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In a context where material durability is essential for the safety of infrastructures and the promotion of a sustainable energy transition, mastering corrosion phenomena represents a major challenge for key sectors such as decarbonized energy transport through buried pipelines and civil engineering (hydrogen, nuclear, underground infrastructures). The CORPORE project addresses this issue by proposing the development of advanced numerical simulation models to study corrosion in porous media using COMSOL Multiphysics.
The main scientific and technological objective is to establish an integrated multiphysics modeling approach for the electrochemical and transport mechanisms within porous materials: studying the coupled influence of chemistry, pore network properties, and material–environment interactions on the initiation and propagation of corrosion.
This approach will help optimize anticorrosion protection strategies, reduce maintenance costs, and extend the service life of structures. From a state-of-the-art perspective, most current models focus on homogeneous media and compartmentalized approaches. Our project stands out by integrating a multi-scale mechanistic modeling framework combined with the use of archaeological data for long-term validation.
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Management of low- and medium-level nuclear waste relies primarily on cements, but their limitations with regard to certain types of waste (reactive metals, oil) require the exploration of new, more effective materials. Geopolymers, particularly those composed of hydrated sodium aluminosilicates (Na2O–Al2O3–SiO2–H2O, or N–A–S–H), appear to be a promising alternative thanks to their chemical compatibility with certain types of waste.
However, despite the growing interest in geopolymers, scientific obstacles remain: 1) The available thermodynamic data on N-A-S-H is still incomplete, making it difficult to predict their long-term stability via modeling, 2) The role of their atomic structure in regard to their reactivity remains unclear, and 3) The links between chemical composition (in terms of Si/Al ratio) and mechanical properties are not established, limiting the representativeness of the models created.
By combining experimentation and modeling in order to link atomic structure and properties, this thesis aims to obtain robust and novel data on the chemical and mechanical properties of N-A-S-H. The thesis is organized around three major objectives: 1) determining the impact of N-A-S-H composition on dissolution and establishing thermodynamic solubility constants, 2) characterizing their atomic structure (aluminols, silanols, and hydrated environments) using advanced NMR spectroscopy, and 3) linking their mechanical properties, measured by nanoindentation, to their structure and composition using molecular dynamics modeling.
Materials used in nuclear energy production systems are subjected to mechanical, thermal, and irradiation condition, leading to a progressive evolution of their mechanical properties. Understanding and modeling the underlying physical mechanisms involved is a significant challenge.
Dislocation Dynamics simulation aims to understand the behavior of the material at the crystal scale by explicitly simulating the interactions between dislocations, microstructure, and crystal defects induced by irradiation. The CEA, CNRS, and INRIA have been developing the NUMODIS calculation code for this purpose since 2007 (Etcheverry 2015, Blanchard 2017, Durocher 2018).
More specific work on zirconium alloys (Drouet 2014, Gaumé 2017, Noirot 2025) has allowed the validation and enhancement of NUMODIS's ability to handle these individual physical mechanisms by directly comparing them with experiments, through in situ tensile tests under a transmission electron microscope. However, these studies are limited by the current inability of the NUMODIS code to handle a sufficiently high and representative number of defects, and thus to obtain the mechanical behavior of the grain (~10 microns).
The objective of the proposed work is to implement new algorithms to extend the functionalities of the code, propose and test new numerical algorithms, parallelize certain parts still processed sequentially, and ultimately demonstrate the code's ability to simulate the deformation channeling mechanism in an irradiated zirconium grain.
The work will focus primarily on algorithms for calculating velocities, junction formation, and time integration, requiring both mastery of dislocation physics and the corresponding numerical methods. Algorithms for integration recently proposed by Stanford University and LLNL will be implemented and tested for this purpose.
Significant work will also be devoted to adapting the current code (hybrid MPI-OpenMP parallelism) to new computing machines that favor GPU processors, through the adoption of the Kokkos programming model.
Building on both previous experimental and numerical work, this study will conclude with the demonstration of NUMODIS's ability to simulate the channeling mechanism in an irradiated zirconium grain and to identify or even model the main physical and mechanical parameters involved.
At the interface between several fields, the candidate must have a good foundation in physics and/or mechanics, while being comfortable with programming and numerical analysis.
References:
1. Etcheverry Arnaud, Simulation de la dynamique des dislocations à très grande échelle, Université Bordeaux I (2015).
2. Blanchard, Pierre, Algorithmes hiérarchiques rapides pour l’approximation de rang faible des matrices, applications à la physique des matériaux, la géostatistique et l’analyse de données, Université Bordeaux I (2017).
