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

PhD : selection by topics

Atomic resolution imagery composition measure applied to superarrays

Département Technologies Silicium (LETI)

Autre laboratoire

01-10-2019

SL-DRT-19-0639

nicolas.bernier@cea.fr

For crystalline materials sensitive to electron beam radiation damage, it is necessary to quantify the chemical composition at the atomic scale while minimizing the electron dose. The usual analytical techniques in the transmission electron microscope (TEM) can not be used because of the high probe current and the relatively long acquisition time. On the other hand, atomic imaging, more precisely using the high-angle annular dark field (STEM-HAADF), is performed at a reduced dose and exhibits contrasts proportional to the atomic number of the elements. In addition, the TEMs Titan on the PFNC are equipped with an aberration corrector to acquire state-of-the-art HAADF images in terms of atomic resolution. However, for the contrast in these images to be quantitatively related to the chemical composition of the material, controlled TEM acquisition conditions and electronic scattering simulations must be developed. In parallel, another imaging technique in the TEM is attracting growing interest: ptychography, or "4D data STEM". This technique, consisting in acquiring a diffraction pattern for each position of the incident electron beam, provide the projected potential in the sample. The development of the quantitative aspect of these imaging techniques has many applications: the one targeted in this thesis is the understanding of the atomic order of GeTe / Sb2Te3 superlattices, materials considered as the most promising for phase change memories (PCRAM).

Hydrogen storage and transport by bio-based liquids

Département Thermique Biomasse et Hydrogène (LITEN)

Laboratoire Echangeurs et Réacteurs

01-10-2019

SL-DRT-19-0641

alban.chappaz@cea.fr

Climate change is becoming one of the major challenge and concern to be solved in the next years. This target implies a transition from a largely fossil carbon-based energy to a decarbonized energy. In this frame, hydrogen produced by electrolysis of water is an energetic vector of the future. However, efficient hydrogen transport and storage solution are still under study, which account for its lack of large scale development of this technology. In that context, liquid organic hydrogen carriers (LOHC), because of their high volumetric and gravimetric density together with a stable behavior in ambient conditions and safe easy handling, offers promising solutions to overcome hydrogen transport and storage issues. The goal of the thesis is to study hydrogenation/dehydrogenation reactions of innovative and promising compounds in order to validate their use as LOHC.

Measurement of nuclear decay data for beta decay and electron capture using metallic magnetic calorimeters

DM2I (LIST)

Laboratoire de Métrologie de l'Activité

01-09-2019

SL-DRT-19-0643

matias.rodrigues@cea.fr

In the framework of ionizing radiation metrology, one of the tasks of the Laboratoire National Henri Becquerel (LNHB), the French national laboratory for ionizing radiation metrology, is the precise determination of nuclear decay data. During this PhD thesis, cryogenic detectors will be developed for the precise measurement of the shapes of beta spectra, photon emission probabilities and capture probabilities of radionuclides decaying via electron capture. These data are required in various fields of research and application, including nuclear medicine, nuclear energy and waste management, or neutrino physics research. The PhD student will conduct experiments comprising the conception and fabrication of cryogenic detectors, their operation in a complex cryogenic setup, work with highly specific electronics, Monte Carlo simulations, and data analysis using sophisticated methods. The measured data will be compared with theoretical calculations and help to improve nuclear data tables.

