Control of Electro-Magnetic Pulse on the LMJ-PETAL Laser Facility
The Mégajoule Laser (LMJ) is a large-scale research instrument designed to heat and compress matter to conditions similar to those found in nuclear weapon operation or at the core of stars. The LMJ (a nanosecond-scale megajoule-class laser) is primarily used for defense applications, supporting the safety and reliability guarantee of France's nuclear deterrent. Since its coupling with the high-power PETAL laser (a picosecond-scale kilojoule-class laser), the LMJ has also been made available to the international scientific community for academic research. Experiments conducted with these two lasers can generate extremely high electromagnetic fields, potentially causing malfunctions in the facility's equipment.
This post-doctoral position is part of a collaboration between teams from CEA/CESTA and CELIA (a joint research unit of the University of Bordeaux, CNRS, and CEA), as well as other European laboratories.
A 3D multi-scale simulation chain has been developed to assess the amplitude, duration, and spectral content of the Electromagnetic Pulse (EMP). To mitigate EMP intensity, a new target holder (EMP mitigation device) has been designed. The electromagnetic environment of the facility is also monitored using specialized diagnostics, including a new device for measuring target discharge current.
The ongoing PETAL Upgrade project aims to enhance PETAL's performance. Additionally, the final LMJ laser chains are currently being commissioned, and the total laser energy will significantly increase in the coming years. Furthermore, new laser target technologies will soon be tested. These developments are likely to increase EMP levels on the facility. Therefore, a precise evaluation of this increase and improved reliability of the EMP mitigation device are essential.
Bimodal RMN and optical glycemia measurments in brain rodents
Nuclear Magnetic Resonance (NMR) spectroscopy of deuterium and oxygen 17, combined with the injection of enriched glucose (2H-Glc or 17O-Glc), are promising approaches to quantify cerebral glucose fluxes in vivo. Despite the low sensitivity of these nuclei, isotopic enrichment provides high specificity to the measurements. However, the absolute quantification of glucose flux requires knowledge of the blood concentration of marked glucose, classically evaluated by blood sampling, an approach incompatible in small animals.
Diffuse Reflectance Spectroscopy (DRS) is a non-invasive optical technique that involves illuminating a diffusing medium in the infrared and measuring the spectrum of the backscattered light. This spectrum depends on the absorption and scattering properties of the medium, related to the concentration and optical characteristics of the chromophores present. Spectral analysis of the signal allows the concentration of chemical species to be determined.
To achieve absolute knowledge of glucose flux, we propose to combine NMR spectroscopy with a second modality, known as spectroscopy in a diffusing medium.
Modelling the black-mass leaching process for battery recycling and optimisation of process parameters using the Cast3M simulation tool
By 2030, Europe will have to manage 3000 kilotonnes of end-of-life lithium-ion batteries, rich in critical metals. Recycling, now necessary, is divided into three main steps: dismantling, material concentration, and hydrometallurgy. The latter, costly step, includes leaching, impurity removal, and element separation. The variability of the incoming material influences the leaching mechanisms, generating additional costs. A digital tool to predict and adjust the optimal leaching parameters would meet the needs of recyclers. LITEN/LRTE is working on battery recycling and has studied the physico-chemical mechanisms of leaching. ISEC/LSPS has developed NOMADECast3M, a digital tool for modeling particle dissolution. The goal is to collaborate between ISEC and LITEN to qualify a leaching kinetics model. The following steps include the acquisition and structuring of experimental data, the calibration of the model parameters, the validation of the model, and the identification of optimal process conditions. Then, the work will be reproduced on different types of BM to validate the robustness of the model.
Thermodynamic approach for the development of eco-designed glasses with low environmental impact
Within the context of the energy transition and the decarbonization of the glass industry, the ThermoGreen_GLASS project aims to create a sustainable glass supply chain featuring eco-designed, and high-value products for the glass industry. These glasses are produced from recycled, alternative, bio-based, or geosourced raw materials (glass cullet, foundry sand, glass fibers, oyster shells, etc.).
Within the context of the energy transition and the decarbonization of the glass industry, the ThermoGreen_GLASS project aims to create a sustainable glass supply chain featuring eco-designed, and high-value products for the glass industry. These glasses are produced from recycled, alternative, bio-based, or geosourced raw materials (glass cullet, foundry sand, glass fibers, oyster shells, etc.).
The main objective is to develop a systemic approach and a robust thermodynamic methodology that will enable:
- Predicting and quantifying the energy efficiency associated with the production of eco-designed glass compared to conventional methods.
- To guarantee the quality of the glass and equivalent properties (composition, homogeneity, performance).
- To optimize the composition of secondary precursors (energy balance, cost, and environmental impact) by ultimately feeding data into a decision-support tool or machine-learning model.
Study of a low-cost K-ion storage system: CAM synthesis, electrolyte, safety and prototyping
The UPBEAT project (France 2030) aims to develop a low-cost potassium-ion technology that is free of critical materials and capable of providing the performance of LiFePO4-type Li-ion cells. The work proposed to the post-doc is in line with this objective: after having optimized the upscaled synthesis of the positive electrode active material, it will involve developing optimized organic liquid electrolytes for this new system (Prussian White vs. Graphite), by studying the most promising salts, solvents, and additives, while maintaining the objectives of cost and durability. The proposed solutions (with and without fluorine) will be formulated, characterized, and electrochemically tested in complete cells (coin cells and pouch cells, including component optimizations) to measure their effectiveness in terms of lifetime and power response. Operando measurements and post-mortem characterizations will be used to understand the effects of the various components. The systems that best meet the project's requirements will also be subjected to abuse tests to assess the safety of the final system.
