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.
Self Forming Barrier Materials for Advanced BEOL Interconnects
Context : As semiconductor technology scales down to 10 nm and below, Back End of Line (BEOL) scaling presents challenges, particularly in maintaining the integrity of copper interconnects, where line/via resistance and copper fill are key issues. Copper (Cu) interconnections must resist diffusion and delamination while maintaining optimal conductivity. In the traditional Cu damascene process, metal barriers and a Cu seed layer are deposited by PVD to enable electrochemical copper deposition. As dimensions shrink, it becomes increasingly difficult to incorporate tantalum-based diffusion barriers, even with techniques like atomic layer deposition (ALD), as the barrier thickness must be reduced to just a few nanometers. To address this challenge, a self-forming barrier (SFB) process has been proposed. This process uses copper alloys containing elements such as Mn, Ti, Al, and Mg, which segregate at the Cu-dielectric interface, forming an ultra-thin barrier while also serving as a seed layer for electroplating.
Thesis Project: The PhD candidate will join a leading research team to explore and optimize materials for SFBs using Cu alloys. Focus areas include:
- Material Selection & Characterization: develop and analyze Cu alloy thin films by electrochemical and PVD methods to study their microstructure and morphology.
- Barrier Formation: Control alloy migration at the Cu/dielectric interface during thermal annealing and assess barrier effectiveness.
- Electrical & Mechanical Properties: Evaluate SFB impact on electrical resistance, electromigration, and delamination, especially in accelerated tests.
Required skills : Master's degree in electrochemistry or materials science with a strong interest in applied research. A pronounced interest in experimental work, skills in thin film deposition, electrochemistry and materials characterization (AFM, SEM, XPS, XRD, SIMS). You should be able to conduct bibliographic research and organize your work efficiently.
Work Environment: The candidate will work in a renowned laboratory with state-of-the-art 200/300 mm facilities and will participate in the CEA’s NextGen Project on advanced interconnects for high reliability applications.
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.
Ultrasound-assisted decontamination of Hg-bearing solids
Mercury is one of the most dangerous pollutants. Yet, it has been widely used in the industry, in particular in electrolysers (chlor-alkali process), resulting in many contaminated facilities. Existing methods to stabilise or decontaminate are either energy-consuming or limited in terms of speciation. The aim here is to develop a new method combining leaching and ultrasonic irradiation, to decontaminate porous solids (e.g. mortar). The characterisation of solids and liquids before/after decontamination will be performed using SEM-EDX, XRD and XRF.
The PhD study will be performed in Marcoule centre, located 30 minutes from Avignon. The two host laboratories are the Laboratory of Supercritical Processes and Decontamination (DMRC/STDC/LPSD) and the Laboratory of Sonochemistry in Complex Fluids (ICSM//LSFC). Marcoule site is served by bus and hosts many PhDs and post-docs. The candidate should hold a master degree with a chemical engineering background and desirable skills in analytical chemistry and inorganic chemistry. The candidate will gain initial experience in the field of decontamination, which is one of the major problems associated with the circular energy economy. Depending on the focus of the thesis, they will be able to pursue a career in academia or industry.
Study of the corrosion behaviour in NaCl-MgCl2-CeCl3 of a nickel-based alloy in the presence of fission products (Te, S) for molten salt reactor
Access to clean and affordable energy seems more crucial than ever in the current context of climate emergency. Several avenues have been explored for years, but many technological barriers remain to be overcome in order to realise them, as they represent significant technological breakthroughs. Whether it's for energy storage or 4th generation nuclear reactors, the molten salt medium used as a heat transfer fluid and/or fuel is highly corrosive, making the choice of structural materials very complex.
