesis will be located at CEA Grenoble France, with several missions to NREL, Colorado, USA

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Study and simulation of the behaviour of lithium-ion cell protection elements in short-circuit or overcurrent conditions at pack level.

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Architecture Electrique et Hybridation

01-09-2021

SL-DRT-21-0839

Laurent.Garnier@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

The safety of Li-ion batteries is a major issue in the development of these technologies. In order to best address this issue and to be able to design safe battery systems, the main dreaded events are classified and one or more safety elements are defined for each one. The internal cell faults leading to a thermal runaway are mainly managed by the venting(s) and design elements that prevent the first fault from propagating. Numerous works aim at improving our understanding of these phenomena. External faults, on the other hand, generally have the specificity of being applied at the same time on all or a large part of the battery pack. If the protections are not adapted, badly positioned or badly designed, the consequences can be dramatic. Voltage overloads or over-discharges are managed at the first level by the BMS, while short-circuits/overcurrents are managed by fuses or contactors of the pack or by internal cell protections such as CID or PTC (Current Interrupt Device or Positive Temperature Coefficient). In this thesis we will focus on external faults like short circuits or over currents applied on all or part of the battery pack, thus concerning a large number of cells. If the short circuit occurs on the load, then the battery pack will simply be protected by the fuse, but if this short circuit for an unknown reason (crash, conductive dust, electrolyte leakage, double insulation fault, ...) occurs on a current path not protected by a fuse, then the internal protections of the cells will be solicited. To be sure that they will operate correctly, it is necessary to have correctly characterized them in the different fault modes. The thesis work will be based on three axes of work : - A first experimental axis will focus on the characterization of the cells and their protection in fault conditions. - A second axis will aim to set up cell models before and after faults - Finally, the last axis will aim at building battery pack models allowing to play scenarios according to random fault conditions (impedance and short circuit position).

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Beyond Shannon with Semantic Communications for 6G Networks and Services

Département Systèmes (LETI)

Laboratoire Sans fils Haut Débit

01-06-2021

SL-DRT-21-0844

emilio.calvanese-strinati@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

The future of mobile communications will be characterized by ubiquitous connection availability, very dense networks in terms of number of users and access points, ultra-low latency, very high bandwidth, and energetic efficiency. The 6G network revolution will be enabled by cutting-edge technological innovations, concerning millimeter-wave radio communications, baseband and RF architecture, resources virtualization, and the native support of artificial intelligence. The main goal of this PhD investigation is to motivate the need, in the design of new 6G networks, for a paradigm shift from the mainstream research, which basically builds on Shannon's framework, towards semantic and goal-oriented communications. A game-changing idea consists in exploring semantics in wireless communications to go beyond the common Shannon paradigm of guaranteeing the correct reception of each single transmitted packet, irrespective of the meaning conveyed by the packet. The idea is that, whenever communication occurs to convey meaning or to accomplish a goal, what really matters is the impact that the correct reception/interpretation of a packet is going to have on the goal accomplishment. The PhD candidate will explore the very recently-proposed and innovative concept of wireless semantic communications. The work will focus on the design of algorithms for a proactive and dynamic implementation of semantic communications, targeting the optimal end-to-end efficiency of the joint allocation of the above mentioned resources. Distributed learning techniques will be investigated and proposed.

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Compact and Efficient Power Converters Integrated Circuits for Supply-Modulated RF Power Amplifiers

Département Composants Silicium (LETI)

Laboratoire Gestion de l'Energie, Capteurs et Actionneurs

01-09-2021

SL-DRT-21-0846

alexandre.giry@cea.fr

Communication networks, IOT, radiofrequencies and antennas (.pdf)

The PhD objective is to explore compact and efficient power converter topology integrated nearby RF power amplifier to enhance energy efficiency in 5G/6G context.

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Département Composants Silicium (LETI)

Laboratoire Gestion de l'Energie, Capteurs et Actionneurs

01-10-2021

SL-DRT-21-0849

adrien.morel@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

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Study of the persistence in IR MCT imaging retina for earth observation from space

Département d'Optronique (LETI)

Laboratoire d'Imagerie IR

01-10-2021

SL-DRT-21-0855

nicolas.baier@cea.fr

Photonics, Imaging and displays (.pdf)