Data Mining and Accelerated Characterization for Understanding Oxidation in Duplex Layers
The FOCACCYA project, conducted over two years by an interdisciplinary consortium (CEA, Institut Clément Ader), aims to understand and prevent the formation of duplex oxide layers, which are critical for material corrosion in industrial environments such as nuclear reactors. It combines bibliographic and experimental data mining, statistical analysis, and advanced characterization experiments to identify the key parameters of this phenomenon. The results will be integrated into a database to model corrosion mechanisms and improve material protection. The recruited candidate, on a two-year post-doctoral contract, will be responsible for setting up the database and exploiting it using numerical methods (statistics, ML, and AI).
Development of Silicon-Perovskite Tandem Solar Cells for Space Applications (M/F)
With record efficiencies now exceeding 35%, silicon-perovskite tandem solar cells are generating a growing interest in the field of photovoltaic. For space applications, their low manufacturing cost compared to the III-V solar cells typically used is particularly appealing.
Conventional silicon-based cells are especially vulnerable to the irradiations encountered in space. Recently, a "self-recovery" solution was demonstrated by a team at the DTS: thin (90 µm) silicon heterojunction (SHJ) photovoltaic cells were shown to self-regenerate after electron beam irradiation within a few hours under conditions representative of the space environment.
The post-doctoral researcher will be based at the DTS on the INES site (Bourget-du-Lac). The goal of this post-doctoral position is to fabricate Silicon-Perovskite tandem cells using these "space-fit" SHJ cells. Primarily in a cleanroom environment, you will carry out all the fabrication steps for the perovskite top cell. You will characterize the fabricated tandems and propose improvements for one or both of the subcells. Tests to assess resistance to the space environment will be scheduled to evaluate the devices' resistance to irradiation (electrons/protons) and rapid thermal cycling.
European standardization of corrosion experiments in molten chlorides
Molten Salt Reactors represent a promising lead for Gen-IV nuclear reactors wit inherent safety features and the possibility to reuse the spent fuels of PWR. Two halides are envisioned for this concept, namely fluorides and chlorides salts. Their choice is justified either by their thermo-physical properties or by their compatibility with the already-existing infrastructures.
Despite their numerous advantages, halides salts -and more specifically chlorides and fluorides- are highly hygroscopic leading to a very aggressive impurity-driven corrosion of the structural materials. In order to investigate both the mechanism of this phenomenon and its kinetics, corrosion studies are carried out worldwide at the lab scale. Due to the plurality of experimental procedures and equipment, the literature is rich but the published data are usually scattered and therefore not usable to compare the corrosion behaviour of materials across different facilities.
The ENHARMONY project aims at providing guidelines for salt purification and corrosion testing in order to standardize corrosion experiment in molten halides. To do so, the corrosion behavior of two materials (stainless steel and nickel-based alloy) in either molten fluorides or molten chlorides will be investigated in several european laboratories following the same experimental procedures and aiming at having a good reproducibility.
Instrumentation and Physics-Informed 3D Reconstruction for Quantum Magnetic Diagnosis of Li-ion Batteries
The OPTIMAQ project of the CEA aims to reduce the reject rate in Li-ion cell formation — currently up to 50%, with a target of 5% — through a non-invasive quantum magnetic measurement system. This post-doctoral position covers both the software and experimental strands of the project: setting up the measurement bench (helium-4 optically pumped magnetometer, shielding, cell translation system) and developing a physics-informed 3D current density reconstruction algorithm (RBF-FD/PINN) to detect defects as early as the formation stage.
Hosted at CEA-LETI in Grenoble within the LSSC laboratory (sensor signal processing, reconstruction), in close collaboration with the L2EP/LAIC laboratories (battery system instrumentation, quantum magnetometry) at CEA-LETI and the LAPS/LMPS laboratories (Li-ion electrochemistry: experimental implementation and testing, modeling and simulation) at CEA-LITEN, this position is part of a 24-month project targeting TRL 3, with prospects for publications and patents.
Artificial Intelligence for Rapid Source Term Estimation (AIFORSTE)
The AIFORSTE project of the CEA aims to improve emergency management for atmospheric releases resulting from industrial accidents or malicious acts. We will develop a source estimation method operating in near real-time, enabling a fast and effective response to these critical events where time is always a fundamental constraint.
Given the impossibility of using detailed CFD simulations for immediate intervention, and the inaccuracy of simplified analytical models, this postdoctoral position will be devoted to a hybrid approach based on Physics-Informed Artificial Intelligence.
The core of the work will consist in designing and optimizing deep neural network architectures combining PINNs (Physics-Informed Neural Networks) and Neural Operators (FNO, DeepONet). The objective will be to quasi-instantaneously evaluate the position, intensity, and kinetics of one or several unknown release sources from a limited number of noisy measurements, while respecting the physical conservation laws.
Hosted at CEA-Leti (Grenoble) and co-supervised by CEA-DAM, the project will apply to realistic case studies (urban districts, industrial sites) using data generated through high-fidelity simulation. This 18-month project offers a unique opportunity to publish in leading journals and to help build strategic technological autonomy in a field where security and environmental monitoring are of major importance.