Design and development of a modular high-side test bench for application validation of Grand Gap components
Wide bandgap transistors (GaN, SiC) play a key role in power electronics, but their industrial integration remains hampered by implementation difficulties. The high-side component, within a bridge arm structure, is particularly sensitive to voltage and current transients, which are highly dependent on routing, topology, and switching modes (ZVS, ZCS). Its floating nature makes measurements complex and can disrupt switching during application testing. A methodology adapted to fast transients was developed during a thesis, resulting in a patented test bench for characterizing low-side components. The subject of the postdoctoral research presented here aims to adapt this methodology to high-side components, which are more complex to drive and measure, in order to characterize and model aging due to gate transients under realistic conditions. The test bench will enable the generation of reproducible stress profiles on low-side and high-side components, and the precise measurement of key parameters such as threshold voltage and dynamic instabilities. To achieve these objectives, a new bench will be designed, incorporating specific control and measurement systems, with a view to application testing and targeted aging tests.
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Synthesis, Characterization, and Molecular Modeling of M-(A)-S-H
The main hydration product of Mg/silicate cements is magnesium silicate hydrate (M-S-H), whose composition evolves with time and environmental interactions [refs 1,2], with Mg/Si ratios ranging from 0.67 to 1.5, variable water content, and potential Al incorporation. Atomistic models of M-(A)-S-H remain largely unexplored [ref 4], and most of their properties are still unknown, making it difficult to establish composition–property relationships.
This project aims to elucidate the atomic-scale structure of (alumino)silicate magnesium hydrates (M-(A)-S-H) by combining experimental techniques and atomistic simulations, and to estimate their mechanical properties. The study will focus on M-(A)-S-H compositions relevant to nuclear applications or new low carbon cement matrices.
VALERIAN: caracterizing electron transport for the ITkPix modules of ATLAS
A precise description of the transport of electrons and photons in matter is crucial in several of the CEA's flagship fields, notably radiation protection and nuclear
instrumentation. Their validation requires dedicated parametric studies and measurements.Given the scarcity of public experimental data, comparisons between calculation codes are also used. The challenge for the coming years is to qualify these codes in a broad energy domain, as certain discrepancies between their results have been identified during preliminary SERMA studies involving the coupled transport of neutrons, photons and electrons. The VALERIAN project involves seizing the opportunity created by a unique data collection Campaign planned for 2025-2026 at the IRFU (DRF) to better characterise these discrepancies. The IRFU has undertaken to check at least 750 pixel modules for the new trajectograph of the ATLAS experiment, as part of the rejuvenation of the large detectors at CERN. Numerous measurements with beta sources will be carried out in 2025-2026 for the qualification of these modules.
Study of the Thermodiffusion of Small Polarons in UO2
The position is published on the CEA website at the following address:
https://www.emploi.cea.fr/job/emploi-post-doctorat-etude-en-ab-initio-de-la-thermodiffusion-des-petits-polarons-dans-UO2-h-f_36670.aspx
PV module designed for repair and recycle using ultrasonic delamination
PV panels, crucial for producing decarbonized electricity, have a limited lifespan due to performance degradation, failures, or economic factors. In the next decade, millions of tons of PV panels will become waste, posing significant environmental and societal challenges. Europe has recognized this problem through the WEEE directive (Waste Electrical and Electronic Equipment) to manage electronic waste, including PV.
PV modules are complex devices containing critical materials such as silver and long-life pollutants like fluorinated polymers. On top of that, the glass sheet and the silicon solar cells show a high carbon footprint, making the reuse essential to mitigate environmental impact. Various dismantling techniques have been explored in R&D labs to obtain pure fractions of metals, polymers and glass, but these methods require further improvement. Key objectives include selectivity and purity, material yield and control of residual pollution. To boost the sustainability of photovoltaic energy, managing module lifespans in a circular economy vision is essential.
The LITEN institute is leading research into delamination and separation methods to enhance the quality of recycled materials. In this postdoc opportunity, we will explore the implementation of ultrasonic waves for dismantling or repairing PV modules. The development of a numerical model to understand vibration phenomena in PV panels will support the design of a tool for efficient wave coupling. Beside modelling ant tool set-up, we will explore new PV architectures based on "design to recycle" and "design to repair" principles, focusing on composite layers sensitive to ultrasound. Evaluating various phenomena induced by these layers, such as optical transmission and thermo-mechanical behaviour, will be a key aspect of the study. The research will leverage a high-level scientific environment, with expertise in thermo-mechanical numerical modelling, PV module design and prototype’s fabrication.
Study of the Velocity-Vorticity-Pression formulation for discretising the Navier-Stokes equations.
