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

PhD : selection by topics

Engineering science >> Metrology
69 proposition(s).

A quantum algorithm to compute classical Worst-Case Execution Time (WCET)

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Calcul Embarqué

01-10-2018

SL-DRT-18-0365

sergiu.carpov@cea.fr

Worst Case Execution Time (WCET) are important data elements to feed any safety and schedulability analysis of safety critical real-time systems for which any default can jeopardize the life of the system or even threaten the life of human beings. WCET is particularly important in the context of real-time autonomous systems (e.g. robotics, self-driving cars). The problem of computing safe upper bonds of execution time is well known, but the challenge is also to have them tight to avoid over-engineering of real-time systems and mastering their costs. But this challenge is still not fully reached and moreover tends to pursue a moving target as the hardware and software architecture of real-time systems also moves forward (pipelines, cache memories, multi-cores, etc.). The goal of this PhD Thesis is to explore what quantum computing can do to simplify the problem, bring for more precision and capacity of analysis of these issues. This work will be supported by existing state of the art, and could explore a bit further than the strict domain of usual WCET analysis. Depending on the candidate profile, the subject will bend more towards either implementation aspects - How to best implement a WCET algorithm onto an available quantum simulator (eg. QX simulator, Quantum Learning Machine), or computational complexity theory aspects.

Development of innovative piezoelectric micromachined ultrasound transducer (pMUT) for automotive applications

Département Composants Silicium (LETI)

Laboratoire Composants Micro-Capteurs

01-09-2018

SL-DRT-18-0471

bruno.fain@cea.fr

The potential use of piezoelectric micromachined ultrasound transducers (pMUT) within smartphones, tablets and connected devices have raised a growing interest during the last years to build new fingerprint sensors and achieve better, low-power range-finder. To meet the specific needs of these new applications, the performances of pMUT have to be increased. This Ph.D. thesis aims at building new devices to cope with the requirements of automobile applications. The conception, the fabrication and the characterization of the pMUT will be investigated by the Ph.D student. The conception will be based on both analytical approaches and finite elements modelling (ANSYS, Comsol Multiphysics). The fabrication process will be achieved within the 8 inches MEMS Platform of CEA-LETI with the strong support of the CEA teams. The characterization, mostly probe measurements at the wafer level, will confirm and refine the models. The relevance of the devices for the targeted applications will be evaluated. For this purpose, the Ph.D. student is expected to have strong background in mechanics. He will tackle both scientific and technological challenges. He should be an autonomous team player.

Analog to Digital Converter for Neural Network based Acoustic Detection System for IoT Systems

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Architectures Intégrées Radiofréquences

01-09-2018

SL-DRT-18-0494

dominique.morche@cea.fr

The purpose of this PhD is to develop a new analog to digital converter whose output will be some trains of spike. This waveform is particularly adapted to the neural network processing. A joint optimization between the ADC and the neural network will be done by the PhD. Signal Detection and Classification is becoming a key function in the internet of things to extract useful information from the environment. For such functionality, neural network based processing is becoming more and more interesting. However, the power efficiency is often limited by the analog to digital interface which is mandatory. Therefore, more power efficient analog to digital interface are required and their power consumption should adapt itself to the application requirements. That is the reason why, the purpose of this PhD is to develop a new analog to digital converter whose output will be some trains of spike. This waveform is particularly adapted to the neural network processing. A joint optimization between the ADC and the neural network will be done by the PhD, in collaboration with a Post-Doc who will be working on the digital part. The design will exploit the 28nm FD-SOI technology developed by STMicroelectronics. Several circuit will be design, fabricated and tested. The objective at the end is to build a demonstrator able to distinguish audio signals. Industrials use cases will be considered. The Phd will be done in collaboration with IMT Atlantique. The PhD will be asked to present his work in the scope of collaborative European project.

Adaptive CMOS Image Sensor for vision systems

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Circuits Intégrés, Intelligents pour l'Image

01-01-2018

SL-DRT-18-0507

gilles.sicard@cea.fr

The aim of this thesis is to explore new kind of smart vision sensor architectures using for enhance the sensor reactivity and for simplify the image processing. The studied vision system will use new 3D microelectronic technologies from CEA-leti to perform both an image acquisition and a real time local adaptation to optimize the pixel setup to its using environment. The PhD student will benefit during his 3-years thesis of the expertise and the scientific excellence of the CEA leti to attend objectives with a high level of innovation through international patents and publications. These technologies are capable to stack several integrated circuits. The main advantage is to propose a high density of interconnections between them, allowing connection at the pixel level. The aim of the adaptive system is to control the pixel (or group of pixels) setup to optimize its functioning and regularize the output image. The dynamic and autonomous candidate, will have a microelectronic master degree, specialized in analog integrated circuit design. A good knowledge of circuit design CAD tools will be important (Cadence, and also Matlab) and good knowledge in image processing will be appreciated. This thesis will start with the state of the art study, then the PhD student will define the optimal architecture. Finally, a test chip will be designed and tested. It will demonstrate the scientific and industrial potentialities of the proposed solutions.

Département d'Optronique (LETI)

Laboratoire d'integration technologique pour la photonique

01-10-2018

SL-DRT-18-0517

francois.boulard@cea.fr

Adaptive Compress sensing radiofrequency solution for feature extraction and direct classification of RADAR signal

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Architectures Intégrées Radiofréquences

01-01-2018

SL-DRT-18-0520

michael.pelissier@cea.fr

This PhD subject aims to develop and line up a radiofrequency solution relying on compress sensing acquisition tailored to feature extraction and direct classification of RADAR signal. Most relevant signals can be compressed: our smartphones are filled of photos taken with multi-million pixels-camera, which, after compression occupy only a few thousand bytes. We can wonder what are the benefits to acquire a huge volume of information if only a small part of it is really relevant? The sparse sampling and the compressive sensing (CS) acquisition suggest to answer the question by extracting the relevant information directly at the acquisition front end level. The problem is fully transferable to radiofrequency receiver at the core of our mobile equipment used daily (Wifi, bluetooth, 3G, 4G ?). Thus the paradigm is switching from "analog to digital converter" to "analog to information converter" or "analog to feature converter" to the extent that we seek to convert the relevant information or signal features rather than the raw signal itself. CS methods find possible application in RADAR system whose demand is pushing up by the development of autonomous system. Within this context, the objective consist in extracting the environment signature for radio-identification application for instance or health monitoring. This PhD subject aims to develop and line up a radiofrequency solution relying on compress sensing acquisition tailored to feature extraction and direct classification of RADAR signal.

integrated electronic interface for optomecanical sensors

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

01-09-2018

SL-DRT-18-0534

gerard.billiot@cea.fr

The aim of this thesis to contribute to development of a new generation of sensors by study the electronic interfaces that allow the correct use of those sensors. The work will consist to study the system architecture, its integration on silicon and its characterization after fabrication and in a first application example. Within LETI, a new generation of sensors is under study: the optomechanical sensors. Their high levels of performances in terms of sensitivity, of stimulation modes as well parallel actuations of several sensors seems very promising. These results allow a broad range of potential usages for chemical sensors, physical sensors, mass sensors, ? However, development of the use of such sensors need the realization of an electronic adapted to such sensors that outperform the setup actually used to characterize these sensors. So, it is needed to understand those sensors, to do a behavioral model for them, to develop one or more architecture that can be integrated on silicon technologies to excite and sense simultaneously several sensors in an efficient way and getting the best of their performances. The phd candidate needs to have good knowledge of electronic in analog and digital fields. A good understanding of signal processing and in technologies used for sensors will be positive points. This phd work will last 3 years and will be done in LGECA lab in CEA-LETI, which has one of its main activities in the field of integrated circuit design of sensors. The operational work will be split in 5 main parts: bibliography (10%), architecture studies and modeling (20%), electronic design (30%), measurements and validation (20%) and publications (20%).

Development of an analytical tool for ovulation detection dedicated to the improvment of the reproduction process in cattle breeding

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Chimie des Matériaux et des Interfaces

01-02-2018

SL-DRT-18-0558

pascal.mailley@cea.fr

This thesis is embedded within a larger aim collaborative project, SmartRepro (CEA-INRA) aiming at developing an automatic estrus detection tool that clearly differs from existing methods. The idea here is to get closer to the reference method of ovulation detection used in experimentation, namely the dosage of reproductive hormones. The originality of the project is to develop an on-board device containing a biological fluid sampling system capable of realizing these assays in real time and generating an alert to the farmer a few hours before the occurrence of ovulation. The aim of the thesis focuses on the development of the subcutaneous sampling tool residing in a network of hollow microneedles connected to a microfluidic device activated by a fluid pump. The implantation of the network is considered for the duration of an ovarian cycle and therefore should remain effective over a period close to 1 month. For this, solutions to avoid all inflammatory phenomena, likely to lead to the encapsulation of microneedles, and biofouling will be developed in order to conduct animal testing. As a preamble to this technical development, the PhD student will participate in experiments with INRA partner to determine the area of application of the sensor. This thesis aims to prove the concept of microneedles for the collection of interstitial fluids on an ovarian cycle over a five stage development from microneedle design to animal testing. We are searching for a PD student having an engineering formation in physics and a good background in microfluidics. A complementary formation in biomedical engineering will be greatly appreciated. The candidate have to be capable to work in a multidisciplinary fields (microfluidic, medical devices, animal experimentation, biomaterials)

Architectures, caracterisations and simulation of organic and hybride PV devices for indoor applications

Département des Technologies Solaires (LITEN)

Laboratoire Modules Photovoltaïques Organiques

01-10-2018

SL-DRT-18-0582

noella.lemaitre@cea.fr

The organic solar cells are at the dawn of their industrialization and the hybrid Perovskite cells are already presented as the 3rd generation cells. The advantages of the technology such as lightness, conformability, the possibility to choose and adapt the design and the good module ratio at low illumination make OPV and hybrid modules good candidates for indoor applications, field in full expansion thanks to the Internet of Things (IoT). This thesis will be dedicated to the realization, understanding and optimization of powerful and stable devices under low illumination for indoor applications. The characterization of the devices by the LED-VIM (Variable Illumination Measurements) method should in particular allow to model their electrical behavior and thus to understand the influent parameters for the "low light". This PhD work will be conducted in close collaboration between the LMPO of CEA in INES for the realization and characterization of the organic and hybrid PV solar cells and the LEPMI of Savoie Mont Blanc University for the modelisation part.

Power Management of Embedded Spike Imager in 3D-IC Technology

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

01-09-2018

SL-DRT-18-0603

gilles.sicard@cea.fr

The PhD objective is to study the power management of a spike imager embedded a neuromorphic signal processing on chip to allow an autonomous operation under safe thermal dissipation. The goal is to define the right power management architecture from energy scavenging to power delivery through a 3D heterogeneous technology stacking to management the restricted energy in the system. The power tree where power supply integration and power network are the key elements has to be defined especially to supply duty cycled and granular spike pixel matrix. The energy management of the signal processing based on convolutional neural network and the associated memories are also key issues to minimize the energy dissipated per logic operation. The technology stacking will be discussed to define the best granular power management strategy and to evaluate the power interconnection needs. Integrated circuit design will be done on some power blocks to verify the system-level energy-focused modeling.

