Combinatory synthesis of Spinels as Barriers to Hydrogen entry in Steels
The oxide layer that forms naturally on steel acts as a ‘natural’ barrier to the ingress or desorption of hydrogen: for the storage and transport of H2, this barrier effect is beneficial as it reduces the risk of hydrogen embrittlement of the underlying metal; for electrolysers, it would help to reduce line losses due to permeation (leakage) through the pipes by limiting desorption; in nuclear fusion applications, they would form a radiological barrier for tritium. However, the values of the parameters {diffusion; solubility; permeability} for hydrogen in the numerous possible oxide compositions and structures—which are necessary to quantify this barrier effect—are virtually non-existent in the literature. The main objective of the thesis will be to rapidly generate a reliable database covering a large number of iron oxide compositions and microstructures. The PhD student will combine rapid synthesis and screening methods (combinatorial synthesis of iron-based oxides with varying structures and compositions using HiPIMS, in situ monitoring and AI-driven optimisation, to be further developed) with techniques for local characterisation of hydrogen distribution (SIMS, nanoSIMS) via the use of isotopic tracers (deuterium) following gaseous exposure in a home-built apparatus. Concentration profiles will be processed using a routine developed (in Python) by the PhD student taking into account the composition and microstructure duality of the oxide layers. The expected final outcome would be a ‘3D’ mapping of hydrogen transport parameters in {Fe, O, Metal1, Metal2} quaternary systems, incorporating the concept of oxide microstructure. This approach could be applied to other systems, or even directed towards the search for optimised coating compositions.
Simulation Methods for Compressible Flows Using Staggered Discretization Methods
Thermal-hydraulic codes require robust and accurate numerical methods capable of handling multiphase flows over a wide range of Mach numbers. In this context, staggered-grid methods provide a particularly attractive framework. This PhD thesis builds upon recent work carried out as part of a previous PhD project, which led to the development of a new method with promising theoretical and numerical properties. The objective is to pursue this work and extend its range of applications. The first part will focus on the theoretical analysis of the explicit version of the scheme applied to the drift-flux model, in order to establish its conservation properties, its behaviour in the low-Mach-number limit, and the convergence of the numerical solutions. The method will then be extended to the Baer-Nunziato two-phase flow model, in which the two phases have distinct velocities and pressures. Finally, high-order reconstruction techniques will be investigated to improve the accuracy of the scheme by reducing numerical dissipation. The expected outcomes are a better mathematical understanding of these schemes and the development of robust and accurate numerical methods suitable for industrial applications. These methods will first be validated in a C++ and Python research code, and then implemented and assessed within the open-source TRUST platform dedicated to high-performance thermal-hydraulic simulations.
Investigation of Degradation Modes of PV Modules for Medium Voltage Applications
To reduce energy losses and costs, photovoltaic power plants have seen their voltage levels increase, which should exceed the standard 1500 Vdc to reach up to 3000 Vdc soon. Even higher voltages, up to 9000 V, could offer very significant economic advantages.
The increase in voltage presents major scientific challenges. High voltages result in degradations grouped under the term Potential-Induced Degradation (PID), leading to significant power losses. These degradations can have several origins: a short circuit of the PN junction (PID-s), depolarization of the solar cell passivation layer (PID-p), or corrosion of the metallization (PID-c). The understanding of PID phenomena at medium voltage remains limited, and there is a lack of comprehensive studies on module materials, the interaction between PID and aging, and the behavior of PID in advanced cell technologies.
The proposed thesis aims to identify the material properties necessary for PV modules to withstand high voltages, combining experimental and simulation approaches.
The doctoral student will need to characterize PV materials (glass, encapsulants) under voltages up to 9000 V, evaluate the impact of aging on the properties of these materials, study the influence of environmental conditions on PID, model the electric field distribution in PV modules, and develop PID mitigation strategies. This research will be conducted in collaboration between G2Elab and CEA, combining expertise in material characterization under medium voltage and photovoltaic module manufacturing.