IR detection is a major stake for ongoing and future space science missions studying the atmosphere chemistry (for instance MicroCarb mission dealing with the measurement atmosphere CO2 concentration) and more generally for science imaging and sensing (for instance the ARIEL mission aiming at studying exoplanet atmospheres). IR detector is a major performance driver for such instruments. The most widely used technology relies on a sensitive layer made of HgCdTe, a narrow gap semiconductor, suitable for IR photon absorption. This sensitive layer is then hybridized onto a silicon read out integrated circuit (ROIC) for multiplexing and signal conditioning. This particular technology has been developed at CEA LETI then transferred to Lynred for qualification and production. The very high level of measurement precision of science missions requires an in depth study of all sources of detection performance degradation. Among various biases is the persistence phenomena: like the human eye looking at the sun, ghosts of previous images are sometime polluting detected images, thus degrading the instrument performance. This effect is most of the time attributed to the sensitive layer (often associated to charge trapping-detrapping phenomenon) and is difficult to calibrate. Ideally, we look for a way to suppress or at least minimize this effect, playing with fabrication parameters. This requires an important work to improve our understanding of the physical phenomenon involved in persistence. Within previous developments with CNES, LETI has built a measurement bench suitable for such fine characterisations. This work intend to study this effect on identification detectors, with regard to different detector fabrication variations. A second step will be to identify the most efficient technological solutions in collaboration with Lynred Company producing such detectors. Last but not the least the validation of the proposed solution shall be performed.

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Influence of the battery electrode manufacturing process on electrode characteristics and electrochemical performance

Département de l'Electricité et de l'Hydrogène pour les Transports (LITEN)

Laboratoire Prototypage et Procédés Composants

01-10-2021

SL-DRT-21-0856

benoit.chavillon@cea.fr

Electrochemical energy storage incl. batteries for energy transition (.pdf)

For several years now, the processes for manufacturing battery electrodes have been unchanging. Indeed the electrodes are manufactured by coating on collector. The coated electrodes are then calendered to obtain the desired electrode porosity. Thus, well mastered formulations exist and can be adapted to many active materials. Once calendered and assembled into batteries, the electrodes allow to obtain cells that can be tested in laboratory. Despite this, the emergence of new materials sometimes induces difficulties in obtaining homogeneous electrodes. Thus, the aim of the thesis is to make a complete study of the influence of each component and of the manufacturing / post-manufacturing parameters on the electrode properties. This study is carried out with the aim of being able to find laws of behaviour and influence of materials. This will lead to the possibility to adapt preliminary of the manipulation to each of the components introduced in the electrode without going through a parametric study. Then, during the PhD, we will then be able to use this new knowledge to develop specific formulations for the new desired cell properties such as fast charging. All the means available at CEA and partners concerning batteries/rheology will be used such as dispersion mixer, planetary mixer for inks, different means of electrode coating and calendering, possibility to extend the study to electrode extrusion, simple rheology and capillary rheometer, cycling benches and potentiostats, DRX, SEM, Raman, MET, porosimeter, specific surface measurement, ... Funding for this topic is still in discussion and not confirmed.

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HIGH PERFORMANCES ELECTROLYTES BY ALD FOR IONIC COMPONENTS

Département des Plateformes Technologiques (LETI)

Laboratoire

01-09-2021

SL-DRT-21-0857

messaoud.bedjaoui@cea.fr

Emerging materials and processes for nanotechnologies and microelectronics (.pdf)

This work aims to explore the feasibility of new ionic layers extremely thin obtained by ALD technique (Atomic Layer Deposition). These inorganic solid state layers are major candidates as high performance dielectric for main applications like high density capacitances or synaptic transistors for neuromorphic computing. The preliminary effort will be focused on the intrinsic characterization of ALD-based layers (thickness<20nm) using 2D short loops in order to identify attractive ones in terms of ionic conductivity and electric conductivity in comparison to solid electrolyte reference LiPON obtained by standard deposition technique. One of the challenges consists to adapt these ALD-based layers with 3D structures (high aspect ratio >200). The other challenge aims to reduce the ALD-based ionic layer thickness less than 5nm while still maintaining the advanced electric properties. This work covers multiple aspects including the ALD process, the ALD precursors, intrinsic layer development and technological integration on 3D components. Particular focus will be devoted to the physical-chemical, morphological and electrochemical characterizations of these layers.

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Integrated circuits to enhance the performance of resistive-based memories

Département Composants Silicium (LETI)

Laboratoire de Composants Mémoires

01-09-2021

SL-DRT-21-0859

gabriel.molas@cea.fr

New computing paradigms, circuits and technologies, incl. quantum (.pdf)

The Phd objective is to explore fine and dynamic tuning circuit techniques, integrated nearby memory cells, to enhance the performance of RRAM.