Embedding of high temperature resistant Fiber Bragg Gratings into metal structures obtained by additive manufacturing processes

DM2I (LIST)

Laboratoire Capteurs et Architectures Electroniques

01-10-2018

SL-DRT-18-0611

guillaume.laffont@cea.fr

LCAE laboratory from the Technological Research Division at CEA List, in partnership with the LISL laboratory from the CEA DEN, specialized in metal additive layer manufacturing processes, proposes a PhD thesis aiming at developing methods to integrate optical fiber sensors (OFS) based on high temperature resistant Fiber Bragg Gratings (FBGs) in metallic components obtained thanks to metal additive layer manufacturing processes either for the aerospace or for the nuclear industry. Thanks to recent developments, ultra-stable FBGs have been realized using direct writing processes into silica optical fibers with femtosecond lasers. These temperature and strain transducers combined with special optical fibers designed for very high temperature environments will be considered for the instrumentation of components obtained by metal additive layer manufacturing. This project aims at contributing to the adoption of in situ monitoring of 3D-printed metallic components, paving the way for their Structural Health Monitoring (SHM) to anticipate failures in the fabrication process and to optimize operating costs thanks to the development of predictive and conditional maintenance-based procedures.

Air pollution control by means of a water layer

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Biologie et Architecture Microfluidiques

01-10-2018

SL-DRT-18-0616

jean-maxime.roux@cea.fr

Air pollution, especially urban air pollution, is a public health problem leading in France to nearly 50 000 deaths per year. The PhD subject deals with the design of a new urban clean-up system based on wet electrostatic precipitation. Air purifiers based on this principle are usually intended for an industrial use. The PhD will focus on a multiphysical numerical simulation of such a device, but adapted to an urban deployment, starting with the central and difficult problem posed by the stability of an air/water interface in an intense electric field. While being based on this simulation, the final challenge is to develop a numerical optimization of the system aiming at a significant reduction of its size and an appropriate integration of the toxic gas / airborne particles sensors developed at CEA GRENOBLE/Leti/DTBS. Experimental studies carried out at CEA will be guided by the obtained numerical results which will in return be validated.

Applying machine learning to improve Intrusion Detection Systems

DPACA (CTReg)

Autre

01-09-2018

SL-DRT-18-0617

pierre-alain.moellic@cea.fr

The proliferation and growing complexity of cyber-attacks targeting the networks of companies, institutions or industrial infrastructures is a major security issue. Today, it is essential to propose technological solutions to detect complex and usually new attacks more particularly for critical infrastructures such as Cyber Physical Systems (CPS) gathering strong operational constraints. Among the available security tools, intrusion detection systems (IDS) rapidly become indispensable solutions such as traditional firewalls or antivirus. However, the available solutions cannot completely thwart current threats mainly because of a detection paradigm that is focused on known attacks (misuse-based or signature-based IDS). The future of these systems go through the development of other approaches (anomaly-based IDS) and the use of analysis and modelling tools based on Machine Learning. A lot of academic works have been proposed in this sense, supported by the strong emulation in ?artificial intelligence?. However, proposed technologies suffer from a lack of real data enabling an efficient evaluation of the performances. In the highly critical context of CPS which we need to precisely define the architectures, the supervision processes and threat models, the PhD aims at developing innovative IDS solutions (using well-known open source platforms) using approaches based on Machine Learning and using real data (from CEA Cadarache). The proposed solutions will have to meet strong performance requirements (accuracy rate, false-positive/false-negative rates) to demonstrate the pertinence of these approaches for real infrastructures.

Hyperspectral microscopy and single-shot optical coherence tomography with a static Fourier transform imaging spectrometer

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Imagerie et Systèmes d'Acquisition

01-09-2018

SL-DRT-18-0621

jean-charles.baritaux@cea.fr

Fourier Transform Spectroscopy measures the degree of coherence of light to recover the spectrum. A Fourier Transform spectrometer is said static when the fringe pattern is recorded in a single shot with no displacement of mechanical parts. Recently this concept was extended to Hyperspectral Imaging (HSI) for Space applications using a new configuration of static interferometer positioned in front of a focal plane array. Aside from HSI, another possibility that has not yet been investigated is to use this static interferometer for Optical Coherence Tomography (OCT). This PhD project is a collaboration between the Department of Astrophysics of the University of Grenoble and CEA Leti. We propose to investigate this new OCT approach, and its coupling to HSI in a fast bimodal system that could address many applications in Diagnostic and Bioimaging. The student will work on the development of a microscope integrating this new kind of interferometer, as well as the numerical processing of the interference patterns. Applications from students with a solid background in optics and data processing are welcome. A strong interest in biophotonics, and bioimaging is expected.

Dimensioning of new X-ray multisource architectures and development of tomosynthesis reconstruction algorithm

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Détecteurs

01-09-2018

SL-DRT-18-0625

vincent.moulin@cea.fr

The imminent advent on the market of new X-ray multi-sources will allow to easily dispose of numerous additional angles of view which, via a reconstruction by tomosynthesis, will provide 3D images of the inspected objects. This modality of examination can satisfy the need of many applications for which X-ray radiography (1D projection of the object) is too restricted and tomography (3D imaging) too constraining to implement. The objective of the thesis consists, on the one hand, of imagining and simulating the first multi-sources architectures and, on the other hand, of implementing and evolving reconstruction algorithms adapted to obtain the best 3D imaging performance. The profile of the candidate for this thesis is oriented "Information processing" with however a "Physical" connotation for the understanding of phenomena of radiation-matter interaction.

Flexible piezoelectric nanosystems: design, assembly and tests of an integrated sensor matrix

Département Systèmes

Laboratoire Autonomie et Intégration des Capteurs

01-09-2018

SL-DRT-18-0626

elise.saoutieff@cea.fr

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.

Use of parsimony and machine learning for the real time simulation of realistic nondestructive testing signals

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Electro-magnétisme

01-10-2018

SL-DRT-18-0628

roberto.miorelli@cea.fr

Many sophisticated numerical solvers are nowadays available for the simulation of complex configurations in the field of non-destructive testing (NDT). This complexity can come from the piece 3D geometry, for products of additive manufacturing processes, or from its composition, for composite structures or complex heat-treated steel, for instance. Beside these aspects, which motivate many efforts of theoretical modelling and numerical implementation, other environmental factors may have a strong impact on the physical NDT signals. Among these effects, one can cite other physical effects like shifts of temperature, electromagnetic perturbations coming from neighbouring machines or more simply additional physical effects that the model does not account for. These effects translate into an uncertainty on the measurements themselves (in terms of repeatability for instance) and consequently in a mismatch between simulated signals and experiments. Such discrepancy can lead to misleading conclusions and estimations. Defining in a general way the discrepancy between theoretical models and real experiments is not an easy task. This component of the signal, which can be labelled as ?noise?, depends on so many factors and practical conditions that it cannot be easily modelled or described theoretically. The proposed PhD subject proposes an approach to address the issue of characterizing this noise component and incorporating it into the simulation process. The tools implemented will focus on NDT inspections of metallic or composite structures by means of ultrasonic or electromagnetic methods. The proposed strategy relies both on advanced concepts of statistical learning theory (supervised and unsupervised learning, dictionary learning and deep learning) and on advanced numerical simulation tools (finite element, boundary element and fast semi-analytical methods) developed at CEA LIST for the simulation of NDT. First, by comparing experimental data and simulations, statistical learning algorithms will allow to determine characteristic features describing the discrepancy between them. Then, contributions based on these descriptors will complement the theoretical signals coming from the physical model in order to get a simulation that compares to experiment with better accuracy, taking into account the particular conditions of experimental acquisitions. When coupled with metamodels, acting as real time substitute of the physical model, then real-time realistic simulators can be obtained. The expected results of this ambitious thesis work are numerous. First of all, realistic models can be obtained and adapted to case-dependent industrial conditions, provided that sufficient amount of experimental data is available. On can thus expect a better performance of online diagnostics and parameters estimations. Then, such models can be used for training purposes as they can in real time generate realistic signals corresponding to various imaginary flaws affecting the material under test. Lastly, such models will enhance the estimation of confidence levels associated to NDT techniques, as they will provide a more accurate description of the real signals variability.

Integrated circuit modification with focalized XRays Beam and FIB

Département Systèmes

Centre d'Evaluation de la Sécurité des Technologies de l'Information

01-10-2018

SL-DRT-18-0633

stephanie.anceau@cea.fr

The understanding and conception of electronic devices require tools to modify these devices after their fabrication. A device failure or a functional bug require to modify the component behavior in order to find the corresponding problem. This modification of the integrated circuit is classically done with a Focused Ion Beam (FIB). This equipment permits to etch materials and deposit conductive or insulator materials, which allows to modify the interconnections of the integrated circuit. This operation is called circuit edit because the device can be reconfigured after his conception. Previous experimentations on ESRF focalized beam line in Grenoble allowed to demonstrate that a focalized XRays perturbation changes the state of a single NMOS transistor and a single memory cell of SRAM-EEPROM and Flash memories block in a semi-permanent manner in the electronic device. This proof of concept has been realized on a new CMOS technology device (45 nm). The 50 nm focalization allows to modify one single NMOS transistor. The most aggressive technologies (<20nm) can be addressed with this technique even with a 50nm focalization diameter. Contrary to the FIB the interconnections of the device are not modified: the state of one (or several if necessary) transistor(s) is modified. This modification is semi-permanent because it is reversible with a simple heating treatment. This new circuit edit technique is very promising. The aim of this PhD is to explore and develop this new technique of integrated circuit modification by using an XRays focalized beam at ESRF. Among the different key points to study, there are: -Precise localization of the transistor to attack with the help of fluorescence scan and GDS layout of the circuit -Modification of single PMOS transistors -Adaptation of the technique to more aggressive technology -Possibility to work without preparation of the package device. The exploration of the perturbation possibilities with laboratory XRays beam (without synchrotron) will be studied with the help of lead and tungsten protection made thanks to the FIB. During the PhD the candidate will have access to beam line shift at ESRF.

Mesoscopic scale simulation of the Barkhausen effect for the characterization of steels

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Simulation et Modélisation en Electro-magnétisme

01-09-2018

SL-DRT-18-0642

anastasios.skarlatos@cea.fr

Barkhausen noise is more and more used as a measure of the health state of magnetic materials. It is indeed strongly correlated to materials microstructure, stress level and chemical composition for instance. In spite of its great practical interest, this measure is often hard to interpret due to the large number of underlying physical phenomena. The development of efficient and accurate modelling tools is thus necessary to enhance the understanding of measurement and access to more quantitative estimations of characteristic quantities, such as the level of stress or a rate of chemical component. From the modelling point of view, the problem to solve is complex due to its multi-scale nature. Existing approaches can be divided in two families: those based on Monte Carlo methods to get a very fine description at the spin level, and those labelled as mesoscopic ones, aiming at solving a magnetostatic problem at the scale of the magnetic domains. In these latter approaches, Maxwell equations are solved considering a simplified configuration of domains in terms of geometry and displacements of domain walls. This PhD subject consists in implementing an optimized simulation tool for the characterization of steels, based on a mesoscopic approach. This tool will exploit empirical considerations on the distribution and dynamic behavior of domain walls in view of deriving macroscopic signals measured in practice and studying the statistics of characteristic parameters involved. Magnetostatic simulations will be carried out with a 3D numerical solver based on Finite Integration Technique (FIT) developed at CEA LIST. The representativeness of the unitary calculation will be the key to the validity of the statistical procedure leading to macroscopic signals. Theoretical results will be compared to experimental data obtained in laboratory controlled conditions by partners of laboratoire Roberval (Université de Technologie de Compiègne, UTC), involved in the PhD work.