The incompressible Navier-Stokes equations are among the most widely used models to describe the flow of a Newtonian fluid (i.e. a fluid whose viscosity is independent of the external forces applied to the fluid). These equations model the fluid's velocity field and pressure field. The first of the two equations is none other than Newton's law, while the second derives from the conservation of mass in the case of an incompressible fluid (the divergence of velocity vanishes). The numerical approximation of these equations is a real challenge because of their three-dimensional and unsteady nature, the vanishing divergence constraint and the non-linearity of the convection term. Various discretisation methods exist, but for most of them, the mass conservation equation is not satisfied exactly. An alternative is to introduce the vorticity of the fluid as an additional unknown, equal to the curl of the velocity. The Navier-Stokes equations are then rewritten with three equations. The post-doc involves studying this formulation from a theoretical and numerical point of view and proposing an efficient algorithm for solving it, in the TrioCFD code.
Development of a new generation of reversible polymer adhesives
Polymeric adhesives are generally cross-linked systems used to bond two substrates throughout the lifetime of an assembly, which may be multi-material, for a wide range of applications. At their end of life, the presence of adhesives makes it difficult to separate materials and recycle them. Moreover, it is difficult to destroy the cross-linking of the adhesives without chemical or thermal treatment that is also aggressive for the bonded substrates.
In this context, the CEA is developing adhesives with enhanced recyclability, by integrating recyclability into the chemical structures right from the synthesis of the polymer networks. The first approach involves incorporating dynamic covalent bonds into polymer networks, which can be exchanged under generally thermal stimulus (e.g. vitrimers). A second approach involves synthesising polymers that can be depolymerised under a specific stimulus (self-immolating polymers) and have the ability to cross-link.
The post-doc will develop 2 networks that can be used as adhesives with enhanced recyclability. A first network will be based on a depolymerizable chemistry under stimulus already developed on linear polymer chains, to be transposed to a network. A second vitrimer network will be synthesised on the basis of previous work at the CEA. Activation of the bond exchange in this network will take place via a so-called photolatent catalyst, which can be activated by UV and will make it possible to obtain a UV- and heat-stimulated adhesive. The choice and synthesis of these catalysts and their impact on the adhesive will be the focus of the study. The catalysts obtained could also be used to trigger depolymerisation of the first depolymerisable system under stimulus.
Impact of Microstructure in Uranium Dioxide on Ballistic and Electronic Damage
During reactor irradiation, nuclear fuel pellets undergo microstructural changes. Beyond 40 GWd/tU, a High Burnup Structure (HBS) appears at the pellet periphery, where initial grains (~10 µm) fragment into sub-grains (~0.2 µm). In the pellet center, under high temperatures, weakly misoriented sub-grains also form. These changes result from energy loss by fission products, leading to defects such as dislocations and cavities. To study grain size effects on irradiation damage, nanostructured UO2 samples will be synthesized at JRC-K, using flash sintering for high-density pellets. Ion irradiation experiments will follow at JANNuS-Saclay and GSI, with structural characterizations via Raman spectroscopy, TEM, SEM-EBSD, and XRD. The postdoc project will take place at JRC-K, CEA Saclay, and CEA Cadarache under expert supervision.
High-performance computing using CMOS technology at cryogenic temperature
Advances in materials, transistor architectures, and lithography technologies have enabled exponential growth in the performance and energy efficiency of integrated circuits. New research directions, including operation at cryogenic temperatures, could lead to further progress. Cryogenic electronics, essential for manipulating qubits at very low temperatures, is rapidly developing. Processors operating at 4.2 K using 1.4 zJ per operation have been proposed, based on superconducting electronics. Another approach involves creating very fast sequential processors using specific technologies and low temperatures, reducing energy dissipation but requiring cooling. At low temperatures, the performance of advanced CMOS transistors increases, allowing operation at lower voltages and higher operating frequencies. This could improve the sequential efficiency of computers and simplify the parallelization of software code. However, materials and component architectures need to be rethought to maximize the benefits of low temperatures. The post-doctoral project aims to determine whether cryogenic temperatures offer sufficient performance gains for CMOS or should be viewed as a catalyst for new high-performance computing technologies. The goal is particularly to assess the increase in processing speed with conventional silicon components at low temperatures, integrating measurements and simulations.
Design and Implementation of a Neural Network for Thermo-Mechanical Simulation in Additive Manufacturing
The WAAM (Wire Arc Additive Manufacturing) process is a metal additive manufacturing method that allows for the production of large parts with a high deposition rate. However, this process results in highly stressed and deformed parts, making it complex to predict their geometric and mechanical characteristics. Thermomechanical modeling is crucial for predicting these deformations, but it requires significant computational resources and long calculation times. The NEUROWAAM project aims to develop a precise and fast thermomechanical numerical model using neural networks to predict the physical phenomena of the WAAM process. An internship in 2025 will provide a database through thermomechanical simulations using the CAST3M software. The post-doc's objective is to develop a neural network architecture capable of learning the relationship between the manufacturing configuration and the thermomechanical characteristics of the parts. Manufacturing tests on the CEA's PRISMA platform will be conducted to validate the model and prepare a feedback loop. The CEA List's Interactive Simulation Laboratory will contribute its expertise in accelerating simulations through neural networks and active learning to reduce training time.