New Reliable Strategies for Optimizing Predictive Thermodynamics Models
Predictive thermodynamic models, developed by the Calphad method, are essential for designing new materials by anticipating their behavior without resorting to costly and time-consuming experiments. These models allow for the extrapolation of the properties of complex materials, predicting their behavior in extreme environments, and linking energy properties to in-service performance. However, current methods for developing these models are complex, and uncertainties are not quantified in existing software. Scientists still rely on their expertise to adjust and validate these models, which is time-consuming and poorly suited to the era of automation.
To address this, it is proposed to develop a reliable, autonomous, and fast digital tool capable of optimizing thermodynamic models based solely on experimental data provided by users. The goal is to provide simple, reliable, validated, and modular models, enabling users to make strategic decisions with confidence, such as evaluating new process conditions or optimizing manufacturing without risking uncertain extrapolations. This project aims to bridge the gap between specific experimental data and modern nonlinear programming methods, using advanced optimization approaches.
Investigation of Very High Cycle Fatigue Behavior of 13-4 Martensitic Stainless Steel Manufactured by Laser Metal Deposition: Influence of Microstructure, Post-treatments and Temperature Project
Recent research on 13-4 martensitic stainless steel manufactured by metal additive manufacturing, particularly using the Laser Metal Deposition (LMD) process, has made it possible to obtain materials with good mechanical properties. Following this optimization phase, current work is now focused on studying their Very High Cycle Fatigue (VHCF) behavior, which is a critical criterion for components subjected to repeated loading under severe operating conditions.
Fatigue is one of the main causes of failure in metallic components during service. This thesis therefore aims to understand and model the fatigue behavior of LMD-produced 13-4 steel. The work will investigate the influence of microstructure, thermomechanical treatments, and testing conditions on crack initiation and propagation during mechanical loading.
Experimental investigations will be carried out using ultrasonic fatigue testing devices. Failure mechanisms will be analyzed through multi-scale characterization techniques such as EBSD, SEM, and TEM. The final objective is to develop a predictive model capable of estimating the service life of components under operating conditions.
Understanding microstructural changes during heat treatment of iron-rich SmCo magnets
The magnetic properties of SmCo magnets (remanence and coercivity) are linked to their microstructure. The final microstructure develops after sintering during homogenization and ageing heat treatments. The optimum temperature and/or duration of these treatments depend on the magnet’s composition. One of the major areas of development for commercial Sm2Co17 magnets is to achieve both high magnetic performance and a reduction in critical materials (notably cobalt). This is achieved by substituting part of the Co with Fe, which also helps to reduce raw material costs. However, the literature shows that when the Fe content exceeds 20% by weight, the coercivity of the magnets is diminished.
The aim of the thesis will be to understand the role and sensitivity of the process parameters that govern the evolution of the microstructure within Fe-rich Sm2Co17 magnets and the resulting properties. These developments will be monitored through various characterization techniques (chemical analyses, magnetic measurements, SEM and TEM observations, etc.) carried out on samples taken at different stages of the process. The aim is to systematically monitor (for the first time for this type of magnet) the structural transformations (chemical segregation, changes in Sm content, presence of defects, oxygen contamination, etc.) that occur from the synthesis of the alloy through to the final magnet. These characterizations should lead to a description of the mechanisms underlying the formation of the expected microstructure. These mechanisms are activated during the various heat treatments, but the influence of the metallurgical and chemical state (for example, defect density and chemical inhomogeneity) inherited from previous stages of the process is still poorly understood and will need to be clarified.
Growth of FAPbBr3 by CSS for X-ray detection
Lead halide perovskites, and particularly hybrid organic-inorganic materials based on formamidinium, possess exceptional optoelectronic properties that have been intensively exploited for photovoltaic (PV) applications. Within this family of materials, FAPbBr3 is also particularly promising for X-ray detection in medical applications. However, this technology requires the ability to deposit thick layers (>100 µm) over large areas. CEA-LITEN has developed an innovative approach for depositing inorganic perovskites using close-space sublimation (CSS), which meets these criteria. Very recently, it has been shown that it is possible to deposit FAPbBr3 using this method, marking a world first.
