Diphasic thermoregulation system for ultra wide bandgap diamond semiconductors
The objective of this thesis is to study a diphasic thermoregulation system for ultra wide bandgap diamond semiconductors. One of the specific behavior of diamond semiconductors is the negative temperature coefficient of is on-state resistance. The thermoregulation proposed in this thesis aims to optimize the global losses of the system and to insure both temperature and electrical constraints between several diamond semiconductors in parallel.
Based on specifications that will be defined at the beginning of this theses (calories to dissipate, temperature range to control), the PhD candidate will have to:
- Define a temperature control strategy
- Define most appropriate materials and fluid of this system
- Design the thermoregulation system
- Realize and validate experimentally the proposed system
This thesis will tackle numerical simulation (component and thermoregulation system modelling) and experimental tests through the realization of a TRL 3-4 prototype of power converter system integrating diamond Schottky diodes.
The global objective to achieve is to put forward an innovative system modeled and experimentally demonstrated, where control strategy, dimensional and operative elements will be investigated and optimized.
From angstroms to microns: a nuclear fuel microstructure evolution model whose parameters are calculated at the atomic scale
Controlling the behavior of fission gases in nuclear fuel (uranium oxide) is an important industrial issue, as fission gas release or precipitation limit the use of fuels at extended burn-ups. The gas behavior is strongly influenced by the material’s microstructure evolution due to the aggregation of irradiation-induced defects (gas bubbles, dislocation loops and lines). Cluster dynamics (CD) (a kind of rate theory model) is relevant for modelling the nucleation/growth of the defect clusters, there gas content and the gas release. The current model has been parameterized following a multiscale approach, based on atomistic calculations (ab initio or empirical potentials). This model has been successfully applied to annealing experiments of UO2 samples implanted with rare gas atoms and has emphasized the impact of the irradiation damage on gas release. The aim of this PhD thesis is now to improve the model, particularly the damage parameterization, and to extend its validation domain through in depth comparison of simulation with a large set of recently obtained experimental results, such as gas release measurement by annealing of sample implanted in ion beam accelerator, bubble and loop observation by transmission electrons microscopy of implanted or in-pile irradiated samples. This global analysis will finally yield an improved parameterization of the CD model.
The research subject combines a “theoretical” dimension (improving the model) with an “experimental” one (interpreting existing experiments or designing some new ones). The variety of techniques will introduce you into the experimental world and thus broaden your scientific skills. You will be welcomed at the Fuel Behavior Modeling Laboratory (part of the Institute for Research on Nuclear Systems for Low-Carbon Energy Production, IRESNE, CEA Cadarache), where you will benefit from an open environment rich in academic collaborations. You also have to manage collaborations for the experiments analysis, for the model development and for the specification of additional atomistic calculations. You will be at the interface of atomistic techniques, large-scale simulation and various experimental techniques. Therefore, You will develop a broad view of irradiation effects in materials and of multi-scale modelling in solids in general.
This project is an opportunity to contribute to the overall development of numerical physics applied to multi-scale modeling of materials, occupying a pivotal position and adopting a global viewpoint. This will allow experiencing yourself the way computed fundamental microscopic data finally helps solving complex practical issues.
Further readings:
Skorek et al. (2012). Modelling Fission Gas Bubble Distribution in UO2. Defect and Diffusion Forum, 323–325, 209.
Bertolus et al. (2015). Linking atomic and mesoscopic scales for the modelling of the transport properties of uranium dioxide under irradiation. Journal of Nuclear Materials, 462, 475–495.
Assisted generation of complex computational kernels in solid mechanics
The behavior laws used in numerical simulations describe the physical characteristics of simulated materials. As our understanding of these materials evolves, the complexity of these laws increases. Integrating these laws is a critical step for the performance and robustness of scientific computations. Therefore, this step can lead to intrusive and complex developments in the code.
Many digital platforms, such as FEniCS, FireDrake, FreeFEM, and Comsol, offer Just-In-Time (JIT) code generation techniques to handle various physics. This JIT approach significantly reduces the time required to implement new simulations, providing great versatility to the user. Additionally, it allows for optimization specific to the cases being treated and facilitates porting to various architectures (CPU or GPU). Finally, this approach hides implementation details; any changes in these details are invisible to the user and absorbed by the code generation layer.
However, these techniques are generally limited to the assembly steps of the linear systems to be solved and do not include the crucial step of integrating behavior laws.