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High frequency inductive coupling wireless power transfer based on GaN

Département Systèmes (LETI)

Laboratoire Autonomie et Intégration des Capteurs

01-10-2021

SL-DRT-21-0862

nicolas.garraud@cea.fr

Energy efficiency for smart buildings, electrical mobility and industrial processes (.pdf)

Wireless power transmission (WPT) technologies are booming with applications in the aerospace, consumer electronics, medical, automotive and defense sectors. The purpose of these technologies is to transmit electrical energy between two elements without using a physical medium with the maximum possible efficiency. Power transmission technology using resonant inductive coupling seems to be the most promising in terms of near-field efficiency. This thesis is part of the development of the thematic on wireless power transmission and power at CEA-LETI in Grenoble. In this context, the objective of the thesis is to study, develop and test the performances of this technology over the VHF frequency range (30-300 MHz) unexploited in the literature, by integrating GaN transistor-based electronics. The candidate will develop analytical and numerical models to optimize the electromagnetic coupler, compare the performances of existing systems in the literature, and propose, develop and test the performances of innovative GaN-based topologies. The final goal of the thesis is the analysis and understanding of the advantages and limitations of this technology compared to the lower frequencies traditionally used. A multidisciplinary profile oriented towards power physics and electronics is sought for this thesis. In addition to a solid theoretical background, the PhD student will need to possess teamwork skills and an aptitude for experimentation. The PhD student will be integrated in CEA-Leti's Systems Department, within teams of researchers with strong skills in the development and optimization of power and wireless power transmission systems.

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Multi-level specification and verification of cybersecurity properties for critical C programs

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire pour la Sûreté du Logiciel

01-09-2021

SL-DRT-21-0866

virgile.prevosto@cea.fr

Cyber security : hardware and sofware (.pdf)

This topic deals with formal specification and verification of software properties, in particular cybersecurity properties. Deductive verification tools allow their users to mathematically prove that a given software implementation is correct with respect to a set of formally specified properties. This is notably the case with the WP plug-in of the Frama-C framework for C programs and ACSL specifications. Another plug-in, MetAcsl, was recently developed in order to ease expressing and verifying High-level properties, with a focus on cybersecurity-related properties (e.g. memory isolation, confidentiality, or integrity). Notably, MetAcsl allows users to pose constraints on all read or write accesses in the program. In practice, verifying such high level properties on complex industrial software is often hindered by a low success rate of the automated theorem provers over the proof obligations generated by deductive verification tools. This is due to two main reasons. First, such software tends to use low-level operations (e.g. bitwise operators or pointer casts), which are difficult to represent in the logic world, hence rendering the proof much more complex. Second, the sheer quantity and complexity of mostly independent properties, notably invariants of complex data structures, can prevent the automated provers from succeeding. However, it is often the case that each function only has an impact on a tiny part of the properties, leaving most of them untouched. As all the properties must a priori be considered in the proof context, the latter is thus needlessly cluttered. Moreover, in a certain number of cases, proving the preservation of the impacted property could be done much more easily at a more abstract level. In addition, higher-level properties are usually also more easily understandable, thereby easing the task of the validation team. Similarly, an abstract executable model can be animated and evaluated more easily than the real code. The aim of this PhD is to propose a multi-level specification and verification framework for C programs. This will include verifying a part of the properties on an abstract version of the software under analysis. The abstract version will take the form of a simpler C code (abstracting away parts of the concrete system), encoding for instance a transition system, while staying sufficiently representative to let users state their properties of interest. As is the case in existing refinement-based techniques (in particular the B method), the links between the abstract system and the real code will need to be rigorously established in order to ensure the correctness of the whole development. Hence the verification of the real code will be made easier, since it will be sufficient to show that it respects the refinement properties to be able to deduce that the high-level properties stated on the abstract system also hold for the real code. Specification and verification of the refinement properties can take advantage of the work done in the MetAcsl plug-in. For instance, MetAcsl already offers some functionalities for proving more easily that if a function does not modify the footprint of a property (i.e. the locations that are read by the property), then the property is preserved by the function. The first part of the PhD will be dedicated to the definition of a methodology for specifying an abstract representation of a concrete software implementation. In particular, a way to define the links between data structures and function of both systems, as well as their properties, will be defined. In addition, refinement properties assuring that if a property is proved on the abstract system, then its concrete counterpart holds as well will be formally stated, too. The proposed technique must be able to be deployed on complex industrial software (using optimized data structures, with low-level operations and many invariants that need to be preserved), in order to verify cyber-security properties. To ensure that, a bottom-up approach can be followed, starting from an existing concrete implementation and actual properties that need to be proved on this implementation. For instance one might want to prove on an abstract level that a resource handling mechanism (memory allocator, task manager in a micro kernel, ...) respects a given access policy. Again, MetAcsl could be used for proving the refinement properties towards the real code. A second step in the PhD will be dedicated to develop a tool for automating the abstractions and refinements. Again, the tool will be evaluated on concrete case studies, either open-source or done in the context of industrial projects.

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