Thermal modelling of sugar alcohol cristallisation for energy storage systems based on phase change material

Département Thermique Biomasse et Hydrogène (LITEN)

Laboratoire Stockage Thermique

01-09-2018

SL-DRT-18-0650

fabrice.bentivoglio@cea.fr

Heat represents 50% of the finale energy consumption in the France energetic mix. It has been identified, in the framework of a general orientation law in 2015 (Loi TECV), as a major source of CO2 emission reduction in particular through the development of urban heating networks that allow massive integration of renewable energy such as biomass, solar or waste incineration. In order to adapt the fluctuant consumption of a urban heating network to renewable energy with low flexibility, next generation urban heating network will combined smart meters for precise diagnostic, smart management systems for a better decision process and a key technological component to shift production and match with consumption: heat storage. Phase Change Material (PCM) heat storage, that allows higher storage density (kWh.m3) than classical hot water tanks, has been identified as a promising concept in particular for heating network sub-station, located inside residential buildings then requiring low volume storage. Current studies on PCM storage for urban heating networks mainly consider paraffin, fatty acids and fatty alcohols as PCM. These PCM families can reach a storage density 50% higher than water. Using Sugar alcohol family (or polyols), a storage density 2 or 3 times higher than water can be reached. In addition sugar alcohol are cheap, safe (even edible) and non-corrosive. These ?ideal? PCM only show one major drawback: a very low nucleation rate and and a very low crystallisation speed that make them unusable in a storage system without adding specific system to help crystallisation. The Laboratoire de Stockage Thermique (LITEN ? CEA Grenoble) develops PCM storage systems for urban heating application, using sugar alcohol and based on tube and shell heat exchangers technology. The specific system used to force crystallisation is based on bubbling that generate mechanical shear stress. The principle has been successfully tested at laboratory scale (500g), around a single finned tube (1kg) and finally in a pre-industrial scale prototype (400kg). The results obtained are very promising. However, complex phenomenon have been brought out, such as a high crystallization delay or a strong coupling between thermal and statistical aspects. The objective of this PhD is, based on new experimental results that will be obtained in the facilities yet available in the laboratory, to propose a model of the heat released by a sugar alcohol in a tube and shell PCM heat storage using bubbling to activate the crystallisation. The model will be based on CFD and 2D models that have yet been developed in the laboratory by previous PhD student but for classical PCM (PCM with high crystallization rate and crystallisation speed such as paraffin). These models are based on enthalpy-porosity Voller formulation. The PhD work will starts with a bibliographic study on the crystallization of sugar alcohol and about the effect of bubbling on this crystallisation, in order to develop a model coupling thermal and kinetic aspect. Then the model will be implemented in a 2D or a CFD code and validated against experimental measurements, first at laboratory scale and then at the scale of a pre-industrial prototype.

Understanding the aging phenomena of an innovative photovoltaic module for a specific application, and setting up

Département des Technologies Solaires (LITEN)

Laboratoire Modules Photovoltaïques Silicium

01-09-2018

SL-DRT-18-0652

benoit.braisaz@cea.fr

The main failures observed on photovoltaic modules (PV modules) are associated with the reliability and durability of both interconnect and encapsulation processes, and materials. The main failures are: delamination, yellowing, corrosion, cell cracking and breakage of interconnections. The improvement of PV module lifetime belongs to the development of the next PV module generation. The analysis of module failures requires the implementation of relevant accelerated aging tests intended to study the behavior over time, and advanced characterization Tools for physicochemical understanding of degradations. In the case of innovative modules that can be used as structural materials (eg solar road), the modules undergo combined climatic constraints: mechanical pressures, temperature variations, current variations, low temperature (<-5 ° C) and high (> 60 ° C), freezing, humidity, standing water (dew) and runoff (rain), illumination (solar and UV), salt (salting of roads), and intermittent shading. The understanding of the physicochemical mechanisms at the origin of the observed degradations will make it possible to identify the phenomena involved and on the other hand, to reproduce them during accelerated tests under controlled conditions in order to evaluate the most durable solutions. For this purpose the LEPMI and DURASOL material characterization platforms will be solicited.

Recycling of polymer composites by means of a supercritical fluid

Département Thermique Biomasse et Hydrogène (LITEN)

Laboratoire de ThermoConversion de la Bioressource

01-10-2018

SL-DRT-18-0660

anne.roubaud@cea.fr

The subject of this PhD is to study and develop a supercritical fluid process for the recycling of carbon reinforced plastic composite, both resins and fibers. Use of composite materials is increasing in a wide range of applications : industrials, sporting, automotive, aeronautical, marine?but the lack of recycling for those non biodegradable materials is an environmental burden. Since 20 years several treatments have been developed for composites wastes, mechanical, thermal processes like pyrolysis and thermochemical like solvolysis. This process is able to breakdown the composite polymer matrix and hence allow the recovery of the fibers. Supercritical fluids are used due to their high diffusivity in porous materials combined to their chemical reactivity. The objective of this work is to define the necessary process conditions for deconstruction of composite resins of carbon fibers reinforced plastic composites. The aim is to recycle the fibers and also to allow a further chemical valorization of resins decomposition products. This work include a detailed analysis of the organic molecules produced and the development of a chemical mechanism for this depolymerisation. Mechanical properties of fibers after treatment will be determined to validate the recycling interest. This work will provide finally a first technico-economical evaluation of the proposed process.

Optimal Battery Management Algorithms for Switched Cell Architecture Systems

Département Systèmes

Laboratoire Electronique Energie et Puissance

01-10-2018

SL-DRT-18-0663

vincent.heiries@cea.fr

Although having benefited from major advances in recent years, batteries still suffer from certain limitations, notably in terms of energy density, lifetime and sometimes safety. In this context, the patented switch-cell battery architecture proposed and developed in the L2EP laboratory represents a major innovation in this field and allows us to go beyond some of these limitations. Today, batteries are essentially composed of a series of cells through which the same current is flowing. These systems are thus limited by the weakest cell in series. One of the advantages of the switched cell architecture is that each cell can be exploited in a differentiated way and thus get the most out of each cell. A first objective of the thesis is precisely to propose an algorithm allowing to exploit at best the energy of all the cells of the battery in order to increase the autonomy of the system while maximizing its lifetime. A second objective of this thesis is the development of innovative estimation algorithms for SoX indicators (SoC: State of Charge; SoH: State of Health, SoE: State of Energy) of accumulators based on an optimal use of the new capabilities offered by the switched cell architecture. Indeed, this architecture brings new functionalities that open the door to the implementation of new algorithms within the Battery Management System. In particular, cell capacity estimation could be greatly improved by on-line correction of the estimator. This procedure can be made possible by a controlled load-discharge profile of individual cells.

Accurate and robust estimation of the PEMFC ageing state Bayesian observers using a model-based approach

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

Laboratoire Electronique avancée, Energie et Puissance

01-10-2018

SL-DRT-18-0665

vincent.heiries@cea.fr

PHM (Prognostics and Health Management) represents a real opportunity to improve fuel cell performance and extend the life of fuel cells. This field of study has recently gained much interest. The main goal is to make optimum use of the data measured by all available sensors in order to evaluate the specific indicators of PEMFC ageing and possibly modify the operation of the fuel cell in order to optimize its lifetime. The proposed PhD is part of a model-based approach and will be based on the expertise in fuel cell modelling developed at the Modelling Laboratory. An on-line estimator of the ageing state of the fuel cell will be developed. The proposed observer presents the characteristic of combining a state model derived from the MEPHYSTO fuel cell model with the different data sensors available (voltage, current, pressure, temperature). The envisaged method makes it possible to jointly estimate the state variables, and in particular the ageing state, as well as to update the model parameters. Given the nature of the state variables to be estimated, we will move towards sophisticated observers adapted to non-linear and non-Gaussian problems in order to obtain a solution approaching the optimal Bayesian estimate.

Definition and validation of an innovative powder metallurgy process for high performance materials

Département Thermique Biomasse et Hydrogène (LITEN)

Laboratoire Conception et Assemblages

01-10-2018

SL-DRT-18-0682

emmanuel.rigal@cea.fr

This PhD project deals with the study, modeling and simulation of a key stage of Hot Isostatic Pressing, a fabrication process that involves the densification of gas atomised metallic powders. This stage, namely outgassing, allows to decrease the oxygen content of the material. As a result its mechanical properties improve and reach, or even exceed, those of the equivalent forged material. Yet, the process has other advantages: it is material efficient, it provides homogeneous and isotropic materials with a good ability to non destructive evaluation. So, a control of the outgassing step will contribute to a better acceptance of the process in industries which use components manufactured according to rules and standards, such like nuclear components or pressure vessels. The main items of the project will be: a study of the initial powder (made of a X2CrNiMo17-12-2(N2) steel), a study of its outgassing behavior using thermogravimetric analysis coupled with mass spectrometry and thermodynamics modelling, the definition of a model describing the gaseous flow in the porous material under anisotherm conditions and taking into account the gas sources and sinks, an experimental validation and a study of the properties of the achieved materials. The study will be hosted by a laboratory of CEA Liten which is well recognized in the field of HIP since many years. It will benefit from recent studies on this topic as well as from a favorable environment in terms of characterisation means.

Bipolar lead-acid batteries with laminated current collectors

Département des Technologies Solaires (LITEN)

Laboratoire Stockage Electrique

01-10-2018

SL-DRT-18-0684

nicolas.guillet@cea.fr

New batteries with bipolar architecture: The thesis project aims the development of high-power / high-energy density / long-life / low cost lead acid batteries with bipolar architecture of the battery module innovative current collector materials and 3D printed components. The bipolar construction of the battery allows enhanced operation at high rates of charge and discharge typical for the energy storage systems used in some smart-grid and hybrid electric vehicle applications. One part of the thesis is focused on the optimisation of thin laminated composite structures composed of titanium and lead foils and their encapsulation in 3D printed plastic structures intended to use as bipolar current collectors. The latter will be used to develop and test lab-scale bipolar lead-acid batteries with optimized compositions and ratios of the positive and the negative active materials. The prototype batteries will be studied at different stages of their ageing using a variety of methods for physical, physico-chemical and electrochemical characterisation in order to estimate the potential failure mores and how to avoid them.

