Self-healing of radiation-induced defects in silicon solar cells for space
Over the last decades, the development of alternative space photovoltaic (PV) solutions to the III-V premium standard has shifted the focus to silicon solar cells. Indeed, leveraging on existing maturity of terrestrial PV silicon devices and processes offers significant potential for innovation and cost reduction. Many satellites nowadays evolve in Low Earth Orbit, a proton and electron rich environment. Such irradiations induce electrically active defects in the material which affect the PV performances. Interestingly, some of the irradiation-induced defects can be healed upon external factors such as temperature and/or photons flux.
The main goals of this PhD thesis will be to i) understand the bulk & interface electron/proton irradiation-induced degradation mechanisms driving the evolution of the optoelectronic properties of silicon passivated contacts solar cells ii) develop a comprehensive understanding of the self-healing effects in irradiated modern silicon solar cells through experimental studies and modeling iii) identify design / fabrication process routes to control & boost the self-healing capability.
To reach these goals, this PhD work will go through defined steps: bibliography review, solar cells fabrication, material/device ageing under proton & electron irradiations, advanced characterizations and modeling. This PhD work will be conducted at CEA/Liten, on the INES campus (Le Bourget du Lac, FR) with frequent interactions with CNES (Toulouse, FR) facilities.
Enhancing Faradaic Efficiency in Protonic Ceramic Electrolysis Cells (PCCELs) through Electrolyte and Electrode–Electrolyte Interface Engineering
Proton conducting ceramic electrolysis cells (PCCELs), an advanced variant of solid oxide electrolysis cells (SOECs), enable the direct production of hydrogen through steam electrolysis using proton-conducting electrolytes. Unlike conventional SOECs, which rely on oxygen ion (O²?) conductors, PCCELs operate at lower temperatures (~400–600?°C vs. 750–850?°C for SOECs) due to their higher proton conductivity. This lower operating temperature helps reduce material degradation and overall system costs. While SOEC technology has reached industrial maturity, with large-scale deployment projects underway, the development of PCCELs remains limited by several scientific challenges. These include the difficulty of densifying electrolytes (such as BaCeO3–BaZrO3) without barium volatilization during high-temperature sintering; the proton transport limitations posed by grain boundaries; and the poor control of electrode–electrolyte interfaces. This thesis aims to improve the faradaic efficiency of PCCELs by optimizing the microstructure of the electrolyte and engineering high-quality interfaces through targeted surface treatments. The methodology includes cell fabrication, interface engineering, and electrochemical evaluation. The ultimate goal is to establish robust and scalable processing protocols that enable PCCELs to achieve faradaic efficiencies above 95%, compatible with industrial-scale deployment.
Controlling the composition and microstructure to achieve high magnetic performance in 1–12 rare earth-poor magnets
Permanent magnets based on rare earth elements (REEs), particularly neodymium-iron-boron (Nd-Fe-B) magnets, are strategically important for the development of more efficient motors and generators (electric vehicles, wind turbines). However, REEs, particularly Nd, are critical materials, with a high risk of supply disruption in the coming years. The growing demand for high-performance magnets requires the development of new types of magnets with reduce RE content. Iron-rich compounds, such as Sm-Fe12 (commonly known as phase 1-12), have very interesting intrinsic magnetic properties and are considered the best alternative to NdFeB magnets, allowing for a TR saving of around 35% by weight. However, achieving sufficient magnetic performance (remanence > 1 T and coercivity > 800 kA/m) depends on obtaining a suitable microstructure and remains the main challenge in the development of Sm-Fe12 magnets.
The aim of the thesis is therefore to improve the magnetic performance of this new family of magnets, in particular by controlling the composition and distribution of phases at grain boundaries. The doctoral work will combine an advanced experimental approach (development of Sm-Fe12 alloys, characterization of equilibrium phases, magnet manufacturing, magnetic characterization) with knowledge of phase diagrams to define compositions and optimal manufacturing conditions to achieve the targeted magnetic performances.