Explaining predicitive-model decisions: towards automatic interpretation of tree-ensemble models

DM2I (LIST)

Laboratoire d'Analyse des Données et d'Intelligence des Systèmes

01-09-2019

SL-DRT-19-0644

pierre.blanchart@cea.fr

Until recently, the focus in predictive modelling has mainly been set on improving model prediction accuracy. Many successful models scaling to big amounts of heterogeneous data have been proposed in the literature, and widely used implementations of these models are available. Unfortunately, these models generally do not intrinsically come with an easy way to explain their predictions, and are often presented as black-box tools performing complex and non-intuitive operations on their inputs. This can be an issue in many applications where the interpretation of the model decision may have a greater added-value than the decision itself. Examples include medical diagnosis where the interpretation would consist in identfying which combination(s) of characteristics presented by an individual contributes most to the diagnosis. In this thesis, we propose to add interpretability to a specific class of machine learning models known as tree-ensemble models, without impacting the performance of the model we want to interpret. In the continuation of the work already initiated in the laboratory, the objective is to analyze the combinations of input features along with their respective numerical values, so that each instance-level decision taken by the model can be explained by a set of input features having particular numerical values. Fault detection in connected manufacturing provides an interesting application for such approaches, and data as well as the fault detection models will be provided as a starting point for this thesis work.

Spintronic Wake-Up Radio

Département Architectures Conception et Logiciels Embarqués (LIST-LETI)

Laboratoire Architectures Intégrées Radiofréquences

01-09-2019

SL-DRT-19-0645

dominique.morche@cea.fr

The increasing number of wireless connected objects and smart sensors requires defining components and operational schemes that drastically reduce the power consumption. Within such communicating networks the RxTx modules are the most power consuming elements. The solution actively searched for is to switch off the main RxTx module when no communication is requested and to use a low power, degraded wake-up radio receiver WuRx that will switch on the main module when receiving an according wake-up signal. The realization of robust and ultralow power WuRx is an active field of research. The thesis proposes to explore RF spintronic devices as such a compact and low power solution. Magnetic tunnel junctions, which are the main spintronics building blocks, are capable to passively convert an RF signal into a DC signal, with frequency selectivity and at relatively high output signal levels. LETI/DACLE and INAC/SPINTEC work together on the realization of such spintroncis based WuRx and the PhD project will be at the interface of the two laboratories. While SPINTEC will realize the devices and optimize their sensitivity to low input signal levels, the thesis will be carried out at LETI/DACLE to realize the corresponding antenna networks and rf electronics. In order to establish the performance parameters the student will first spend some time at SPINTEC to get trained on the characterization of spintronic based rf components. The student will also be involved in the testing of the developed rf circuits with the spintronics components to iteratively optimize the electronic circuits and adapt it to the spintronics device performances.

Advanced network management for controlling the real-time redeployment of a mobile network infrastructure under traffic performance constraints

Département Intelligence Ambiante et Systèmes Interactifs (LIST)

Laboratoire Systèmes Communiquants

01-10-2019

SL-DRT-19-0646

Michael.Boc@cea.fr

The digitization of industries introduces the need for providing high-speed wireless connectivity on industrial sites, which is extremely difficult due to the constraints imposed by these environments. To address them, this PhD thesis will investigate opportunities to increase real-time reconfiguration capabilities of the wireless infrastructure by means of an SDN-oriented management of the network. This network management will control the mobility of the infrastructure equipment as an additional degree of freedom in order to improve the performance of the data flows. This capability should provide two key benefits: 1) not having to rely on a lengthy and costly planning phase for network deployment, and 2) being able to implement new and more sophisticated network reconfiguration strategies to increase its overall performance level at any time. The mobility of the infrastructure could be provided by mobile robots that can be controlled through an SDN protocol and carrying some of the network equipment. In the case of a nuclear dismantling operation, for example, we could consider the wireless communication infrastructure as being composed of a fleet of mobile robots (terrestrial or aerial) whose mobility is managed by a network management system (SDN) in charge of ensuring the proper performance of the connectivity for dismantling robots remotely operated. The objective of the proposed thesis work is to define an advanced and centralized network management system for the control of the real-time redeployment of a mobile network infrastructure under performance constraints of data flows. This system should be able to 1) identify when a topological change becomes relevant considering the types of data flow performance problems and the limitations of existing network optimization solutions, 2) to define and pilot the redeployment of the network infrastructure in order to improve the performance of these data flows.

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