Phase-Change Memory for high density Storage Class Memory applications

Département Composants Silicium (LETI)

Laboratoire de Composants Mémoires

01-10-2018

SL-DRT-18-0691

gabriele.navarro@cea.fr

Nowadays, the need of a data storage infrastructure allowing Big Data processing requires memory devices with improved performance. The objective of this PhD is the development of innovative Phase-Change Memory (PCM) devices to target Storage Class Memory applications (SCM) that require higher programming speed and endurance. To achieve this goal, the phase change material engineering becomes fundamental, in particular exploring new alloys capable of higher crystallization speed and higher stability. The candidate will contribute to the following tasks: development and electrical characterization of PCMs based on innovative materials, also co integrated with new BackEnd selectors developed in LETI, from single device analysis to full matrix statistics; physico-chemical characterization of the different alloys by resistivity measurements, XRD, FTIR, TEM etc.; multi-physical simulations to correlate the device performances with the material properties. In addition, the student will contribute to industrial projects, and will interact with experts at the international level in the field of the phase change materials.

New wake up radio for an energy efficient integration of interacting IoTs in Cyber-Physical Systems

Département Systèmes

Laboratoire Communication des Objets Intelligents

01-09-2018

SL-DRT-18-0693

mickael.maman@cea.fr

With the massive deployment of sensor network applications, long lifetime networks are mandatory and very challenging. To optimize the network lifetime, it is crucial to design ultra-low power communication systems. Several technologies are competing for low power uplink communications (e.g., LoRa, Sigfox, Bluetooth LE, Thread, Zigbee, WiFi). But when interaction with IoT devices is mandatory (e.g., command in Cyber Physical System, interaction with the real environment in Augmented Reality), ultra-low power as well as predictable latency Downlink communications are missing. A lot of efforts were devoted to the design of energy efficient communication protocols, and especially MAC protocols. MACs have a critical role in the energy efficiency of communications as they control the transceiver. The aim of MAC protocols is to allow point-to-point communication between two neighboring nodes. Some technologies (e.g., LoRa, SigFox) proposes to open a window for Downlink communications after each Uplink communication in case of traffic. This approach does not work for latency constraint applications since a Downlink command could be process only after an Uplink communication. Other MAC solutions propose to periodically listen to Another approach is the use of ultra-low power wake-up receivers (WRX) which can significantly reduce the overall power consumption of the system. In this approach, the device can continuously listen to a wake up signal in the channel. The drawbacks of these solutions are their low maturity (proof of concept) and their very low sensitivity. During this PhD, we propose a cross-layer approach (RF/PHY/MAC). Our goal is to make a tradeoff between the energy consumption, the latency and the performance (e.g., range of communication).

Spectral unmixing and classification in X-ray hyperspectral imaging

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Détecteurs

01-10-2018

SL-DRT-18-0731

caroline.paulus@cea.fr

As part of its X-ray (RX) imaging developments, LETI is studying the contribution of new CdTe-based hyperspectral RX detectors combined with advanced processing methods. The main applications are medical imaging, scientific instrumentation and control for security. The laboratory works in particular on X-ray detection systems of illicit substances such as explosive materials in air transport. Current data processing methods for discriminating materials or tissues analyzed from measurements are derived from techniques used with dual energy detectors. The aim of the thesis is to design advanced unmixing and classification algorithms taking into account all the spectral information provided by the detectors to improve the performances of the systems in terms of false alarm rate and good detection rate. The challenge is to demonstrate that these detectors and their associated data processing make it possible to achieve performances specified by equipment certification authorities. The proposed methods might be inspired by spectral unmixing and classification techniques widely developed in the context of hyperspectral imaging for Earth observation. The candidate must be specialized in signal processing and show interest in physics and instrumentation.

Raman microspectroscopy coupled to isotopic labelling for the monitoring of antibiotic stress on single bacterial cells

Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratoire Imagerie et Systèmes d'Acquisition

01-10-2018

SL-DRT-18-0738

veronique.rebuffel@cea.fr

The antibiogram (antibiotic sensitivity test) test is in the heart of the rationalization of the antibiotic therapies. Faster novel antibiogram methods (answer in less than 2:00) will have a decisive impact in the fight against the extension of the multiresistances of pathogenic bacteria. The current methods, based on the capacity of a molecule to inhibit or not the growth of pathogens, cannot satisfy these speed requirements, because of latency time preliminary to any culture. The Raman microspectroscopy makes it possible to meet this need, with an approach authorizing the characterization of single cells. A time consuming culture, preliminary to the test itself, would not be thus necessary any more. Moreover, the sensitivity to antibiotic would be determined by evaluation of metabolism decrease, a criterion of sensitivity much earlier than growth inhibition. The objective of the thesis is to explore a new method of isotopic marking to measure, thanks to the Raman microspectroscopy, metabolism variations at the level of the single bacterium. Work will implement existing optical devices, as well as techniques of clinical microbiology. Algorithmic developments will concern both spectra and multivariate analysis, and modelling. The candidate must be titular of a diploma of engineer and/or Master degree in signal or data processing, eventually instrumentation, with knowledges in biophysics or optics. Strong interest for microbiology is required.

Wireless and powerless sensor antenna with frequency transposition

Département Systèmes

Laboratoire Antennes, Propagation, Couplage Inductif

01-09-2018

SL-DRT-18-0742

camille.jouvaud@cea.fr

The thesis takes place in the context of the development of the Internet of Things and its reliability to connect and automatically transfer data over a large network. In this context, needs for real time information are intensified. Therefore, new wireless sensor that consumed as less as possible are expected. Among existing sensors technologies, electromagnetic sensors have a strong interested in their passive side Those sensors, which are read remotely by an interrogating antenna, use the variations of electromagnetic properties of an antenna to measure a physical phenomenon. Development and optimisation of those sensors properties, of their communication abilities as well as their miniaturization constitute a major stake for their generalization in our professional or private environments. Moreover, constraints imposed by the different medium where the sensors will be implemented, and so where the data will be transferred, imply some issues in terms of detectability and reliability. This thesis proposes to contribute to the problem of the miniaturization of the sensor-antennas and their sensitivity towards the propagation channel, through the study of the properties of miniature antennas themselves as well as the methods of interrogation of these antennas.

Secure implementation of stream ciphers

Département Systèmes

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-10-2018

SL-DRT-18-0762

mathieu.desnoes@cea.fr

Recent attacks on processors (Meltdown [1] and Spectre [2]) highlight vulnerabilities of hardware circuits for consumer electronics. This applies to PC, laptop and smartphones, but also to small processors integrated in smart devices (Internet of Things). It becomes urgent to secure these processors taking into account theirs specifics contraints (hardware footprint and low power consumption). More specifically, it is required to secure intra-chip communications in order to ensure confidentiality and integrity of data exchanged between a CPU and peripheral (eg. FLASH, DMA, SRAM?.). Stream ciphers [3] are well adapted to meet the above challenge because of their lightweight implementation [4]. The security of the system is however transfered to the implementation of the stream cipher. The goal of this thesis is thus to propose lightweight implementations that are robust to side channel and fault injection attacks. The applicant will propose and implement countermeasures taking into account the constraints imposed by the IoT context: a small amount of hardware ressources, low power consumption and acceptable speed performance. [1] https://meltdownattack.com/meltdown.pdf [2] https://spectreattack.com/spectre.pdf [3] http://www.ecrypt.eu.org/stream/ [4] https://www.cryptolux.org/index.php/Lightweight_Cryptography

Spalling of thin films: study and applications

Département Composants Silicium (LETI)

Laboratoire Intégration et Transfert de Film

01-09-2018

SL-DRT-18-0770

lucie.levan-jodin@cea.fr

This Ph. D is conducted in LETI/DCOS/SCPE/LIFT, a laboratory specialized in layer-splitting and wafer bonding for microelectronic applications. A new way for layer-splitting is developed at the laboratory, the splitting under stress called ?spalling?. It is a low cost technology to split monocrystalline thin films or electronic components. This phenomena is simply based on a stress application on the surface of the substrate from which the film will be split. Recent progress shown the potential of this method, especially for photovoltaic applications but also photonic, piezzo? The Ph. D is organized in two parts. In the first one, the candidate is going to study and model the fracture from commercial substrates (Si, Ge, GaN?) combining experimental results and finite element simulation. The second part will focus on the integration of this splitting process on the transfer of functional components in collaboration with other CEA laboratories and Ph. D students.

Pattern density multiplication for Nanoimprint Lithography for large scale master manufacturing

Département Technologies Silicium (LETI)

Laboratoire

01-10-2018

SL-DRT-18-0772

hubert.teyssedre@cea.fr

NanoImprint Lithography, based on the use of a nanopatterned stamp, has been developed to 2D or advantageously 3D (discrete or analog) patterns within polymer layer. One of the essential steps of this technology is the design and manufacturing of the master designed to code the information to be printed. When the surfaces to be printed become equivalent to the size of a standard microelectronic silicon wafer (300 mm in diameter) and the dimensions of the patterns are lower than 100 nm, the manufacturing of such masters remains a real challenge to date. As part of this thesis we propose to implement an innovative solution for manufacturing this type of masters. A first trial of the solution proposed by the laboratory (not requiring expensive lithography tools) has demonstrated the feasibility of this approach. The aim of the thesis will be to optimize this new technique while focusing on identifying the limits of this approach.

Performance Improvement of silicon nano-gauges for MEMS sensors

Département Composants Silicium (LETI)

Laboratoire de Caractérisation et Fiabilité des Composants

01-10-2018

SL-DRT-18-0781

antoine.nowodzinski@cea.fr

The piezoresistivity of the silicon nano-gauges is the basis of many CEA-Léti's MEMS sensors: accelerometers, pressure sensors, gas sensors? and the performance of these sensors is directly conditioned by the performance of the nano-gauges. As part of this thesis, the student will conduct research work to optimize the performances of nano-gauges according to the main parameters related to their technological fabrication process: SOI substrates, doping level, implantation method, geometry, release step (to suspend the nano-gauges), passivation or annealing after release... In particular, the PhD student will study the low-frequency noise of nano-gauges made on SOI substrates: he will characterize various types of nano-gauges, will seek to understand the mechanisms at the origin of the low-frequency noise in nano-gauges and will make the necessary simulations to reinforce the hypotheses explaining the electrical fluctuations within the nano-gauges. The maximum mechanical stress acceptable by the nano-gauges and the linearity zone of their piezoresistivity will also be studied, and a thermal study will have to be carried out to determine the maximal current usable for the piezoresistive measurement. These studies should allow, at the end of the thesis, to propose more efficient nano-gauges, as well as their manufacturing process. The integration of this process will be studied to allow the realization of a complete sensor based on this optimized piezoresistive transduction.