However, the growth mechanisms of FAPbBr3 and hybrid perovskites via CSS are largely misunderstood, and the possibilities offered by this deposition method are yet to be fully explored. Furthermore, these results are also extremely promising for PV applications, as similar growth is expected by substituting Br to form FAPbI3.
This thesis aims to (i) determine and optimize the growth conditions via CSS for FAPbBr3 layers, (ii) understand the growth mechanisms of FAPbBr3 through advanced characterizations (in-situ and ex-situ), and (iii) optimize devices for X-ray detection. The extension of this work to FAPbI3 for PV applications is also anticipated. The novelty of this approach and the potential to address multiple applications offer prospects for publications and patents.
Toward Robust Earthquake Location and Uncertainty Quantification in Dense Seismic Networks: Methodological Developments and Application to Cephalonia Island (Western Greece) and the Middle Durance region (France)
This PhD project aims to develop a robust methodological framework for earthquake location and realistic uncertainty quantification in the context of dense seismic networks. Despite recent advances in automatic detection, deep-learning-based phase picking, and earthquake relocation techniques, uncertainties related to velocity models and network geometry remain a major limitation and are often underestimated by conventional approaches. The project will compare and benchmark different detection, picking, and location methodologies in order to assess their respective strengths and limitations. Particular emphasis will be placed on identifying, quantifying, and disentangling the main sources of uncertainty, including phase picking errors, network configuration, and velocity model assumptions. The research will primarily rely on data from Cephalonia Island (Greece). In a second phase, the developed methodologies will be transferred to the Middle Durance region near Cadarache (France), allowing their applicability to lower-seismicity environments to be assessed. The expected outcomes include improved seismic catalogs, a better understanding of active tectonic processes.
Development of durable and flexible KNN piezoelectric materials: toward an alternative to lead-based ceramics and fluorinated polymers
The project aims to develop lead-free and PFAS-free (perfluoroalkyl and polyfluoroalkyl substances) piezoelectric thin films based on potassium sodium niobate (KNN) that are compatible with flexible substrates, in direct response to the growing regulatory and environmental constraints affecting conventional piezoelectric materials. PZT ceramics (lead titanate-zirconate) and PVDF polymers (polyvinylidene fluoride), which currently dominate the market, have significant limitations related to lead toxicity and the environmental persistence of PFAS, respectively. In this context, identifying sustainable and integrable alternative materials is a strategic priority for the CEA, particularly for flexible electronics applied to medical, embedded, and sustainable devices.
KNNs are among the most promising alternatives due to their high piezoelectric properties and high Curie temperature. However, their integration in the form of thin films remains severely limited by crystallization temperatures exceeding 600 °C, which are incompatible with polymer substrates. The project’s objective is to overcome this barrier by developing an innovative sol-gel combustion deposition process, enabling localized or global crystallization at low temperatures (<350 °C), compatible with flexible substrates. Beyond the KNN system, this approach could constitute
Characterisation of the physico-chemical properties of solid residues from biomass hydrothermal carbonisation
Hydrothermal carbonisation (HTC) is a thermochemical conversion process performed in pressurized water (2-6 MPa) between 180 and 260°C. The main product is a carbonaceous solid residue (hydrochar). Various applications are foreseen for hydrochar: combustion, gasification, adsorption, catalysis, soils amendment, hard carbon for Na-ion batteries, …, each of them requiring specific properties.
The objective of the thesis is to characterise and better understand the origin of several physico-chemical properties of biomass hydrochars. A special attention will be paid to hydrophobicity and drying capacity, to physical and textural characteristics of the particles (porosity, granulometry, specific surface), as well as to chemical characteristics (composition). The influence of biomass type and HTC conditions on these properties will be investigated.
The approach will consist in: experimentations in batch reactors on pre-selected biomass resources, together with use of different characterisation techniques for hydrochars; analysis of results aiming at determining links between the characteristics, elucidating the links between the resource and its hydrochar properties as a function of operational conditions.