Topological magnons in quantum materials
Topology has become an essential paradigm in condensed matter, making it possible to classify phases of matter according to properties that are invariant under continuous deformations. Early research has mainly focused on electronic band structures, leading to the discovery of “topological insulators” for example. However, there is growing interest in applying topological concepts to bosons, in particular magnons. Magnons, which are collective excitations in magnetic materials, illustrate how topology influences magnetic dynamics and affects heat and spin transport. Analogues of topological insulators and semi-metals appear in their band structures. Magnons thus offer a platform for studying the interplay between magnetic symmetries and topology, examining the effect of interactions on topological bands, and generating protected spin currents at interfaces. The search for materials containing topological magnons is therefore crucial, especially for applications in magnonics, which exploit spin waves for fast data storage and processing.
This thesis project is dedicated to exploring these topological aspects in candidate quantum materials using neutron and X-ray scattering techniques in large scale facilities (ILL, ESRF, SOLEIL) to probe the magnon band structure in search of topological features such as Dirac or Weyl points. Experimental results will be supported by numerical and theoretical calculations of magnonic bands incorporating topological concepts.
Strain field imaging in semiconductors: from materials to devices
This subject addresses the visualization and quantification of deformation fields in semiconductor materials, using synchrotron radiation techniques. The control of the deformation is fundamental to optimize the electronic transport, mechanical and thermal properties.
In a dual technique approach we will combine the determination of the local deviatoric strain tensor by scanning the sample under a polychromatic nano beam (µLaue) and a monochromatic full field imaging with a larger beam (dark field x ray microscopy, DFXM).
New developments of the analysis will be focused on 1/ the improvement of the accuracy and speed of the quantitative strain field determination, 2/ the analysis of strain gradient distributions in the materials, and 3/ the determination of the dynamic strain field in piezoelectric materials through stroboscopic measurements. To illustrate these points, three scientific cases corresponding to relevant microelectronic materials of increasing complexity will be studied:
1- Static strain fields surrounding metallic contacts, such as high-density through silicon vias (TSV) in CMOS technology.
2- Strain gradients in Ge/GeSn complex heteroepitaxial structures with compositional variations along the growth direction.
3- Dynamical strain in LiNbO3 surface acoustic wave resonators with resonance frequency in the MHz range bulk
Establishing this approach will mean moving a step forward towards more efficient microelectronics and strain engineering.
Atomistic investigation of the diffusion of small xenon clusters in the metallic nuclear fuel UMo
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.
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 to deploy new computational methodologies in order to investigate the evolution of their thermophysical properties under irradiation conditions.
During this PhD project, you will be in charge of validating (and, if necessary, recalibrating) the atomistic computational models for UMo that have been published in the literature. You will then apply those to the simulation of the stability and diffusion of small xenon clusters (typically up to 5 xenon atoms) within UMo crystals. Those computations will be performed leveraging accelerated molecular dynamics methods, and systematically compared to the results obtained for the reference nuclear fuel UO2. The results will also be analyzed by comparison to experimental measurements performed within the department, as well as used as reference data for larger-scale nuclear fuel performance codes. The results of your research will be published in scientific journals, and you are expected to attend international conferences to present your findings.
Those different investigations will allow you to acquire a set of competences applicable to many areas of materials science: ab initio calculations, machine-learning adjustment of interatomic potentials, classical and accelerated molecular dynamics, as well as many elements of statistical physics and condensed matter physics, which are among the areas of expertise of the PhD advisors.
The PhD will be based in the Fuel Behavior Modeling Laboratory (IRESNE Institute, CEA Cadarache), a dynamic research environment within which you will have the opportunity to interact with other PhD students. You will also benefit from a rich collaborative network (experimental researchers from the department, ISAS Institute at CEA Saclay, CINAM Laboratory in Marseille), that will allow you to become a member of the nuclear materials research community.
