Study of the corrosion behaviour of complex multi-element materials/coatings in H2SO4 and HNO3 environments
This thesis is part of the CROCUS (miCro laboRatory fOr antiCorrosion solUtion design) project. The aim of this project is to develop a micro-laboratory for in situ corrosion analysis that can be brought into line with processes for synthesising anti-corrosion materials or coatings
By testing a wide range of alloy compositions using AESEC (a technique providing access to elementally resolved electrochemistry), the project will provide a real opportunity to build up a corrosion database in different corrosive environments, whether natural or industrial, with varying compositions, concentrations, pH and temperatures.
The aim of the thesis will be to study the corrosion behaviour of promising multi-element complex materials/coatings using electrochemical techniques coupled with AESEC.
The first part of this work concerns the determination of the limits of use of these promising alloys as a function of the proton concentration in H2SO4 and HNO3 media for temperatures ranging from room temperature to 80°C. The passivity of these alloys as a function of acid concentration will be studied using electrochemical techniques (voltammetry, impedance, AESEC).
The presence of certain minor elements in the composition of these alloys, such as molybdenum, may have a beneficial effect on corrosion behaviour. To this end, the passivation mechanisms involved will be studied using model materials (Ni-Cr-Mo), electrochemical techniques (cyclic and/or linear voltammetry, impedance spectroscopy and AESEC) and surface analysis.
The second part deals with the transition between passivity and transpassivity, and in particular the occurrence or non-occurrence of intergranular corrosion (IGC) as a function of oxidising conditions (presence of oxidising ions). The aim will be to determine the different kinetics (comparison between grain and grain boundary corrosion rates), as well as to validate the models set up to study IGC in steels.
Finally, the student will participate in the development of a materials database for corrosion in aggressive environments, whether natural or industrial, with different compositions, concentrations, pH and temperatures, enabling the development of new generations of corrosion-resistant materials or coatings through the use of digital design and artificial intelligence optimisation tools.
Modeling and prediction of electromagnetic emissions from power converters using deep learning
In recent years, electromagnetic compatibility (EMC) in power converters based on wide bandgap (WBG) semiconductors has attracted growing interest, due to the high switching speeds and increased frequencies they enable. While these devices improve power density and system efficiency, they also generate more complex conducted and radiated emissions that are challenging to control. In this context, this thesis focuses on the prediction, modeling, and characterization of electromagnetic interference (EMI) (> 30 MHz), both conducted and radiated, in high-frequency power electronic systems. The work is based on a multi-subsystem partitioning method and an iterative co-simulation approach, combined with in situ characterization to capture non-ideal and nonlinear phenomena. In addition, deep learning techniques are employed to model EMI behavior using both measured and simulated data. Generative artificial intelligence (Generative AI) is also leveraged to automatically generate representative and diverse configurations commonly encountered in power electronics, thereby enabling efficient exploration of a wide range of EMI scenarios. This hybrid approach aims to enhance analysis accuracy while accelerating simulation and design phases.
Integrating social interactions between chiropterans and variations in prey abundance to understand the distribution of chiropterans
The feeding behaviour of animals is of vital importance for the physical condition of individuals and is strongly influenced by the transfer of inter-individual information and competition. The study of these cause-effect relationships is particularly difficult for elusive taxa such as bats, whose extremely diverse hunting behaviour and strategies introduce a new degree of complexity. Bats increase the efficiency of their foraging by being attentive to the information-carrying behaviour of other individuals; they then adapt their own behaviour either to avoid competition or to increase it. Previous studies on this phenomenon of listening among bats have produced very different and partly contradictory results, probably because they generally focused on a single species, differed considerably in the rate of eavesdropping and generally did not take account of the activity of conspecifics. Taking these social interactions into account now seems essential both to advance our ‘global’ understanding of how chiropterans integrate social information into their decision-making, to explain species distribution patterns and to elucidate the mechanisms by which species coexist. This understanding will help to provide answers in the field of conservation in relation to the increase in anthropogenic pressures, such as lighting and the fragmentation of environments. The aim of this thesis is to identify the pairs of species that are most subject to competition, in order to understand the causes and perceive the consequences at the scale of the landscape and anthropogenic pressures (light pollution). A second objective will be to characterise the feeding areas and to study the spatio-temporal rearrangement of the food resource - measured directly - over time, and its consequences for chiropterans and their interactions. A third objective will be to apply these concepts to a practical case of anthropogenic modification of natural balances and to model the effects (causal model). The case will be that of the effect of light pollution, and will enable clear hypotheses to be put forward on the effect of light pollution (most of the arthropod prey of chiropterans being attracted and concentrated under light sources) and its consequences on the competitive equilibrium in chiropterans.