3. Durocher, Arnaud, Simulations massives de dynamique des dislocations : fiabilité et performances sur architectures parallèles et distribuées (2018).
4. Drouet, Julie, Étude expérimentale et modélisation numérique du comportement plastique
des alliages de zirconium sous et après irradiation (2014).
5. Gaumé, Marine, Étude des mécanismes de déformation des alliages de zirconium
après et sous irradiation (2017).
6. Noirot, Pascal, Etude expérimentale et simulation numérique, à l'échelle nanométrique et en temps réel, des mécanismes de déformation des alliages de zirconium après irradiation (2025).
Metal alloys used in industrial applications most often have a ductile fracture mode involving nucleation, growth, and coalescence of internal cavities. The cavities appear as a result of the rupture of inclusions and grow under mechanical loading until they join together, leading to the failure of the structure. Resistance to crack initiation and propagation results from this mechanism. The prediction of toughness therefore requires the modeling of the plasticity of porous materials. The behavior of porous materials has been extensively studied from an experimental, theoretical, and numerical point of view in the case of monotonic mechanical loading under large deformations, leading to constitutive equations that can be used to simulate ductile fracture of structures. The case of cyclic mechanical loading and / or involving low levels of deformation / low number of cycles has been comparatively little studied, even though this type of loading is of interest in industrial applications, for example in the case of earthquakes. In this thesis, the effect of oligocyclic loading on ductile fracture properties will be investigated systematically from an experimental, theoretical, and
numerical point of view. Test campaigns will be carried out on various materials used in nuclear applications and under different mechanical stress conditions in order to quantify the effect of oligocyclic loading on fracture deformation and toughness. At the same time, numerical simulations will be performed to obtain an extensive database on the plastic behavior of porous materials under cyclic loading, with a particular focus on the effects of elasticity, porosity, mechanical loading, and spatial distribution of cavities. These numerical simulations will be used to validate analytical models developed during the thesis to predict the evolution of porosity and yield stress. Finally, the models will be implemented in the form of constitutive equations and used to simulate experimental tests.
The mechanical behavior of metallic materials under highly dynamical loading (schock) and especially their damage behavior is a topic of interest for the CEA-DAM. For tantalum, damage is ductile : by nucleation, growth and coalescence of voids within the material. Usual ductile damage models have been developed using the simplifying assumption that voids are isolated in the materials. However, recent studies by direct simulations explicitly describing a void population in the material (and experimental observations after failure) have shown the importance of void interaction for predicting ductile damage. Yet, the microscopical mechanisms of this interaction remain little known.
The objective of the PhD is to study the growth and coalescence phases of ductile damage through direct numerical simulations of a porous material undergoing dynamic loading. Hydrodynamic simulations, in which voids are explicitly meshed within a continuous matrix, will be used to study relevant scales of length and time. Monitoring the void population throughout the simulation will provide valuable information on the influence of void interaction during ductile damage. Firstly, the bulk behavior will be compared to the one predicted by usual models of isolated voids, showing the macroscopic effect of void interaction. Secondly, the evolution of the size distribution in the void population will be monitored. The last objective will be to understand microscopic void-to-void interaction. In order to take advantage of the wealth of simulation results, approaches based on artificial intelligence (neural networks on the graph associated with the pore population) will be used to learn the link between a void's neighborhood and its growth.
The doctoral student will have the opportunity to develop their skills in shock physics and mechanics, numerical simulations (with access to CEA-DAM supercomputers), and data science.
Controlling the behavior of fission gases in nuclear fuel (uranium oxide) is an important industrial issue, as fission gas release or precipitation limit the use of fuels at extended burn-ups. The gas behavior is strongly influenced by the material’s microstructure evolution due to the aggregation of irradiation-induced defects (gas bubbles, dislocation loops and lines). Cluster dynamics (CD) (a kind of rate theory model) is relevant for modelling the nucleation/growth of the defect clusters, there gas content and the gas release. The current model has been parameterized following a multiscale approach, based on atomistic calculations (ab initio or empirical potentials). This model has been successfully applied to annealing experiments of UO2 samples implanted with rare gas atoms and has emphasized the impact of the irradiation damage on gas release. The aim of this PhD thesis is now to improve the model, particularly the damage parameterization, and to extend its validation domain through in depth comparison of simulation with a large set of recently obtained experimental results, such as gas release measurement by annealing of sample implanted in ion beam accelerator, bubble and loop observation by transmission electrons microscopy of implanted or in-pile irradiated samples. This global analysis will finally yield an improved parameterization of the CD model.