Non Orthogonal Multiple Access for efficient Internet of Things Communications

Département Systèmes

Laboratoire Communication des Objets Intelligents

01-10-2018

SL-DRT-18-0786

francois.dehmas@cea.fr

Machine-to-Machine (M2M) type communication is expanding, and the potential market for low-powered wireless solutions in the Internet-of-Things (loT) is expected to grow exponentially. This increase sets major and new constraints on the communication systems according to the addressed applications (as network/spectrum access, energy efficiency, coverage, etc.). These requirements of the IoT communication system have then led to the development of different technologies as: - Short range communication system (Bluetooth and ZigBee) - Cellular technologies (2G, 3G et 4G) - Wifi and IEEE 802.15.4 WAN - Proprietary LPWA (Low Power Wide Aera) communication system: Sigfox, LORA, etc. These technologies have usually been developed for specific scenarios (low power consumption, low throughput/long range, cellular, high throughput/short range, etc.) and major evolutions, in terms of standardization, are again required. Hence, 5G and in particular the « massive machine type communication » (mMTC) will have to manage a massive access with a very high devices density. This new standard, called New Radio massive machine type communication (NR-mMTC), is planned from the 3GPP R16 (end 2018). In the IoT network the flow is expected to be sporadic, not synchronized and with a relatively small quantity of information to transmit. Hence, to keep a good efficiency, the signaling overhead has to stay limited resulting in a synchronization process that can suffer at low sensitivity. Non-Orthogonal Multiple Access (NOMA) is an essential enabling technology for the 5G wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity and high throughput. The key feature of NOMA is to serve multiple users at the same time/frequency/code, with for example different power levels, which yields a significant spectral efficiency gain over conventional orthogonal multiple access. Different approach have been considered: MUSA (Multi-User Shared Access), RSMA (Resource Spread Multiple Access), SCMA (Sparse Code Multiple Access), PDMA (Pattern Division Multiple Access), etc. These approach enable to reach a devices density around 1 million of devices/km2. However, the features of these pre-existing technologies don't enable to reach the performance defined in the IoT sceanarios. Indeed, the main goals of the thesis can be splitted in 3 items as follows: - Propose new NOMA schemes which meet the IoT constraints: Low power consumption, high density (high multi-user overload), high level of scalability of the massive IoT applications and low complexity. - Evaluate and propose new waveforms for the 5G NR-NB-IoT with the following properties: energy efficiency, good coverage, high level of flexibility, interference resilience, etc. The associated NOMA scheme will be then assessed. - Propose different synchronization mechanisms (time, frequency, channel estimation, etc.) for the NOMA, with a controlled signaling overhead and a strong constraint on the energy consumption.

Enhanced neuronal patterns decoding from sensorimotor cortex for a clinical closed loop intracranial (ECoG-based) Brain-Computer Interface application

Clinatec (LETI)

Clinatec (LETI)

01-09-2018

SL-DRT-18-0796

thomas.costecalde@cea.fr

The thesis will be carried out within the frame of the interdisciplinary project ?Brain Computer Interface? (BCI) at CEA/LETI/CLINATEC® (Grenoble, France). The BCI system is based on the measurement and processing of neuronal activity from the cerebral cortex (ElectroCorticoGram, ECoG) of subject executing motor imagery task. Clinical trial of chronical ECoG based motor BCI system is in progress affording a unique opportunity of long term ECoG based BCI clinical study. The crucial step of BCI is identification of decoding model. Adaptive algorithms were developed for easy to use and efficient BCI system. Adaptive BCI allows efficient supervised learning of neural decoder. The mission of PhD fellow will be exploring a feasibility of unsupervised / semi-supervised identification of decoding/control system for motor BCI: test the detectability of error related neuronal responses from sensorimotor cortex using implantable recording device WIMAGINE®; explore unsupervised and semi-supervised approaches for decoding model identification; develop adaptive real-time learning algorithm. Algorithms will be implemented on MATLAB/C/C++ and integrated to BCI software platform.

CIPV: Car-Integrated-PhotoVoltaics. Development of specific photovoltaic modules for vehicle integration

Département des Technologies Solaires (LITEN)

Laboratoire Modules Photovoltaïques silicium

01-10-2018

SL-DRT-18-0797

julien.gaume@cea.fr

Photovoltaic technologies increased significantly with a production largely dominated by rigid and flat crystalline silicon-based modules (over 90% market share), intended for residential applications or solar farms. In the case of specific applications, where integration and weight are predominant, thin and flexible PV modules have been developed. The market for autonomous and hybrid vehicles has significantly grown in the recent years. Despite this growth, few solutions integrating photovoltaic panels have been proposed. The Laboratory of Silicon Photovoltaic Modules of the CEA-Liten at INES has acquired a knowledge in the development of innovative photovoltaic PV modules for specific applications. This knowledge will be applied to the development of PV modules specifically dedicated to the application of autonomous or hybrid vehicles. The objectives of the thesis will be: - a state of the art establishment on the application of PV as a direct source of energy for electric cars. - Identification of technological locks and technical tracks to solve them. - Estimatation/modeling the energy production of different surfaces and the effects on the autonomy of the car, according to several scenarios. - Sizing, realization and characterization of innovative photovoltaic modules prototypes in indoor environment thanks to all the PV Modules platform. Integration into an electric demonstration vehicle. - studying PV & battery system interaction to optimize the electric charging.

Participatory localization of connected objects through deep learning techniques

Département Systèmes

Laboratoire Communication des Objets Intelligents

01-10-2018

SL-DRT-18-0806

benoit.denis@cea.fr

Conventional localization methods based on low-cost and low-complexity wireless communication standards (e.g., Long Range - IoT Lora or Sigfox systems, WiFi/BT-LE) can provide a positioning accuracy level (respectively, 500m to 1km in outdoor, 5m to 10m in indoor) that is not suitable to the needs of emerging applications, such as geo-referencing of the data produced by mobile IoT sensor nodes, or smartphone-based pedestrian navigation in public areas or office buildings. In the frame of these PhD investigations, we thus propose to rely on Artificial Intelligence on the one hand (typically, on deep learning techniques), as well as on advanced management/representation methods adapted to spatialized data on the other hand, so as to improve localization performance, while relaxing underlying technological specifications (more particularly, in terms of wireless transmission capabilities). The idea is to learn (over both space and time) and to fuse multi-parameter maps, benefitting not only from radio metrics notoriously ill-adapted to localization (e.g., received power, packet error rate...) and contributed in a participatory way by the different mobile agents on the field, but also from other available modalities depending on the application context (e.g., prior road network map/building layout, physical environmental measurements such as ambient sound, embedded inertial units, etc...).

Non Destructive Testing by Eddy Current method of metal parts obtained by Additive Manufacturing

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Instrumentation et Capteurs

01-09-2018

SL-DRT-18-0833

natalia.sergeeva-chollet@cea.fr

CEA/LIST develops methods of Non Destructive Testing (NDT) by Eddy Current (EC) methods for various industrial sectors such as aeronautics, oil and gas industry, or nuclear industry. In these industrial fields, metal additive manufacturing is booming but is often limited by the lack of a control solution of the produced parts ensuring the integrity of the parts. To make progress in this sector, an "Additive Factory Hub", located at CEA in Saclay, was created and inaugurated at the end of last year. The current methods of monitoring and control of the produced parts are based on an optical examination of the surface of the part being manufactured by a camera or to monitor the atmosphere of the manufacturing chamber. The purpose of the proposed subject is to implement a surface and sub-surface inspection by Eddy Currents of the additive manufacturing parts. The PhD student will contribute to the improvement of the control of the pieces. He or she will invest in the optimization of Eddy Current sensors and associated working frequencies, in order to increase the sensitivity to the defects to be detected, such as superficial or sub-surface melting defects and local porosities. These optimizations will be conducted by simulation based on the CIVA simulation platform developed in the department (http://www-civa.cea.fr). He or she will proceed to the experimental evaluation of these sensors. Signal processing algorithms will also be developed to minimize the impact of the roughness of the parts. To carry out these works, knowledge in electromagnetism, instrumentation and electronics is desired.

Van der Waals epitaxy of CdTe on 2D materials

Département d'Optronique (LETI)

Laboratoire des Matériaux pour la photonique

01-10-2018

SL-DRT-18-0843

philippe.ballet@cea.fr

2D materials nowadays attract a great amount of research because of their unique properties directly derived from their graphene-like electronic structure and crystalline organization. These materials have strong in-plane chemical bounds while extremely weak, van der Waals type, out-of-plane interaction describing them a 2D sheets of monolayer material. 2D material epitaxy on conventional 3D semiconductors may thus occur without any lattice parameter mismatch strain. The opposite is also true when depositing a 3D onto a 2D. The PhD work consists in studying in details these new epitaxial systems with the proposal of realizing the strain free epitaxial growth of photovoltaics CdTe or infrared sensitive HgCdTe on 2D layers. These materials (2D and 3D) will be grown by molecular beam epitaxy allowing for an in-situ control of the interface. The growth mode of 3D(CdTe)/2D and 2D/3D(HgCdTe) will be first independently studied with the goal of providing a full 3D(CdTe)/2D/3D(HgCdTe) heterostructure where the 3D(CdTe) will promote, through the very thin 2D, the crystalline structure and orientation for the ultimate growth of HgCdTe. Inserting a weakly bonded 2D material also offer promising new functions by enabling the HgCdTe layer to be detached and transferred onto another substrate opening the way towards new optoelectronic applications. The thesis scientific environment will be brought to a broader range by considering the availability and proximity of the nano-characterization platform (CEA-PFNC) where skilled teams and last generation of equipment are dedicated to revealing the chemical nature and crystallographic structure of the epitaxial stacks.

Scalable quantum bits in Si CMOS technology

Département Composants Silicium (LETI)

Laboratoire d'Intégration des Composants pour la Logique

01-09-2018

SL-DRT-18-0855

louis.hutin@cea.fr

The first few decades of the previous century have witnessed a revolution in the physical sciences due to the advent of quantum mechanics. Now, a hundred years later, quantum mechanics is about to drive a new revolution in technology via the exploitation of the inherent complexity of quantum systems. The elementary building block of quantum information, the qubit, can be made out of a large variety of material systems. When it comes to a crucial issue such as large-scale integration, however, the range of possible choices becomes much narrower. Among solid-state approaches, qubits based on superconducting elements have so-far reached the most advanced level of development. An alternative solid-state approach relies on semiconducting elements. Here the quantum information is encoded in a spin degree of freedom, such as the magnetic moment of an electron or that of a nucleus. Though the development of spin qubits has been lagging behind, recent experimental breakthroughs have sparked a renewed interest, exhibiting exceptionally long coherence times ranging between 1 ms and 0.5 s in isotopically purified silicon. In addition to long coherence times, silicon spin qubits have other potential advantages. The first one is size: a spin qubit with its readout device can be comfortably fitted within a square micron. The second advantage lies in the inherent compatibility with silicon technology. The exceptional control on the fabrication processes of silicon devices is definitely an asset for large-scale qubit integration. In addition, qubits may be straightforwardly coupled to CMOS-based on-chip electronics for qubit driving and readout. Owing to the above-mentioned properties, silicon spin qubits provide one of the most promising pathways to scalable quantum computers. The main objective of this thesis is the realization of scalable quantum nanocircuits at the single electron spin level in a silicon CMOS platform. The project will initially focus on distilling the elementary spin qubit device down to the simplest and most scalable design, in order to lay the foundation for future large-scale integration. We will then investigate different strategies and geometries for qubit integration.