Reducing the complexity of France's building stock to better anticipate anticipate energy demand flexibility and the integration of solar solar resources
The aim of this work is to respond to the current challenges of energy transition in the building sector, France's leading energy consumer. French public policies are currently proposing far-reaching solutions, such as support for energy-efficient home renovation and incentives for the installation of renewable energy production systems. On a large scale, this is leading to structural changes for both building managers and energy network operators. As a result, players in the sector need to review their energy consumption and carbon impact forecasts, integrating flexibility solutions adapted to the French standard. Some flexibility levers are already in place to meet the challenges of energy and greenhouse gas emission reduction, but others need to be anticipated, taking into account long-term scenarios for energy renovation and the deployment of renewable energy sources, particularly photovoltaic energy, across the whole of France. The issue of massification is therefore an underlying one. That's why this thesis proposes to implement a methodology for reducing the size of the French installed base based on previously defined criteria. In particular, the aim will be to define a limited number of reference buildings that are statistically representative of the behavior resulting from the application of flexibility strategies that meet the challenges of energy efficiency and limiting greenhouse gas emissions. To this end, the CSTB (Centre Scientifique et Technique du Bâtiment) is developing and making available a database of French buildings (BDNB: Base de Données Nationale des Bâtiments), containing information on morphology, uses, construction principles and energy consumption and performance.
Optimising the durability of high-temperature metal alloys: exploring new oxidation conditions
The aim of the OPTIMIST exploratory project is to increase the service life of metal alloys (alumina and chromia forming alloys) by forming a protective oxide layer, as is almost always the case to protect alloys from corrosion. The great originality of OPTIMIST will consist in forming an oxide layer with a minimum of 0D (point defects) and 2D (grain boundaries) structural defects. This objective will be based on two distinct strategies: the first will consist of forming a so-called endogenous oxide layer, i.e. by pre-oxidising the substrate by carefully choosing the pre-oxidation conditions (temperature, oxidising medium, oxygen partial pressure) in two types of Rhines Pack specifically developed at CEA/DES and IJL; the second will consist of forming a so-called exogenous oxide layer, i.e. created by a deposition technique: the HiPIMS recently commissioned at the CEA/INSTN. Different pre-oxidation conditions (for the endogenous layer) and process conditions (for the exogenous layer) will be investigated, then their 0D and 2D defects will be characterised at SIMaP using a novel combination of cutting-edge structural (TEM-ASTAR), chemical (atom probe, SIMS, nano-SIMS) and electronic (PEC PhotoelEctroChemistry) techniques. Finally, these characterised samples will be corroded in two environments (in air and in molten salts) at high temperatures to assess the effectiveness of the protection compared with conventional pre-oxidation. The stages of oxide growth, its stoichiometry and its microstructure (grain size and shape, nature of the grain boundaries) will thus be identified as a function of the endo and exogenous growth conditions so as to control them in order to achieve an oxide layer containing as few defects as possible.
Simplified Model for Rotary Tube Calcination
Since the vitrification lines at La Hague began operation in 1989, ORANO (formerly AREVA) has faced difficulties in controlling the calciner. Actions taken to significantly reduce these problems have considerably eased them, but without completely eliminating them. Most of the recommended actions are based on expert opinions, which themselves are based on inactive test results that don't cover all situations encountered by ORANO. To definitively resolve these control difficulties, it was decided to launch a more theoretical modeling study, while simultaneously investigating new calciner control instrumentation.
Optimization of transports in the Gas Diffusion Layers of Proton Exchange Membrane Fuel Cells: Artificial Intelligent as a support to define optimal porous structures and usage
The design and manufacturing of innovative materials with required properties is a key objective for developing advanced technologies in the field of energy, such as Hydrogen and Alcaline fuel cells and Electrolysers. These improvements will contribute to propose even more attractive low-carbon electrical energy systems, with reduced pollution and green-house effects.
This thesis focuses on the Gas Diffusion Layer (GDL) which plays a crucial role on the performance and durability of Proton Exchange Membrane Fuel Cell (PEMFC).
Your main aim will be to set-up a numerical approach so as to propose improved porous structures to optimize the different transports inside a GDL, for given targets and constraints. To do so, you will make the bridge between advanced modeling of (electrical, heat, liquid, gas) transports in 3D porous media and artificial intelligence. You will then analyze the influence of the operating conditions on such optimal structures and propose design recommendations.
