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.
Incremental Generation of Polycubes Driven by Geometric Quality
The proposed work consists of designing and developing a new algorithm for generating block-structured hexahedral meshes using a “Polycube”-typed strategy. Usually, these methods deform a geometric domain G to be discretized into a polycube P, i.e. a polyhedron whose all the faces are orthogonal to one of the X, Y, or Z axes. This polyhedron can be easily discretized using a hexahedral mesh, which is then transformed via the inverse deformation to pave G.
Unlike traditional approaches, which are based on constructing the deformation function, we focus on the inverse function by treating the pair (geometry G, polycube P) as input. Our goal is to compute the inverse function F that transforms P into G, and, depending on some local properties of F, modify P to provide a “better” mesh of G from a geometric point of view.
Generation of Curved Hexahedral-Dominant Block Structures Using Median Objects
The automatic generation of block-structured hexahedral meshes is a challenging problem, solved in practice through the use of dedicated interactive software, such as Magix3D, which is developed and maintained at CEA DAM. Using such software, a specialist engineer may spend several days creating the expected mesh.
The objective of this thesis is to help such an engineer to quickly sketch initial block structures with a hexahedral-dominant structure by relying on the medial object of the 3D geometric domain to be discretized. When considering CAD-type geometric domains, represented by their boundary, the medial object provides volumetric information intrinsic to the domains, which will guide the engineer in creating individual hexahedral blocks.
The objective of this thesis is twofold: first, to propose an efficient method for generating 3D medial objects; and second, to develop an algorithm and an associated interactive tool for creating predominantly hexahedral block structures.
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.
Towards Efficient and Authenticated Private Set Intersection in Multi-Cloud Environments
Private Set Intersection (PSI) is a cryptographic protocol that allows two (or more) parties, each holding a set of items, to compute the intersection of their sets without revealing any items outside the intersection. That is, each party learns only which items they have in common, and nothing else about the other’s data. For example, two companies could collaborate to find out which customers they share without disclosing any customers that are unique to one company. PSI is a special case of secure multi-party computation focusing on set overlap; it has applications in private contact discovery, privacy-preserving data mining,..In this thesis, we study PSI improvements with fully holomorphic encryption.
In-situ Monitoring of RF Power Amplifier Circuits Aging for Eco-design and Extended Lifetime
The semiconductor industry, and more specifically the radio-frequency (RF) circuit sector, is facing critical challenges related to eco-design and eco-innovation. These challenges include the need to extend the lifetime of circuits while meeting the growing demands of emerging markets such as 5G and the future 6G. Among these circuits, power amplifiers (PA) play a central role, being both critical components in terms of energy efficiency and key targets for improving robustness against aging and enabling potential reuse.
In this context, in-situ aging monitoring of PAs appears to be a promising approach for developing innovative and sustainable solutions. This research topic is therefore fully aligned with eco-design strategies, leveraging advanced technological platforms such as current and future CMOS SOI technologies, while integrating industrial constraints through existing strategic collaborations with major partners of CEA Leti.
This thesis aims to design an innovative in-situ monitoring solution to evaluate and compensate for the aging of power amplifiers, thereby extending their lifetime through reuse and self-correction strategies. To achieve this, it will rely on methodologies and circuits specifically adapted to practical use cases. The ambition is thus to develop a new generation of robust and durable circuits, integrating intelligent aging management mechanisms. By adopting an eco-design approach, this work aims to address environmental challenges while enhancing the industrial competitiveness of CMOS SOI technologies.
Study of vibration effects on electrical cable diagnosis using reflectometry
This thesis focuses on the effect of vibrations on the diagnosis of electrical cables using reflectometry. Cable systems, which are present in many critical infrastructures such as aeronautics, railways, space systems, and nuclear facilities, are exposed to mechanical and environmental stresses that may lead to soft and intermittent faults. Under vibration, these faults may appear, disappear, or modify their electrical signature, making their detection particularly challenging.
One of the main challenges concerns No Fault Found situations, in which a fault observed during operation becomes non-reproducible once the vibration conditions disappear. Another important issue is the temporary masking of certain faults by vibrations, which may lead to false negatives during diagnosis and delay the detection of latent degradation.
The objective of this thesis is to better understand and model the electromechanical behavior of cable faults subjected to vibrational stress, in order to link vibration profiles, the mechanical and electrical evolution of the fault, and the signatures measured by reflectometry. The work will be based on experiments combining fast reflectometry and a high-speed camera, as well as on the development of models and analysis tools. Experimental and simulated data will then be used to improve the detection, characterization, and prediction of fault evolution, with a view to advanced diagnosis and predictive maintenance.
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.