Inspired by the successful experience of the open-source project mgis.fenics [1], this thesis aims to develop a Just-In-Time code generation solution dedicated to the next-generation structural mechanics code Manta [2], developed by CEA. The objective is to enable strong coupling with behavior laws generated by MFront [3], thereby improving the flexibility, performance, and robustness of numerical simulations.
The selected PhD candidate should have a solid background in computational science and a strong interest in numerical simulation and C++ programming. They should be capable of working independently and demonstrate initiative. The doctoral student will benefit from guidance from the developers of MFront and Manta (CEA), as well as the developers of the A-Set code (a collaboration between Mines-Paris Tech, Onera, and Safran). This collaboration within a multidisciplinary team will provide a stimulating and enriching environment for the candidate.
Furthermore, the thesis work will be enhanced by the opportunity to participate in conferences and publish articles in peer-reviewed scientific journals, offering national and international visibility to the thesis results.
The PhD will take place at CEA Cadarache, in south-eastern France, in the Nuclear Fuel Studies Department of the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE)[4]. The host laboratory is the LMPC, whose role is to contribute to the development of the physical components of the PLEIADES digital platform [5], co-developed by CEA and EDF.
[1] https://thelfer.github.io/mgis/web/mgis_fenics.html
[2] MANTA : un code HPC généraliste pour la simulation de problèmes complexes en mécanique. https://hal.science/hal-03688160
[3] https://thelfer.github.io/tfel/web/index.html
[4] https://www.cea.fr/energies/iresne/Pages/Accueil.aspx
[5] PLEIADES: A numerical framework dedicated to the multiphysics and multiscale nuclear fuel behavior simulation https://www.sciencedirect.com/science/article/pii/S0306454924002408
Turbulence synthetization methods in porous media from detailed simulations for multi-scale simulations of nuclear cores
The production of electricity through nuclear energy plays a crucial role in the energy transition due to its low carbon impact. To continuously improve safety and performance, it is essential to develop new knowledge and tools.
The core of a nuclear reactor consists of thousands of fuel rods traversed by a turbulent flow. This flow can cause vibrations, leading to wear. Two flow scales are identified: a local scale, where the fluid interacts with the rods, and a global scale, representing the flow distribution within the core. The local scale requires CFD simulations and fluid-structure coupling, while the global scale can be modeled using averaged approaches, such as porous media simulations.
Coupled fluid-structure interaction (FSI) simulations at the CFD scale are limited to small domains. To overcome this limitation, multi-scale approaches are required, combining large-scale porous media simulations and detailed small-scale CFD simulations. The goal of the thesis is to develop methods for synthesizing turbulence from the results of porous media simulations to improve boundary conditions for CFD simulations. The candidate will first study how existing turbulence models can provide details on turbulent flow at the component scale, and then how to synthesize turbulence for local CFD simulations.
This PhD project is the subject of a collaboration between the IRESNE Institute (CEA) and the ASNR (main execution site of the thesis) in Cadarache. Funding is provided by a MSCA Doctoral Network. The PhD student will be integrated into a network of 17 PhD students. To be eligible, the candidate must have resided no more than 12 months in the last 36 months in France.
Electrical characterization and optimization of III-V HBT on Si for 6G and datacom applications
As digital content demand surges, 6G systems face major challenges, particularly in developing power amplifiers for Sub-THz frequencies. These frequencies promise ultra-high data rates but push the limits of current silicon technology. In AI datacenters, optical communication between GPUs is a must to reduce the total energy usage, compared to classical wiring. The highest speed devices are then needed in photodetectors & lasers’ electrical drivers. InP-based Heterojunction Bipolar Transistors (HBTs) on large silicon substrates offer a promising solution, combining high-speed performance with minimal system losses. This technology comes with the challenges of integrating III-V layers with CMOS-compatible processes while allowing promising new device architectures, for both electrical parasitics reduction and self-heating management.
This PhD program aims to guide Leti’s III-V HBT on Si developments to optimize the device architecture and increase the RF performance.
In this program the student will:
Perform electrical characterization of various device geometries and technological splits through DC and RF measurements such as IV, thermal analysis, S-parameters and possibly Load-Pull.
Simulate key parasitics and new device architectures to understand device limitations
Collaborate closely with process engineers to link electrical results with fabrication choices and guide device optimization
CORTEX: Container Orchestration for Real-Time, Embedded/edge, miXed-critical applications
This PhD proposal will develop a container orchestration scheme for real-time applications, deployed on a continuum of heterogeneous computing resources in the embedded-edge-cloud space, with a specific focus on applications that require real-time guarantees.