This work will be conducted in close relationship between world-renowned scientific actors : the fuel cells and the modelling teams of CEA/LITEN (Grenoble), the specialists of transports in porous media at CNRS/IMFT (Toulouse), and the specialists of GDL, modeling and AI at FZJ (Juelich, https://www.fz-juelich.de/en).
Scientific publications are expected and patents could also be proposed.
Development of Single-Ion Eutectogel Electrolytes through Polymerization of Deep Eutectic Solvents (DES)
The proposed PhD thesis focuses on the development of innovative polymer electrolytes for next-generation batteries, aimed at improving the safety and performance of energy storage systems.
Polymer electrolytes represent a promising solution to replace traditional liquid electrolytes. However, their development is limited by challenges related to ionic conductivity and low ion transport numbers. The addition of Deep Eutectic Solvents (DES) into the polymer matrix enhances ionic conductivity. Furthermore, the "single-ion" approach, based on grafting the counter-ion onto the polymer chain, leads to unipolar conduction.
CEA has recently developed "single-ion eutectogel" electrolytes, obtained by polymerizing a DES composed of a single-ion monomer and a hydrogen bond donor (HBD). These electrolytes exhibit very promising performance, achieving unipolar ionic conductivities greater than 0.1 mS/cm at room temperature. However, it is essential to further explore the relationships between formulation, structure, and properties, as well as the conduction mechanisms within these materials, in order to continue their development.
The thesis will be structured in three main phases:
Study of the reference system: Establish a research methodology to link polymerizable formulations, polymer structure, and their electrochemical properties. This will include the study of the starting DES and the electrolyte resulting from its polymerization. The study of conduction mechanisms within these electrolytes will be a central focus of this phase.
Optimization of properties: Based on the results from the previous phase, optimize the properties of the electrolytes through formulation work to select the most promising electrolyte for the next phase.
Integration into a complete system: Explore the integration of the electrolyte into a battery cell, using the in situ polymerization process to synthesize the electrolyte directly within the cell.
Physicochemical techniques (NMR, DSC, TGA, FTIR, RAMAN, SEC, SAXS, ...) and electrochemical techniques (EIS, CV, GCPL, ...) will be used throughout the project.
The PhD will be carried out in collaboration with CEA and LEPMI, providing access to state-of-the-art infrastructures and recognized expertise in formulation, polymer chemistry, and polymer electrolyte electrochemistry.
Relationship between the nature of hard carbons and the properties of electrodes for Na-ion batteries
Hard carbons are the most commonly used negative electrode materials in Na-ion batteries. Their capacity exceeding 300 mAh/g, low operating voltage, long lifespan, and power performance make them the best option for commercializing Na-ion batteries. However, several challenges remain to approach the performance of low-impact Li-ion technologies like LF(M)P/graphite. One major limitation is their low volumetric density. Their disordered nature and resulting microporosity lead to a lower skeletal density compared to graphite. This significantly affects both the volumetric and gravimetric energy densities due to the difficulty of compressing the electrodes.
The main objective of this thesis is to establish a link between the material's skeletal density and the electrode's calendering capability to reduce its porosity. First, we will evaluate the relationship between the structure, morphology, and surface state of hard carbon and the electrode's density. We will attempt to understand the impact of calendering on the material’s properties. Then, we will assess the tortuosity and conductivity of hard carbon electrodes to predict their performance. Finally, we will work on improving and optimizing the electrodes in terms of energy densities, focusing particularly on electrode formulations.
Modelling/Simulation of the synthesis of anti-corrosion coatings using the MOCVD process for low-carbon energy production
The durability of materials used in many areas of energy production is limited by their degradation in the operating environment, which is often oxidising and at high temperature. This is particularly true of High Temperature Electrolysers (HTE) for the production of ‘green’ hydrogen, or the fuel cladding used in nuclear reactors to produce electricity. Anti-corrosion coatings can/should be applied to improve the lifespan of these installations, thereby conserving resources. A process for synthesising coatings using a reactive vapour route with liquid organometallic precursors (DLI - MOCVD) appears to be a very promising process.
The aim of this thesis is to model and simulate the DLI-MOCVD coating synthesis process for the two applications proposed above. Simulation results (deposition rate, deposit composition, spatial homogeneity) will be compared with experimental results from large-scale ‘pilot’ reactors at the CEA in order to optimise the model's input parameters. On the basis of this CFD simulation/experiments dialogue, the optimum conditions for deposition on a scale 1 component will be proposed. A coupling between CFD simulations and Machine Learning will be developed to accelerate the change of scale and the optimisation of scale 1 deposits.