Potential synergy between NH3 and NaBH4 for improved H2 density and enhanced safety
The thesis focuses on the study of the hybrid ammonia–sodium borohydride system (NH3–NaBH4) as an innovative chemical energy carrier. The objective is to investigate the combination of ammonia (NH3), recognised for its high hydrogen density and mature industrial infrastructure, with sodium borohydride (NaBH4), a high-capacity chemical hydrogen storage material, in order to overcome certain limitations associated with each vector when considered separately.
The proposed work specifically addresses the safer storage and transport of ammonia through its coupling with sodium borohydride, enabling a reduction in vapour pressure (compared to 8.88 bar at 21 °C for liquid ammonia) and less restrictive operating conditions. In parallel, the thesis aims to improve the stability (relative to the H2O–NaBH4 system) and operability of sodium borohydride which, when combined with ammonia molecules (acting as inert species), forms stable liquid or viscous phases that are potentially pumpable, thereby facilitating integration into energy-related processes.
The fundamental goal of the thesis is to understand the physicochemical mechanisms governing this hybrid system, particularly the role of dihydrogen interactions between the N–H bonds of ammonia and the B–H bonds of borohydride, and their influence on stability, reactivity, transport properties, and hydrogen release pathways (thermal and/or hydrolytic).
Beyond its storage function, the thesis also explores the potential of the NH3–NaBH4 system as a novel hybrid material with high gravimetric and volumetric hydrogen capacity, while considering realistic operational constraints relevant to energy applications in a dual-use context. At this stage, exhaustive optimisation is not the primary objective.
Intelligent control and optimization of DC microgrids using digital twins in real-time simulation
This thesis addresses the challenge of decarbonizing industrial and territorial systems by proposing a transition to direct current (DC) microgrids controlled by a Digital Twin. Faced with the saturation of alternating current (AC) grids due to the growth of photovoltaics, energy storage, and electric mobility, DC allows for a reduction in conversion losses (5 to 15%), improved flexibility, and a simplification of the electrical architecture.
The project is based on the development of a high-fidelity Digital Twin synchronized in real-time simulation. More than just a monitoring tool, it acts as a proactive decision-making system integrating advanced optimization algorithms, such as artificial intelligence and predictive control. It anticipates voltage instabilities, which are particularly critical in low-inertia DC grids, and continuously optimizes power flows to maximize self-consumption while preserving battery life.
Experimental validation relies on a Hardware-in-the-Loop approach within the CEA-Liten/G2Elab ecosystem, integrating physical converters. This methodology guarantees robustness, security, and resilience before any real-world deployment.
The expected outcomes are scientific (stability and real-time modeling), operational (provision of technical guides and decision-making tools), and strategic (strengthening French technological sovereignty in Smart Grids and accelerating the 2050 carbon neutrality trajectory advocated by ADEME).
High-throughput screening of catalysts for the direct conversion of CO2 into synthetic fuels
This doctoral project aims to develop an innovative high-throughput screening approach for catalysts for the direct conversion of CO2 into synthetic fuels, known as CO2-FTS. This approach will combine a catalyst screening platform with in situ/operando characterization techniques and artificial intelligence methods to accelerate the discovery and optimization of high-performance catalysts. It aims to identify doped FeOx-type catalysts for the CO2-FTS reaction (>50% conversion, high selectivity towards C8-C16). Several high-throughput screening campaigns will allow for iterative optimization of compositions and reactive conditions. A numerical model of the parametric landscape will then be developed. This model will subsequently be coupled with multi-scale modeling from the active site to the reactor level. The developed catalysts will contribute to the energy transition by enabling a circular carbon economy.
Li alloys for all solid-state batteries with sulfide electrolyte
Using lithium metal as a negative electrode would significantly increase the energy density of current batteries. However, today, this material quickly leads to short circuits during charge/discharge cycles, mainly due to the formation of dendrites and the instability of the interface with the electrolyte. All-solid-state batteries, particularly with sulfide electrolytes, are a promising alternative, but the limitations of lithium metal remain. Lithium alloys appear to be a solution for improving mechanical and interfacial properties while maintaining good energy densities.