Applications, from autonomous vehicles, environment monitoring, or industrial automation, applications traditionally require high predictability with real-time guarantees, but they increasingly ask for more runtime flexibility as well as a minimization of their overall environmental footprint.
For these applications, a novel adaptive runtime strategy is required that can optimize dynamically at runtime the deployment of software payloads on hardware nodes, with a mixed-critical objective that combines real-time guarantees with the minimization of the environmental footprint.
Real-time measurement of edge plasma parameters for the optimization of the WEST tokamak performance
The control of heat fluxes at the plasma edge, and particularly in the divertor — a dedicated volume where these fluxes are focused — is a major challenge in research on magnetic confinement fusion. In future devices, heat fluxes will need to be dissipated by radiation to reduce the heat conducted to the divertor. However, the operational window for these high-radiation regimes is quite narrow and requires precise control of the edge plasma. The PhD first objective is to develop a real-time measurement of the density and temperature profiles at the plasma edge from the Thomson scattering diagnostics. By leveraging a large experimental database and simulations performed with edge plasma modeling tools and plasma/wall interaction models, the student will then develop meta-models to create a real-time control algorithm for WEST scenarios, particularly for high radiation discharges. This development will rely on continuous iteration between simulations, experimental observations, and real-time control performance requirements. This thesis is part of a collaborative framework involving French universities and international collaborations, with a high level of expected scientific visibility.
Development of Zinc Sodium-ion batteries for stationary storage of renewable energy
In the global context of massive renewable energy deployment, production and storage are becoming increasingly intertwined. Battery electrochemical energy storage systems (BESS) are currently experiencing strong market growth. These systems differ radically from electric mobility solutions due to their specific characteristics (cost, safety, durability). Faced with the limitations of Li-ion batteries (fire risks, the criticality of lithium and cobalt, production costs), aqueous zinc/sodium-ion technology presents a disruptive alternative. Based on abundant, non-toxic, and inherently safe materials, it offers unique potential for long-term storage with a low environmental impact. The zinc battery sector faces scientific challenges that limit reversibility and cycle life, notably the formation of zinc dendrites and cathode instability. This doctoral thesis project proposes to overcome these obstacles through a research and development strategy for innovative electrodes based on the reversible transformation of zinc into zinc phosphate in an aqueous sodium phosphate medium. This choice of electrolyte allows the use of sodium-ion positive electrodes as well as AGM (absorptive glass mat) separators, developed notably for lead-acid batteries.
The thesis work will focus on experimental electrochemical studies combined with multiphysics modeling of the system at the cell scale, taking into account the thermodynamics and kinetics of the included reactions. This approach will allow for the rapid exploration of a vast design space to identify the conditions enabling scaling up and transfer to industry, meeting the imperatives of energy sovereignty and the circular economy.
Physics-Informed Learning for Acoustic Inverse Problems: Field Reconstruction, Detection, and Detectability Analysis in Complex Environments
This PhD project aims to develop a mathematical and algorithmic framework for solving acoustic inverse problems in complex environments, based on physics-informed learning. By explicitly incorporating the wave equation into artificial intelligence architectures, the objective is to improve acoustic field reconstruction from partial measurements, the localization of mobile sources, and the quantitative analysis of their detectability. The project combines partial differential equation modeling, constrained optimization, and hybrid deep learning. Applications include distributed acoustic sensing systems and the detection of mobile platforms.
Integration of security functions for imagers: encryption, watermarking using compact functions close to the sensor
Illicit uses of images have dramatically risen with deepfake content manipulation or unauthorized access. Securing images at their source i.e., at the image sensor level, is key to addressing the challenges of this field of cybersecurity. The "trusted imagers" concept addresses the need to ensure image security, authentication, and encryption starting at the point of acquisition.
Building on our initial research, notably regarding the in-situ generation of keys, your PhD thesis will focus on finding innovative solutions to integrate security functions into image sensors with the challenge of meeting the requirements of low power consumption and compact integrated architecture, while keeping a high level of security. After an initial phase aiming at the development of the skills specific to the thesis, and depending on your background and interests, your work will involve:
- Developing encryption and/or watermarking algorithms in Python to evaluate their complexity, then proposing compact versions compatible with integration into image sensors.
- Evaluating the impact of algorithmic choices and hardware implementation on image quality.
- Designing and validating hardware architectures that implement the algorithms.
- Designing the integrated circuits implementing these functions.
With the ultimate goal of fabricating an integrated circuit, the work will be conducted at CEA-Leti, using professional IC design tools and software development environments.