Predicting thermodynamic properties of defects in medium-entropy alloys from the atomic scale through statistical learning
The properties and behaviour of materials under extreme conditions are essential for energy systems such as fission and fusion reactors. However, accurately predicting the properties of materials at high temperatures remains a challenge. Direct measurements of these properties are limited by experimental instrumentation, and atomic-scale simulations based on empirical force fields are often unreliable due to a lack of precision.This problem can be solved using statistical learning techniques, which have recently seen their use explode in materials science. Force fields constructed by machine learning achieve the degree of accuracy of {it ab initio} calculations; however, their implementation in sampling methods is limited by high computational costs, generally several orders of magnitude higher than those of traditional force fields. To overcome this limitation, two objectives will be pursued in this thesis: (i) to improve active statistical learning force fields by finding a better accuracy-efficiency trade-off and (ii) to create accelerated free energy and kinetic path sampling methods to facilitate the use of computationally expensive statistical learning force fields.
For the first objective, we improve the construction of statistical learning force fields by focusing on three key factors: the database, the local atomic environment descriptor and the regression model. For the second objective, we will implement a fast and robust Bayesian sampling scheme to estimate the anharmonic free energy, which is crucial for understanding the effects of temperature on crystalline solids, using an adaptive bias force method that significantly improves convergence speed and overall accuracy.We will apply the methods developed to the calculation of free energy and its derivatives, physical quantities that give access to the thermo-elastic properties of alloys and the thermodynamic properties of point defects. To do this, we will use algorithmic extensions that allow us to sample a specific metastable state and also the transition paths to other energy basins, and thus to estimate the free energies of formation and migration of vacancy defects. The thermodynamic quantities calculated will then be used as input data for kinetic Monte Carlo methods, which will make it possible to measure the diffusion coefficients in complex alloys as a function of temperature.
One aim will be to try to relate the atomic transport properties to the complexity of the alloy. Since our approach is considerably faster than standard methods, we will be able to apply it to complex alloys comprising the elements W, Ti, V, Mo and Ta at temperatures and compositions that have not been studied experimentally.
Behavior of nanocavities under mechanical loading: from understanding physical mechanisms to homogenizing nanoporous materials
Nanocavities - typically a few nm to a few tens of nm in size - are often observed in metals, for example in high-temperature applications due to the condensation of vacancies or in metal alloys used in nuclear reactors due to irradiation. The presence of these nanocavities degrades the mechanical behaviour of materials and contributes to fracture. It is therefore necessary to determine the physical mechanisms associated with the behaviour of these nanocavities under mechanical loading and to obtain homogenised models describing the macroscopic behaviour of these nanoporous materials. The results available in the literature remain limited to date, particularly with regard to the representativeness of the simulations carried out and the models proposed for the applications of interest. This includes for example considering crystal defects surrounding the cavities, the effect of cyclic loading and the localisation of nanocavities at grain boundaries. The objectives of this thesis are therefore to determine the behaviour of nanocavities under mechanical loading and the associated physical mechanisms by considering realistic situations with respect to applications, to develop physically-based analytical models to describe the behaviour of nanocavities under mechanical loading, and finally to propose homogenised models adapted to nanocavities that can be used to simulate the failure by growth and coalescence of cavities. The targeted applications are those related to metal alloys under irradiation, but the elements of understanding obtained and the models developed could be used in a broader context. In order to achieve these objectives, Molecular Dynamics (MD) simulations will be performed, analysed from the elastic theory of dislocations and used to propose relevant homogenised models for nanoporous materials.
Atomic-scale study of dislocation mobility in MOX fuel
The transition to carbon neutrality requires a rapid increase in low-carbon energy sources, including nuclear power, which necessitates a deep understanding of irradiated materials. Mixed oxide (MOX) fuel is particularly important as it optimizes the use of nuclear resources and reduces radioactive waste. The mechanical behavior of MOX under irradiation is crucial for ensuring the integrity of the fuel under various operating conditions.