The objective of the PhD is to develop and select lithium alloys suitable for sulfide electrolytes batteries, then integrate them into all-solid-state cells in order to study degradation mechanisms. The work will be focused on the synthesis of the alloys, their shaping in thin films and their integration into cells. The alloys will be finely characterized and then electrochemically tested in laboratory cells and pouch cells. Finally, degradation phenomena, particularly at interfaces, will be studied using advanced post-mortem characterizations.
Hybrid CPU-GPU Preconditioning Strategies for Exascale Finite Element Simulations
Exascale supercomputers are based on heterogeneous architectures that combine CPUs and GPUs, making it necessary to redesign numerical algorithms to fully exploit all available resources. In large-scale finite element simulations, the solution of linear systems using iterative solvers and algebraic multigrid (AMG) preconditioners remains a major performance bottleneck.
The objective of this PhD is to study and develop hybrid preconditioning strategies adapted to such heterogeneous systems. The work will investigate how multilevel and AMG techniques can be structured to efficiently use both CPUs and GPUs, without restricting computations to a single type of processor. Particular attention will be paid to data distribution, task placement, and CPU–GPU interactions within multilevel solvers.
From a numerical point of view, the research will focus on the analysis and construction of multilevel operators, including grid hierarchies, intergrid transfer operators, and smoothing procedures on avalible GPU's and CPU's. The impact of these choices on convergence, spectral properties, and robustness of preconditioned iterative methods will be studied. Mathematical criteria guiding the design of efficient hybrid preconditioners will be investigated and validated on representative finite element problems, e.g., regional-scale earthquake analysis.
These developments will be coupled with domain decomposition and parallelization strategies adapted to heterogeneous architectures. Particular attention will be paid to CPU–GPU data transfers, memory usage, and the balance between compute-bound and memory-bound kernels. The interaction between numerical choices and hardware constraints, such as CPU and GPU memory hierarchies, will be designed and developed to ensure scalable and efficient implementations.
Control & optimization of fuel cell temperature
Proton exchange membrane fuel cells (PEMFC) represent a key technology for the development of clean and sustainable energy systems, particularly for heavy-duty transport applications where their energy density is very attractive. However, in order to represent a viable industrial alternative, a number of obstacles still need to be overcome, including operating costs and, above all, the durability of the systems under real-world conditions. Among the levers for action, optimizing operating conditions is a promising avenue for limiting the degradation phenomena occurring within the cell. The operating temperature is a particularly key parameter because it affects all aspects of the system, from the kinetics of degradation mechanisms to the thermal capacity that the system can dissipate, including the water balance within the fuel cell. Despite the influence of this parameter on durability, it is generally only optimized at the system level to achieve the best performance, the shortest possible response time and to limit the size of the thermal management system.
The aim of this thesis is to work on optimizing the temperature management of a fuel cell within a system, taking into account not only performance but also sustainability criteria. To do this, the impact of operating temperature on degradation mechanisms will be analyzed using various simulation tools already available at LITEN and the teams' fifteen years of experience in studying PEMFC fuel cell degradation. Various thermal architectures will be proposed and evaluated in conjunction with the work on temperature control optimization. The latter will be implemented on a real fuel cell system in order to demonstrate the relevance of the proposed solution using concrete experimental data.
Development of a new numerical scheme, based on T-coercivity, for discretizing the Navier-Stokes equations.
In the TrioCFD code, the discretization of the Navier-Stokes equations leads to a three-step algorithm (see Chorin'67, Temam'68): velocity prediction, pressure solution, velocity correction. If an implicit time discretization scheme is to be used, the pressure solution step is particularly costly. Thus, most simulations are performed using an explicit time scheme, for which the time step depends on the mesh size, which can be very restrictive. We would like to develop an implicit time discretization scheme using a stabilized formulation of the Navier-Stokes problem based on explicit T-coercivity (see Ciarlet-Jamelot'25). It would then be possible to solve an implicit scheme directly without a correction step, which could significantly improve the performance of the calculations. This would also allow the use of the P1-P0 finite element pair, which is frugal in terms of degrees of freedom but unstable for a classical formulation.