The research subject combines a “theoretical” dimension (improving the model) with an “experimental” one (interpreting existing experiments or designing some new ones). The variety of techniques will introduce you into the experimental world and thus broaden your scientific skills. You will be welcomed at the Fuel Behavior Modeling Laboratory (part of the Institute for Research on Nuclear Systems for Low-Carbon Energy Production, IRESNE, CEA Cadarache), where you will benefit from an open environment rich in academic collaborations. You also have to manage collaborations for the experiments analysis, for the model development and for the specification of additional atomistic calculations. You will be at the interface of atomistic techniques, large-scale simulation and various experimental techniques. Therefore, You will develop a broad view of irradiation effects in materials and of multi-scale modelling in solids in general.
This project is an opportunity to contribute to the overall development of numerical physics applied to multi-scale modeling of materials, occupying a pivotal position and adopting a global viewpoint. This will allow experiencing yourself the way computed fundamental microscopic data finally helps solving complex practical issues.
Further readings:
Skorek et al. (2012). Modelling Fission Gas Bubble Distribution in UO2. Defect and Diffusion Forum, 323–325, 209.
Bertolus et al. (2015). Linking atomic and mesoscopic scales for the modelling of the transport properties of uranium dioxide under irradiation. Journal of Nuclear Materials, 462, 475–495.
This PhD project focuses on developing nuclear fuels with improved properties through the addition of a dopant, for use in pressurized water reactors.
In nuclear reactors, the fuel consists of uranium dioxide (UO2) pellets stacked inside zirconium alloy cladding. These pellets, in contact with the cladding, must withstand extreme conditions of temperature and pressure. One of the challenges is to limit chemical interactions that may occur during the migration of fission products from the center to the periphery of the pellet and with the cladding. A notable example of such a phenomenon is the stress corrosion assisted by iodine, which can occur during accidental transients.
One strategy is to dope the UO2 ceramic with a metal oxide in order to control the material’s microstructure and also to modify its thermochemical behavior, thereby limiting both the mobility and corrosive nature of fission gases. Among the possible dopants, manganese oxide (MnO) represents a promising option and a potential alternative to chromium oxide (Cr2O3), which is currently a mature solution for the industry.
This PhD will explore the role of manganese in the sintering of UO2, particularly the microstructure and final properties of the fuel. The work will take place at the CEA Cadarache center, within the Institute for research on nuclear systems for low-carbon energy production (IRESNE).
During these three years, you will be hosted in the Laboratory for the study of uranium-based fuels (LCU) within the fuel study department (DEC), in close connection with the Laboratory for fuel behavior modeling (LM2C).
This research, combining experimentation and modeling, will be structured around three main topics:
• Study of the influence of manufacturing conditions on the microstructure of Mn-doped UO2,
• Investigation of the impact of doping on defect formation in UO2 and the associated properties,
• the contribution to the thermodynamic modelling of the system, based on experimental tests.
During this PhD, you will gain solid experience in the fabrication and advanced characterization of innovative materials, particularly in the field of ceramics for the nuclear industry. Your work could lead to publications, patents, and participation in national and international conferences.
You will also acquire numerous technical skills applicable across various research and industrial fields, including energy, microelectronics, chemical and pharmaceutical industries.
Uranium – molybdenum alloys UMo present excellent thermal properties and a good uranium density. For those reasons, they are considered as nuclear fuel candidates for research reactors. It is therefore crucial for the CEA to deploy new computational methodologies in order to investigate the evolution of their thermo-physical properties under irradiation conditions.
This project is centered on the application of atomistic methods in order to investigate the stability and diffusion of intra-granular xenon clusters within the metallic nuclear fuel UMo.
The first step of your work will involve continuing the development of atomic-scale computational models for UMo, as initiated within the host laboratory. These models use machine learning methods to develop interatomic potentials and will be validated by comparison with existing experimental data for this material. They will then be used to assess the temperature-dependent evolution and the impact of defect accumulation (both point and extended defects) on several thermophysical properties critical to fuel modeling, such as elastic properties, density, thermal expansion, as well as thermal properties like specific heat and thermal conductivity. In collaboration with other researchers in the department, you will format these results for integration into the Scientific Computing Tools used to simulate the behavior of nuclear fuels.
In a second phase, you will be responsible for extending the validity of your models to account for the formation of fission gases such as xenon within UMo single crystals. This will enable you to simulate the stability of xenon clusters in UMo crystals. These calculations, performed using classical molecular dynamics methods, will be systematically compared with experimental observations obtained via transmission electron microscopy.