Optimisation of energy management strategy for fuel cell hybrid véhicles by combinatorial optimization methods using multi-physics models of performance and degradation

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

Laboratoire Modélisation multi-échelle et suivi Performance

01-10-2018

SL-DRT-18-0856

ramon.naiff-dafonseca@cea.fr

The hybrid architecture requires the management of the components in order to improve some characteristics when comparing to conventional solutions. The power split strategy among the components allows to increase the performances of the system by the minimization of the energy consumption and/or increasing the durability of the system, while considering the mission requirements and technological constraints. Several methodologies has been used to develop an approach to obtain the energy management strategy with important results, but also with some limits related to the application. This PhD thesis proposition aims to deal with the indicated problems by applying a methodology able to solve a problem with different sources (battery, hydrogen fuel cells, super capacitors, etc.), different criteria (energy consumption, durability, cost, etc.) and several state dimensions (time, SOC, voltage, temperature, etc.) in an optimal way while considering a time calculation adapted to the application (sizing offline calculation, embedded implementation, etc.). The combinatory optimization methods are considered, at first sight, as valid options thanks to their capacity to solve complex and nonlinear problems that are used present in multi-sources and multi-dimensions hybrid applications. In the State of the Art, this type of methodology have shown the possibility to perform global optimization with less calculation effort and less memory allocation than the Dynamic Programming Method. Moreover, this methodology is less depend on the discretization of the problem as Dynamic Programming is. The main objective of this thesis is to develop an optimization methodology that combines the models of the system (performance models, controls and degradation) to the combinatory optimization strategy in a formal optimization problem.

Simulation and modeling of ferroelectric material based transistors for logic (NCFET) and memory applications

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-10-2018

SL-DRT-18-0859

sebastien.martinie@cea.fr

The main idea of this PhD is to initiate a new activity in the field of compact modeling (MOSFET) and memory (resistive memory RRAM). A first part will concern the study of the ferroelectric effect from a CMOS device point of view and its impact on the electrical device characteristics; A second part will deal with the physical modeling of the memory effects induced by the use of the same ferroelectric properties. This innovative work will be declined as follows: To include the ferroelectric effect in a compact modeling according to the surface potential approach of the standard models such has well-known PSP model for bulk and Leti-UTSOI for FDSOI. An experimental contribution will complement and validate the modeling work (through internal collaboration with LCTE). Set up an appropriate modeling strategy for the memory effect in order to propose a generic solution that will be implement in a SPICE environment. A final part will concern the comparative evaluations of the sensitivity to the ferroelectric effects of the upstream types of FinFET and Nanowires based devices following the development of the Leti-NSP model dedicated to stacked nanowires. The student will rely for this on the simulation TCAD.

micro-concentrator for spatial applications

Département des Technologies Solaires (LITEN)

Laboratoire Photovoltaïque à Concentration

01-09-2018

SL-DRT-18-0861

philippe.voarino@cea.fr

CPV (Concentrator PhotoVoltaics) technologies take more and more an important play in the field of existing PV solutions. Record modules reach efficiency of 36.7% with cells of 5x5mm². By miniaturizing concentrating systems, it becomes possible to reduce costs and also to increase the efficiency by using microelectronics processes developed in LEDs manufacturing. These based micro-concentrator systems can also be used for spatial missions for which the surface reduction of III-V solar cells has a direct impact on the cost and the robustness of the solar generator. LITEN has lied on micro-concentration for many years, and continue to develop this activity. Within the framework of the thesis, we propose to study different solutions of lenses on wafer which can be applied for spatial applications, and the associated physical phenomenon. Material behaviors should be taken into account for extreme environmental conditions. A micro-concentrator system will be realized and tested under solar simulation.

Learning Techniques for Joint Proactive Communication, Computing, Caching in 5G and Beyond Networks

Département Systèmes

Laboratoire Sans fils Haut Débit

01-10-2018

SL-DRT-18-0875

Nicola.DIPIETRO@cea.fr

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 5G network revolution will be enabled by cutting-edge technological innovations, concerning millimeter-wave radio communications, baseband and RF architecture, resources virtualization, and much more. A game-changing idea consists in empowering the mobile edge of the network with data elaboration and storage capabilities, thus bringing cloud support the closest possible to the user. This paradigm is called Mobile Edge Cloud (MEC). In the proposed PhD investigation, we consider MEC empowered by small cell access points, endowed with hardware and software resources adapted to handling the three main pillars of modern networks: communication, computing, and caching. The research will target the design of solutions for joint allocation of these resources. The PhD candidate will explore the very recently-proposed and innovative concept of computational caching: reducing latency and optimizing precious computational resources by reusing the same processing results for different users. The work will focus on the design of algorithms for a proactive and dynamic implementation of computational caching, targeting the optimal efficiency of the joint allocation of the above mentioned resources. Distributed learning techniques will be investigated and proposed.

Compact modeling of MOSFETs operating at cryogenic temperatures

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-10-2018

SL-DRT-18-0883

thierry.poiroux@cea.fr

Recent experimental demonstrations of silicon-based Qbits pave the way to the fabrication of quantum computing circuits with standard nanoelectronics technologies. However, the design of such Qbit-based functional circuits requires a relevant design environment. In particular, designers need compact models able to reproduce the behavior of MOSFETs operating at cryogenic températures. CEA-Leti has developed a physics-based compact model dedicated to FDSOI technology, called Leti-UTSOI, that is used in industrial design kits. This model has been conceived to fulfill the requirements of applications operating close to ambient temperature (typically -45° to +125°). Therefore, new developments are required in order to extend the predictability of Leti-UTSOI down to ultra-low températures. These developments are essential in order to simulate, optimize and validate the design of circuits at cryogenic temperature. Moreover, they will be implemented in other compact models dedicated to bulk MOSFET technologies or to finFET and nanowire device architectures. The availability of these models, able to reproduce the behavior of various transistor architectures at very low températures, will allow very useful benchmarks of MOSFET technologies for cryogenic applications.

GaN/Si transistor compact modeling for power and RF-5G applications

Département Composants Silicium (LETI)

Laboratoire de Simulation et Modélisation

01-10-2018

SL-DRT-18-0888

joris.lacord@cea.fr

GaN RF devices are developped since more than 15 years by industrial companies and many research laboratories continue to improve this technology. Leti wants to start a GaN/Si activity, mainly for 5G application. It will be based on Leti experience concerning GaN/Si device for power application. A first version of compact model was developped for Normally-ON transistor and is already available at Leti (Leti-HSP). Nevertheless, this model core (DC) needs to be consolidated and improved to justify its use for Normally-OFF transistor and then to be adapted to GaN-RF transistors, which are, at device structure level, very different from power devices. Those model developpments are mandatory to determine the GaN/Si technology potential for power and RF applications. Leti-HSP model was developped at Leti and well described device behavior (DC/AC) of GaN/Si power devices. The first step of this PhD thesis will be to understand the existing model code (verilogA language) and to determine its force and weakness. A special focus will be needed on on the description of current stauration but also of moderate inversion regime both known as weaknesses of Leti-HSP model in terms of accuracy. Weaknesses analysis of the existing model will then be followed by the development of a new version with associated model, which will be provided to designers through a PDK (Process Design Kit) Finally, after the study of differences between GaN/Si transistor for power and RF applications, the final objective of this PhD thesis will to to bring the mandatory modification to Leti-HSP model to guarantee its ability to describe GaN/Si device behavior in RF field. Each activity listed above will be supported by: ? Power device compound integration laboratory of Leti with its strong expertise in GaN/Si device physics. ? Electrical characterization with the collaboration with the electrical characterization laboratory of Leti which already perform GaN/Si device characterization. ? TCAD simulation, performed by the PhD student in the simulation and modeling laboratory of Leti to deeply understand GaN/Si device behavior, to be able to build an analytical model.

Development of a drip process for the elaboration of silicon milli-balls.

Département des Technologies Solaires (LITEN)

Laboratoire Matériaux et Procédés Silicium

01-10-2018

SL-DRT-18-0903

malek.benmansour@cea.fr

The photovoltaic industry knows a strong growth and an important reduction of the manufacturing costs of the solar devices. One of the reasons is the industry's adoption of the diamond wire technology for silicon blocks cutting. This technology besides allowing a reduction of the core wires, allows the feasibility of the silicon wastes (named kerf-Si or powders) which represent approximately 40 % of losses. Those powders have a granulometry centered around the micron and an apparent density close to 0.7 g.cm-3 when the density of the polysilicon is at 2.33 g.cm-3. This last point is an important issue for the implementation of a process of silicon powders recycling. Thus, the aim of this work is to develop a solution allowing the shaping and the densification of the fine silicon powder in order to reuse it in a directional solidification process. The studied solution in the present thesis, co-financed by the CEA (French Atomic Energy Commission), is to develop a synthesis process of milli-balls of silicon by a flow of drops. The work will start by the conception, the realization and the optimization of the pilot furnace dedicated to the flow of drops as well as the development of an on-line monitoring system. The control of the powder densification requires the study of numerous process parameters and the characteristics of the raw material. The obtained milli-ball are finally validated as a raw material in a standard crystallization process in order to elaborate silicon ingots for photovoltaic applications.

Performance demonstration of Guided Wave based Structural Health Monitoring for aerospace

Département Imagerie Simulation pour le Contrôle (LIST)

Laboratoire Méthodes CND

01-10-2018

SL-DRT-18-0918

olivier.mesnil@cea.fr

Access to space is a critical stake of the first half of this century, demanding the conception of new low-cost and reusable space launchers leading to a new kind of demand for structure monitoring and maintenance. Structural Health Monitoring (SHM) is a group of methodologies aiming at monitoring large and potentially complex structures by embedding sensors permanently on or within it. SHM is particularly promising for aeronautical and aerospace structures to provide early defect detection and optimize the use. Guided Wave (GW) based SHM relies on the use of guided elastic waves to interrogate the structure and detect flaws as change in the GW propagation. Even though multiple in-lab prototypes of GW-SHM system do exist, the main barrier to a mainstream adoption of the technology is the difficulty to demonstrate the performances of such a system. Indeed, the performances must be quantified and certified before any usage of such technologies in the demanding aerospace and aeronautical industries. The objectives of this thesis is to develop, based on simulation tools for GW simulation, a methodology to quantify the performances of a GW-SHM system. This goal will require the following tasks: After getting used to the simulation tools and the SHM imaging methodologies available in the laboratory, a statistical approach to quantify the performances of an SHM system based on the simulation will be developed. Experimental trials will then be conducted to validate the approach and eventually improve the gap between the simulation and the experiment. This thesis is part of the collaboration CEFIPRA program between France and India (CEFIPRA: Centre franco-indien pour la Promotion de la Recherche avancée).

Processors ensuring confidentiality, authenticity and integrity of programs

Département Systèmes

Laboratoire Sécurité des Objets et des Systèmes Physiques

01-12-2018

SL-DRT-18-0965

olivier.savry@cea.fr

Until now, confidentiality, authenticity and integrity have never been shown jointly in modern secure processors, whereas they are essential to guarantee the intellectual property, deployment, safety and reliability of products Industrial objects such as IoT (Internet of Things) or CPS (Cyber Physical Systems). In this thesis, we will seek to ensure the integrity of program execution with authenticated encryption of instructions and lightweight and powerful data from the CAESAR competition. It will be shown that confidentiality can be achieved by these same techniques and that they allow a simple deployment. The correct execution of the flow of instructions will be proved and this until the processing by the ALU using corrector and / or error detection codes. The derived security architecture can then be validated on RISC V on an FPGA target.