The objective of this thesis is to perform atomistic simulations to understand dislocation mobility, essential for supporting multiscale modeling of the mechanical behavior of MOX. Molecular dynamics calculations will analyze dislocation mobility under different conditions of temperature, stress, plutonium content, and stoichiometric deviations, with the aim of establishing velocity laws. The results of these simulations will enhance micromechanical modeling within the CEA’s PLEIADES simulation platform, which is dedicated to simulating the complete lifecycle of nuclear fuel, from its fabrication to its storage.
The doctoral student will be based at the Fuel Behavior Modeling Laboratory in Cadarache, a dynamic environment with 11 permanent researchers and an equal number of doctoral students. Located in Provence, this center offers a pleasant working environment between the Verdon and Lubéron natural parks. The thesis will be carried out in collaboration with IM2NP, a leading laboratory in materials physics research.
The candidate should have a strong background in materials physics, ideally with experience in small-scale mechanics. These skills can be further developed during an M2 internship at the laboratory. The doctoral student will have the opportunity to present their work through scientific publications and at international conferences, opening up career opportunities in both research and industry.
Multi-scale modeling of hydrogen diffusion in Ni polycristals
In many applications metallic structural materials face hydrogen-containing environment and at some point the hydrogen enters the metal leading to mechanical properties deterioration and eventually to rupture. The mechanisms of hydrogen embrittlement have been widely studied. Yet, a general, predictive and quantitative model of these phenomena is still missing. This thesis focuses on hydrogen segregation at grain boundaries which is one of the mechanisms identified in hydrogen embrittlement. We aim at modeling the kinetics of the segregation process starting down from the atomic scale. In order to do this, we need to find the equilibrium structures of grain boundaries, identify the segregation sites for each grain boundary and then quantify how each grain boundary affects the diffusion coefficient of hydrogen. All this data will then be fed to a finite element model whose purpose is to compute hydrogen distribution in a polycristalline sample as a function of time, accounting for the specific properties of each grain boundary. These results will be compared with hydrogen permeation experiments which give access to an effective diffusion coefficient, as well as measures localized around a single grain boundary (PANI and SKPFM methods).
Understanding helium trapping mechanisms in new nickel-based alloy grades developed for molten salt reactors
Nickel-based alloys are structural materials of choice for Molten Salt Reactors (MSRs). They offer excellent mechanical properties and good corrosion resistance. In these materials, helium production, mainly caused by the transmutation of nickel by fast neutrons, can reach levels sufficient to strongly embrittle the material or cause it to swell under irradiation. Helium is hardly soluble in the material, and condenses in the form of bubbles or segregates at grain boundaries. To limit these phenomena and successfully trap the helium, one solution is to introduce into the material to be irradiated a high density of nanoprecipitates, whose interfaces will serve as germination sites for nanometric bubbles capable of trapping the helium atoms, preventing the latter from migrating to the grain boundaries and degrading the material's performance. Corrected transmission electron microscopy will be used to study the precipitation kinetics of the thermodynamically expected phases, as well as the atomic structure of the interfaces formed between the precipitates and the matrix. A phase-field simulation of precipitation will also be considered. Finally, the He trapping mechanisms at the interfaces will be studied using electron energy loss spectroscopy (EELS).
Structure and mobility of unterstitial clusters and loops in uranium oxide
Uranium oxide (UO2) is the usual fuel used in nuclear fission power plants. As such, its behaviour under irradiation has been extensively studied. Irradiation creates vacancies or interstitial defects that control the evolution of the material's microstructure, which in turn impacts its physical (e.g. thermal conductivity) and mechanical properties. Interstitial clusters in particular play a major role.