The results obtained during the various stages of this project will be completely innovative and will be the subject of scientific publications as well as presentations at international scientific conferences. Besides, this work will enable you to complement your training by acquiring skills applicable to many areas of materials science, including ab initio calculations, machine learning-based interatomic potential fitting, classical molecular dynamics, use of CEA supercomputers, and key concepts in statistical physics and condensed matter physics—fields in which the supervising team members are recognized experts.
You will join the Fuel Behavior Modeling Laboratory at the Research Institute for Nuclear Systems for Low-Carbon Energy Production (IRESNE, CEA Cadarache), a dynamic research team where you will have regular opportunities to interact with fellow PhD students and researchers. This environment also provides extensive opportunities for national and international collaboration, including with:
• Developers and users of the MAIA fuel performance code (dedicated to research reactor fuel studies),
• Experimental researchers from the Nuclear Fuel Studies Department,
• Teams from other CEA centers (Saclay, CEA/DAM),
• International partners.
This rich and multidisciplinary context will enable you to fully engage with the scientific community focused on nuclear materials science.
[1] Dubois, E. T., Tranchida, J., Bouchet, J., & Maillet, J. B. (2024). Atomistic simulations of nuclear fuel UO2 with machine learning interatomic potentials. Physical Review Materials, 8(2), 025402.
[2] Chaney, D., Castellano, A., Bosak, A., Bouchet, J., Bottin, F., Dorado, B., ... & Lander, G. H. (2021). Tuneable correlated disorder in alloys. Physical Review Materials, 5(3), 035004.
This PhD thesis is part of the optimization of nuclear fuel fabrication processes, which rely on the powder metallurgy of uranium dioxide (UO2) and plutonium dioxide (PuO2). These powders exhibit a hierarchical microstructure composed of crystallites forming rigid aggregates, themselves agglomerated into larger structures. The morphology and interactions between aggregates play a key role in the macroscopic behavior of the powders—particularly their flowability, compressibility, and agglomeration capacity—and directly influence the quality of the fuel pellets obtained after pressing and sintering. However, the experimental characterization of these aggregates remains complex and does not yet allow for the establishment of a predictive link between synthesis processes and morphological properties.
The objective of this thesis is to combine experimental and numerical approaches to achieve a detailed characterization of the aggregates in a reference powder. Experimentally, techniques such as Scanning Electron Microscopy (SEM), specific surface area measurement (BET), and laser granulometry will be used to determine particle size, roughness, and size distribution. In parallel, numerical simulations based on the Discrete Element Method (DEM) will be employed to construct a granular digital twin consistent with the experimentally measured properties. This digital twin will allow the reconstruction of the internal structure of the aggregates, the evaluation of interparticle adhesion forces, and the analysis of agglomeration and densification phenomena under controlled conditions.
The PhD will take place at CEA Cadarache within the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE). The student will be assigned to the PLEIADES Fuel Development Laboratory (LDOP), which specializes in simulating nuclear fuel behavior (from fabrication to in-reactor performance) and in multi-scale numerical methods. The work will be carried out in collaboration with the CNRS/LMGC in Montpellier, internationally recognized for its research on granular materials, and with the Uranium Fuel Laboratory (LCU – CEA Cadarache), which has extensive experience in the experimental characterization of uranium powders.
The PhD candidate is expected to demonstrate strong skills in numerical simulation and in the physical analysis of results. He will share its results through publications and conference presentations and will have the opportunity to learn or further develop various experimental and numerical techniques that can be applied in other contexts.In particular, the issues related to the physics of granular media — which constitute the core of this PhD — are of significant industrial relevance and are common to many other sectors handling powders, such as pharmaceuticals, agri-food, and powder metallurgy.
[Hebrard2004] S.Hebrard, Etude des mécanismes d’évolution morphologique de la structure des poudres d’UO2 en voie sèche, thèse de doctorat, CEA-LSG2M-COGEMA), 2004.
[Pizette2010] P. Pizette, C.L. Martin a, G. Delette, P. Sornay, F. Sans, Compaction of aggregated ceramic powders: From contact laws to fracture and yield surfaces, Powder Technology, 198, 240-250, 2010.
[Tran2025] T.-D. Tran , S. Nezamabadi , J.-P. Bayle, L. Amarsid, F. Radjai , Effect of interlocking on the compressive strength of agglomerates composed of cohesive nonconvex particles, Advanced Powder Technology 36, 2025.