Electric Field mapping by scanning transmission electron microscopy

Département Technologies Silicium (LETI)

Autre laboratoire

01-10-2018

SL-DRT-18-0983

david.cooper@cea.fr

The candidate will develop scanning transmission electron microscopy based techniques for the measurement of electric fields (dopants and piezoelectricity) with nm-scale resolution. The recent availability of fast CCD cameras allows the deflection of an electron beam to be locally measured as it is scanned across a region of interest. From the deflection of the beam, information about the electric and magnetic fields can be obtained. Experiments will be performed using a double aberration corrected FEI Titan Ultimate equipped with a fast One-View camera. A range of different specimens will be examined during this Phd subject, including Silicon CMOS devices and IIIV devices for applications such as energy efficient lighting. In this Phd subject we will develop the technique in terms of the optimization of the electron microscope focusing on spatial resolution, sensitivity and the reduction of electron beam damage on the specimen. In addition, some light coding tasks will be required to fit the position of the measured electron beam to provide accurate measurements of the fields. This subject will suit a candidate looking to expand their experimental skills combining state-of-the-art electron microscopes tools to develop the characterisation techniques of the future.

Development of low-temperature processes for the synthesis of lamellar (2D) sulfides

Département Technologies Silicium (LETI)

Laboratoire

01-09-2018

SL-DRT-18-0993

stephane.cadot@cea.fr

Among the most promising materials for ?More than Moore? technologies (chemical sensors, photodetectors, nano-batteries,?), 2D transition metal dichalcogenides have recently been identified as high-potential candidates. In particular, semiconducting transition metal disulfides such as MoS2 and WS2 have been thoroughly studied because of their chemical robustness, but their synthesis actually requires ultrahigh-temperature processes (> 800°C) which severely hinder their integration capabilities. In this context, tin disulfide (SnS2) appears as a good alternative to MoS2 or WS2 since it can be obtained with good crystallinity at much lower temperatures (< 350°C), making it potentially compatible with an ?above IC? integration. Moreover, tin is a relatively non-toxic and earth-abundant metal with almost all of its oxide and sulfide derivatives (SnS, Sn2S3, SnS2, SnO et SnO2) being semiconductors, which opens up a wide range of perspectives in term of potential applications. This PhD work will aim at developing industrially-relevant processes for the synthesis of SnS2 (or other semiconducting 2D materials that can be obtained at low temperature), either by sulfurization of the corresponding oxide or using a deposition process such as ALD (Atomic Layer Deposition), in order to create novel devices based on these materials, and ideally compatible with already-existing technologies on 200 or 300 mm wafers. This study will also cover the characterization of the obtained materials through different methods (XPS, X-ray fluorescence, Raman, XRD, TEM, KPEEM,..) as well as the assembly of basic devices allowing to establish a correlation between physicochemical properties and electrical characteristics of the target material.

Development and characterization of innovative etch process with very large selectivity ? application to low-k spacer etch for advanced embedded flash memories technologies

Département Composants Silicium (LETI)

AUTRES

01-10-2018

SL-DRT-18-0997

erwine.pargon@cea.fr

Advanced embedded flash memories technologies are being developed at STMicroelectronics for various applications. The latest technology node is based on FD-SOI 28nm CMOS, with the constant will to improve device performance. The introduction of new low-k materials in the gate stack introduces new etch challenges, especially the etch stop on the SiGe underlayer. Damages or consumption of this layer would compromise the device performance. In this context, the objective of this thesis is to evaluate innovative spacer etch processes for low permittivity spacer materials, using advanced plasma etch chamber. The work will consist in characterization of this spacer etch and of its impact on both etched material and substrate materials. The goal is to understand the etch mechanisms at stake during this process. The work thesis will be conducted at ST Crolles site and in LTM laboratory (Laboratoire des Technologies de la Microélectronique) CNRS, on the CEA Grenoble site

Extreme elastic deformation of semiconductor materials for optoelectronic applications

Département Composants Silicium (LETI)

AUTRES

01-10-2018

SL-DRT-18-0998

jumana.boussey@cea.fr

Extreme elastic deformation of materials has been proven to modify their physical properties paving the way to numerous innovative applications. The goal of this thesis consists in the homogeneous deformation of a crystalline film over a macroscopic surface up to levels never obtained so far by other methods. For semiconductors materials, such a deformation allows for an important modification of optical and electronic properties: For instance, the charge carrier mobility can be significantly enhanced in silicon under tensile strain while the band structure of germanium undergoes various modifications when exposed to strain. High tensile strain levels have led to change this indirect semiconductor into a new material in the sense of a quantitative (band gap) and qualitative (indirect-direct transformation) modification of electronic properties. The intention of this thesis topics is to obtain the quantitative control of elastic strain imposed in a germanium crystalline film and to produce a proof of concept material for innovative industrial applications

Thermomechanical Modeling of Photovoltaic Modules Manufacturing Processes . THERMOD

Département des Technologies Solaires (LITEN)

Laboratoire Modules Photovoltaïques Silicium

01-09-2018

SL-DRT-18-0999

maryline.joanny@cea.fr

Photovoltaic (PV) modules are made of a stack of active PV layers (Si, passivation), protective polymer encapsulation and glass plates. Performance and lifetime of PV modules depend on their ability to sustain various environmental conditions that are linked to thermomechanical, physical, chemical and/or electrical phenomena. The purpose of this PhD is to model the cells encapsulation and interconnection processes to better understand their influence on the main failure mechanisms observed in the modules. In order to address such technological and scientific issues, the research work will focus on: - Modeling the thermomechanical phenomena experienced by a module during its manufacturing process and evaluating the induced residual stresses within the module; - Determining the impact of the thermomechanical conditions on module performance and the level of residual stresses; - Proposing solutions to reduce the levels of residual stresses. Numerical models will be developed to simulate the thermomechanical phenomena involved during the manufacturing processes of PV modules. The influence of the process parameters on the modules performance will be modeled and validated experimentally to better optimize the processes and the selection of materials involved in the PV module.

GaN doping by ion implantation and innovative annealing

Département Technologies Silicium (LETI)

Autre Laboratoire

01-10-2018

SL-DRT-18-1001

frederic.mazen@cea.fr

In response to societal needs for the preservation of the environment and alternative energies, the CEA is developing an activity on the production of power devices. For this, the CEA has chosen a breakthrough technology based on the use of Gallium Nitride, which should make it possible to overcome the theoretical limits of silicon. However, GaN-based technologies are much less mature than those based on the use of silicon. The objective of this thesis work will be to contribute to the implementation of the technological GaN doping brick by ion implantation and to seek innovative annealing allowing to anneal at very high temperature in order to activate the dopants without damaging the structure of the Gan on Si wafer. Despite significant progress in recent years, the realization of effective doping processes and the understanding of the associated mechanisms remain significant challenges. This work will involve the development of ion implantation processes and innovative heat treatments that will be evaluated and compared to reference processes. A particular focus will be on understanding and modeling the impact of defects created by the implantation process and their evolution during thermal treatments on the activation of dopants. For this, many physicochemical, structural, optical and electrical characterization techniques (SIMS, TEM, RBS / MEIS, X-ray Diffraction, PL, ECV, Tomographic Atomic Probe, Hall Effect ...) will be implemented or developed. The final objective of the work, in connection with the integration teams, will be to develop doping processes adapted to the specifications of the envisaged devices.

3D porous materials for the design of sequential fluidic bioreactors

Département Nord Pas De Calais

01-10-2018

SL-DRT-18-1018

frederic.revol-cavalier@cea.fr

3D porous materials are currently used for their intrinsic structural properties that offers exceptional surface/volume ratio. This property allows rapid exchanges between a processed fluid and the macroporous surface. Moreover, the use of deformable (compression, stretching?) macroporous materials enables easy management of filling and the extraction of fluids through reduction or increase of the internal volume under mechanical stress. These deformable macroporous 3D structures represent a new class of materials of high interest for the design of electrochemical bioreactors. Indeed, the intrinsic open-porosity could be used for the confinement of biological species (enzymes or cells), transforming each pore into single microreactor. Moreover, this 3D macroporous structure could benefit from further implementation of electronic conductivity to the structural material to generate volume 3D electrodes. This thesis deals first with the development of conducting, biocompatible and deformable 3D macroporous-materials in the perspective of enzymatic or cell bioreactor design. These materials will bring original insights on in situ monitoring of cell cultures or on the design of highly sensitive biosensors. Thereby, in a second step the thesis will consist on the functionalization of the macroporous structures and on the design of the bioreactors. The applicant should presents a strong background on materials sciences (and especially macropourous deformable materials) and electrochemistry. Some knowledges on biology/biochemistry and microfluidic would be positive.

Electronic Additive Manufacturing for Smart Materials

DLORR

01-10-2018

SL-DRT-18-1019

manuel.fendler@cea.fr

Additive manufacturing offers the opportunity to revolutionize the fabrication of printed circuits, whose architecture is similar to a 2D + Z vertical stack. Indeed, the photolithography and chemical deposition processes necessary for the realization of the tracks, are not only harmful for the health and the environment, but also do not allow the direct functionalization of 3D objects. At the time of the Internet of Things, intelligence is getting deeper and deeper into designs, and additive manufacturing gives a unique opportunity to value the inter strata obtained by 2D + Z slicing. Thus we propose to leave the manufacture of printed circuits from chemical baths, in favor of an addition of conductive material by 3D printing.

3D Objects discovery in 3D scene

DPLOIRE (CTReg)

Autre

01-10-2018

SL-DRT-18-1039

anthony.mouraud@cea.fr

Object detection and localization in images is a problem studied since many years. The latest technological developments now allow the real-time acquisition of depth data coupled to color data (RGBD). At the same time, modern machine computing capabilities and intelligent image processing methods have led to significant advances in the detection / localization of 2D objects with many different approaches (bounding boxes, contours, from CAD models ...). An important step is being taken in recent years with the research conducted to directly extract the volume of detected objects and their position in 3D. These works are still in their infancy, but the first results are encouraging, both from 2D images (eg DeepManta) and from 3D images (eg Deep Sliding Shapes). However, there remain several identifiable scientific / technological barriers before allowing the democratization of this type of approach for the automatic extraction of objects in potentially unknown scenes. The objective of this work is to identify the current approaches of detection / localization of 3D objects, to target their weaknesses and work on new processing technologies to mitigate them. Moreover, the object discovery in unknown environments and the inference of the operator's intention by observation / location of his attention are two areas of interest that this work aims at addressing. Beyond their applications for demonstration learning, the software bricks resulting from this project can also be reused for other applications such as augmented reality ("smart" scanning, etc.), surveillance or mobile mobility for example.