On the one hand, at the smallest sizes, the diffusion of interstitials in UO2 is still relatively poorly understood. Experimentally, we observe the appearance of dislocation loops made up of interstitials as large as ten nanometres. Conversely, no cavities are observed and the vacancy defects remain sub-nanometric in size. This indicates that interstitials diffuse more rapidly than vacancies, with diffusion allowing interstitials to agglomerate and form loops. However, atomic-scale calculations show no major difference between the diffusion coefficients of vacancies and interstitials in UO2. One hypothesis to explain this apparent contradiction is that interstitial clusters diffuse rapidly (Garmon, Liu et al. 2023).
On the other hand, the three-dimensional interstitial clusters are expected to be the seeds of the dislocation loops observed by transmission electron microscopy in irradiated uranium oxide. However, the mechanisms by which the aggregates transform into loops and the nature of the loops changes remain poorly understood in uranium oxide. These mechanisms have very recently been elucidated for face-centred cubic metals (Jourdan, Goryaeva et al. 2024). It is possible that comparable mechanisms are at work in UO2 with the complication induced by the existence of two sub-lattices.
We therefore propose to study interstitial clusters in UO2 using atomic-scale simulations.
We will first study the structure of these three-dimensional subnanometric clusters. To do this, we will use artificial intelligence tools for classifying defect structures developed in the laboratory (Goryaeva, Lapointe et al. 2020). We will study the diffusion of these objects using molecular dynamics and automatic searches for migration saddle points using kinetic-ART type tools (Béland, Brommer et al. 2011). Secondly, we will study the relative stability of 3D clusters and loops of faulted and perfect dislocations and the transformations between these different objects.
This study will be based on interatomic interaction potentials. We will start by using empirical potentials available in the literature before turning to Machine Learning-type potentials (Dubois, Tranchida et al. 2024) under development at the CEA Cadarache Fuel Studies Department.
Béland, L. K., et al. (2011). ‘Kinetic activation-relaxation technique.’ Physical Review E 84(4): 046704.
Chartier, A., et al. (2016). ‘Early stages of irradiation induced dislocations in urania.’ Applied Physics Letters 109(18).
Dubois, E. T., et al. (2024). ‘Atomistic simulations of nuclear fuel UO2 with machine learning interatomic potentials.’ Physical Review Materials 8(2).
Garmon, A., et al. (2023). ‘Diffusion of small anti-Schottky clusters in UO2.’ Journal of Nuclear Materials 585: 154630.
Goryaeva, A. M., et al. (2020). ‘Reinforcing materials modelling by encoding the structures of defects in crystalline solids into distortion scores.’ Nature Communications 11(1).
Jourdan, T., et al. (2024). ‘Preferential Nucleation of Dislocation Loops under Stress Explained by A15 Frank-Kasper Nanophases in Aluminum.’ Physical Review Letters 132(22).
Atomistic modeling of fracture in heterogeneous borosilicate glasses
Heterogeneous borosilicate-based glasses contain crystalline or amorphous precipitates forming secondary phases embedded within the glass matrix. These materials are valued for their high thermal shock resistance and excellent chemical durability, making them ideal for various applications such as cookware and laboratory equipment. In particular, within the nuclear industry, many wasteforms effectively function as glass-ceramics due to the presence of elements that form precipitates.
It is well known that secondary phases can significantly affect mechanical properties, particularly fracture toughness. However, the specific mechanisms by which they influence mechanical properties at the atomic scale remain poorly understood. In particular, whether they are crystalline or amorphous and the structure of their interface with the bulk glass are expected to play a crucial role.
The primary aim of this project is to investigate the specific mechanisms by which precipitates influence mechanical properties at the atomic scale.
Additionally, it seeks to understand how these precipitates affect crack propagation.
For this purpose, numerical modelling tools based on molecular dynamics will be employed.
This technique simulates the behaviour of individual atoms over time under different testing conditions.
Thus, it enables probing the local structure of crack tips and how they interact with precipitates at the atomic level, providing valuable insights into the mechanisms underlying crack resistance in heterogeneous glasses.