Fabrication and characterization of normally-off GaN high electron mobility transistor (HEMT)

Département Composants Silicium (LETI)

AUTRES

01-10-2018

SL-DRT-18-1043

erwine.pargon@cea.fr

GaN-HEMT silicon substrate technologies are seriously considered as the next generation of power electronics devices between 200V and 1200V. The basic component for this new technology is the Normally-Off transistor. The latter must have electrical figures of merit perfectly mastered and reliable over time (voltage-breakdown, threshold, leakage current grid, saturation current ....). A promising approach for "normally-off" operation is to use a metal-insulator-semiconductor architecture for HEMT (MIS-HEMT). However, the expected performance for the reliability of these components subjected to high voltage, current and temperature constraints require a material quality with less defects and a perfect technological mastery. Two key steps of this technological process are the etching of the cap on the active area of ??the transistors and the deposition of the gate dielectric and its associated surface pretreatment. These steps directly control the instabilities of the threshold voltage of the transistors related to the interface states, gate leaks and therefore to the proper operation of the latter. For GaN MIS-HEMT technologies to be widely adopted in the power electronics devices of the future, it is necessary to be able to remove the technological barriers related to the manufacture of these devices. The objectives of the phD research project proposed jointly by the LN2 in Sherbrooke, Quebec, Canada and the LTM in Grenoble, France is then to fabricate a normally off GaN MIS-HEMT with optimal electronic performances

Towards a logics and tooled framework for the refinement and verification of properties that improve privacy and data protection in systems

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire exigences et conformité des systèmes

01-09-2018

SL-DRT-18-1044

gabriel.pedroza@cea.fr

The overall objective of this PhD is to define, specify and deploy a formal framework (logics) which allow to (1) model systems including data processes, and (2) verify properties related to the Privacy and Data Protection (PDP) area. To do so, the candidate should first define a formal language supporting systems modeling in which data flows, users/stakeholders, processing units and storages interact. The language should be enriched with a formal semantics (for instance an operational semantics) in order to support the verification of high-level requirements derived from privacy-related-risks methods like LINDDUN (https://distrinet.cs.kuleuven.be/software/linddun, Linkability, Identifiability, Non-repudiation, Detectability, Disclosure of information, Unawareness, Non-compliance). Once the framework is already defined, a set of algorithms should be designed and deployed in order to verify the properties and relations associated to the high-level privacy requirements. To accomplish this phase, the candidate should set appart properties to be verified at model level from those to be verified at code level (for instance, targetting a C-code). A refinement method and the application of existing verification tools (concretely the Frama-C tool, https://frama-c.com/) are foreseen. In addition, the high-level requirements and systems modeling module will be deployed on the top of the Papyrus environment (https://www.eclipse.org/papyrus/).

Inverse reinforcement learning of a task performed by a human

DPLOIRE (CTReg)

Autre

SL-DRT-18-1047

laurent.dolle@cea.fr

Learning from demonstration involves an agent (e.g., a robot) learning a task by watching another agent (e.g., a human) performing the same task. It often uses reinforcement-learning methods to improve the robot's ability to perform a task in new situations (i.e., generalization). These methods involve providing a positive reinforcement (i.e., a reward) when the outputs of the algorithms help achieving the task, but require a human designed reward function. The more the task is complex the more difficult is the reward function to design, but it can be learned from a series of examples with methods called inverse reinforcement learning. The use, jointly or not, of these techniques has shown encouraging results, but which are limited to toy examples and cannot be adapted as such to tasks more representative of the industrial environment. During the thesis, the PhD student will analyze and test state-of-the-art previous works. S/He will then propose a method, combining inverse reinforcement learning to other algorithms (e.g., generative adversarial networks, GAN), so that the robot will understand the task performed by the operator (with as little explanation from the operator as possible), and will generalize enough to make the robot robust to dynamic environments (obstacles, moving objects?). This method should be suited for a "pick and place" task in an industrial environment and ensure a reasonable enough learning period (information a priori, feedback from the operator) for tasks of medium complexity.

Understanding TCO/a-Si:H interface limitations in heterojunction solar cells: improvement in front and back side for bifacial devices

Département des Technologies Solaires (LITEN)

Laboratoire HETerojonction

01-10-2018

SL-DRT-18-1049

perrine.carroy@cea.fr

In this work, the interface between the transparent conductive oxide (TCO) layer and the hydrogenated amorphous silicon (a-Si:H) layer of silicon heterojunction (SHJ) solar cells will be extensively studied for the front and the back sides of bifacial devices. The main objectives will be: 1- Characterize the interface by means of electrical and morphological characterization for different amorphous layers and different TCO materials or TCOs deposited by different techniques (PVD, ALD, SALD, others). Electrical simulation can be also performed. 2- Optimize the interface according to the results of characterization and simulation by tuning the interfacial properties of the a-Si:H and TCO layers and integrate the optimized layers into SHJ solar cell devices. Optical and electrical characterization of the final devices will also be performed. 3- Define the best configuration of the a-Si:H/TCO stack for bifacial solar cells in order to increase the bifaciality of the devices.

Towards a tooled framework and method for safety and security co-engineering of Ciber-Physical systems guided by the integration, refinement and verification of patterns

Département Ingénierie Logiciels et Systèmes (LIST)

Laboratoire exigences et conformité des systèmes

01-10-2018

SL-DRT-18-1057

gabriel.pedroza@cea.fr

Problematics and main goal: Nowadays, the so called Cyber-Physical Systems (CPS) are deployed in a variety of application domains like automotive, aeronautics, health care, etc. The impacts in case of failures or misbehaviours, due to accidental faults or attacks, may be critical with respect to economical, business, and safety criteria and, in the end, potentially jeopardize human lives. According to the principle called correct-by-design, an effective identification and management of safety and security risks is crucial and should be conducted at early design phases in the systems development cycle. However, the state of the art of approaches for safety and security engineering shows that, for many cases, the analyses are conducted independently and, more importantly, without including a co-engineering phase that ensures their consistency. Despite that, several known CPS case studies (e.g.,in the automotive domain) exhibit a clear and critical entanglement between safety constraints (e.g., performance and latency) and security exigencies (e.g., ciphering mechanisms). To prevent potential conflicts and ensure consistency between safety and security exigencies, a joint safety-security analysis need to be conducted. It is clear that a joint safety-security analysis may not be necessary for certain systems, however for those that need it, the co-engineering phase can become critical. Since safety and security analyses can be conducted independently and are indeed challenging subjects due to their inherent complexities, new methods, formal languages, techniques and tools are needed to better support and ease safety-security co-engineering. The proposed Ph.D. targets a formal framework and tool to integrate this decisive phase into the systems development cycle.

Machine Learning for a precision agriculture

DLORR

01-11-2018

SL-DRT-18-1060

ulysse.marboeuf@cea.fr

This PhD is at the interface between agriculture and Machine Learning. The project is based on a collaboration between the CLAAS company based in Woippy (Moselle) specialized in the manufacture of "high-end" agricultural Equipment and CEA Tech in Metz. This PhD is part of the statistical modeling of an agricultural press system. It aims to design a parametric statistical model by supervised learning, to automate the compression procedure of the biological material and help the farmer in this task. This model must meet physical and environmental constraints.

¨Preamorphization via ion implantation for salicide optimization

Département Technologies Silicium (LETI)

Laboratoire

01-09-2018

SL-DRT-18-1064

frederic.mazen@cea.fr

? Pre-amorphization implantation (PAI) for salicidation has been introduced during the last years to limit leakage junction, to optimize Schottky Barrier Height (SBH) and contact resistance of ultra-shallow junction by controlling roughness and limiting agglomeration of silicide. It seems also a good way to increase contact stability and yield, for example, by limiting silicidation close to the FD-SOI MOS transistor channel (piping defect). To take benefit and integrate this new step in the next CMOS technology generation and beyond, it seems necessary to accelerate development and understanding on this item. ? The thesis objectives will be to develop a process and to acquire a well understanding of the different interaction between pre-amorphization implantation conditions (species, energy, dose, etc.), and NiSi (or NiSiGe) formation in terms of metallurgical structure, roughness, and agglomeration. Interaction with dopant junction will be also studied. In parallel, piping evolution with PAI could be explored on morphological wafers. At the end, PAI physics understanding and impact on NiSi material will be discussed. Electrical performance, contact resistance, silicide stability and yield will be the figure of merit of developments. This work will have to permit a reduce development time to integer this new process in the next transistor Technology. Thesis will be achieved in collaboration with CEA-LETI and IM2NP. ? Based on the state of the art, and technological constraint, student will propose experiment, and characterization needs. He will be in charge of defining morphological and electrical test vehicle (short-loop) with adapted process flow, and following realization in clean room. Standard physical and electrical characterization as DRX in temperature, TEM (EDX, cross-section), SIMS, TLM and Rs measurement will be used. Thanks to IM2NP experience in Atom Probe Tomography (APT), 3D chemical analysis of NiSi will be a key to exhibit composition, segregation effect and understanding correlation between silicidation, PAI and contact parameters. TCAD simulation could be also used to define implantation conditions.

Acoustic characterization of direct bonding energy

Département Technologies Silicium (LETI)

Laboratoire

01-11-2018

SL-DRT-18-1069

frank.fournel@cea.fr

Direct bonding is now more and more used for imager application for instance. One of its main parameter is the direct bonding energy but up to now, its characterization is based on a destructive technique as the DCB technique for instance. Last year, at the end of Ali Dekious Phd, a new way to characterize the bonding was discover using the acoustic microscopy. This acoustic characterization is non destructive and could perform a mapping of the bonding energy with a millimeter precision. This is very important as the bonding energy of the wafer edges could then be measured for the first time. But this technique is bright new and further developments are needed to have a reliable characterization. The aim of this project is to use the acoustic microscopy to characterize the bonding energy of direct bonding interface using standard commercial acoustic microscope. At first, a qualitative bonding energy mapping will have to be obtain. Then a research on the quantification of the acoustic bonding energy will be conducted using several standard bonded structure. This work will also need a good characterization and modelisation of the acoustic signal in order to use and to develop the model done by previous works.

Water management in direct bonding

Département Technologies Silicium (LETI)

Laboratoire

01-10-2018

SL-DRT-18-1070

frank.fournel@cea.fr

Direct bonding is now used in many applications. Very recently, at CEA Grenoble, it has been shown that water can soak in a non-annealed direct bonding interface as well as to be removed from it. As water is one of the main parameter in hydrophilic direct bonding, controlling and accurately understand this phenomenon is very important for all hydrophilic direct bonding and not only for the Silicon/Silicon bonding. This study aim will be to study in detail the water management inside a direct bonding interface following different ways: A first part of the study will be to find a way to isolate the bonding interface. It is mandatory for all the accurate characterization of the direct bonding in order to have stable samples. It is also very interesting for many applications for which the edges are important and would like to get rid of this phenomenon. A second part of the study will be to continue the characterization of the water low dynamic at an annealed direct bonding interface. It will be also interesting to evaluate this flow during the annealing. The in or out dynamic will be evaluate regarding the bonding energy reached by the interface at the different annealing temperature. A last part of the study will be to evaluate accurately the water amount at the hydrophilic direct bonding interface of ?stable? samples. Varying this water quantity, a link will be done with the direct bonding energy and the possible defectivity which could appear under certain conditions. The student will be formed to all the needed technology used in direct bonding (chemistry, CMP, bonding, thermal annealing?) as well as all its usual characterization techniques (Infrared spectroscopy, acoustic microscopy, anhydrous bonding energy, XRR?)

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