The objective of the proposed PhD project within the Service of Corrosion and Material Behaviour (S2CM) is the comprehensive study of the behaviour of promising nickel-based alloys in the NaCl-MgCl2-CeCl3 ternary system, representative of the salt used in the French molten salt reactor concept, at 600°C. By "comprehensive", this refers to everything from specimen preparation to the multi-scale and multi-technique characterisation of corrosion products. This topic has therefore a strong experimental character and focuses on understanding corrosion mechanisms. The influence of fission products, such as tellurium or sulphur, on corrosion mechanisms will be specifically studied.
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.
Oxide-clad joint and internal corrosion layer modelling in GERMINAL using experimental data provided by different characterisation techniques
This work will be done in the frame of studies on the thermo-mechanical and physico-chemical behaviour behaviour of the « uranium and plutonium mixed oxide fuel » during irradiation currently considered for the future reactors of 4th generation. Because of its particularly hight thermal level during irradiation this kind of fuel is subject to several physical and chemical phenomena duringf its stay in reactor. Those one can have a strong impact on the behaviour of the whole fuel element (pellet and clad), but we can focus on two specific phenomena that take place at middle and high burnup :
- the formation by evaporation-condensation of a fission products layer between the external surface of the fuel pellet and the inner surface of the cladding material at middle burnup, designed as JOG for Joint Oxyde-Gaine;
- the formation of a corrosion layer on the internal surface of the clad, containing fission products and elements constituting the cladding material at high burnup, and resulting from the FCCI (Fuel-Cladding Chemical Interaction),
The occurence of this two phenomena is a limiting factor for increasing the burnup. Thus it is important de be able to estimate quite precisely the chemical composition of the fuel pellet and of the fuel-to-clad gap during irradiation. Previous experimental work had shown that the JOG consisted mainly of caesium, molybdenum and oxygen, with the presence of other elements such as tellurium and barium. Observations have also shown the presence of chromium, iron and nickel, along with other volatile fission products (VFP), in areas of ROG. These observations were backed up by thermodynamic calculations, which led to the assumption that the JOG consisted mainly of caesium molybdate Cs2MoO4. However, until recently, there had been no direct evidence of the presence of this compound. Recently, more detailed characterisation methods carried out as part of a current thesis on (U,Pu)O2 fuel samples confirmed quantitatively that the JOG was mainly made up of Cs, Mo and O, but also of I and Ba distributed in several phases. Other elements were detected and measured in localised areas, namely Te, Zr as well as U and Pu. With regard to corrosion, phases based on Fe, Te and Pd were observed, as well as the joint presence of Cr and O.
At the same time, work was started on modelling the axial redistribution of caesium, with a view to improving the description currently used in GERMINAL. The chemical element inventory at a given axial dimension has a first-order effect on the calculated JOG thickness and ROG thickness.
The aim of this thesis is to improve the description and modelling of JOG and ROG formation in the GERMINAL scientific calculation tool (OCS), which is dedicated to calculating the thermo-mechanical and physico-chemical behaviour of 4th generation reactor fuel irradiated under nominal and/or incidental conditions.
To this end, research will be developed in three areas:
- Further development of the radial migration methodology adopted in the GERMINAL code through comparison with existing and recently obtained experimental results. This is based on a coupling with a thermochemistry module in which several hypotheses for the release of volatile fission products created in the pellet towards the pellet-cladding gap can be considered.
The aim of this PhD subject consists in improving the JOG and FCCI modeling into the fuel performance code (FPC) GERMINAL, dedicated to the calculation of the thermo-mechanical and physico-chemical behaviour of the 4th generation reactors’ fuel irradiated in normal and off-normal conditions. For that purpose, an acurrate experimental caractherization of some irradiated fuel samples, to which the PhD student will contribute, will be elaborated and coupled to a thermodynamic approach. The research will be based on the two items :
- Determination and experimental identification of the chemical elements and phases located into the fuel pellet, into the gap and at the fuel-to-clad interfaces at the end of the irradiation using the implementation of microprobe-SIMS-SEM/FIB techniques, by combining elemental and isotopic analysis results with microscopic observations.
- Comparison of the results with thermodynamic calculations: type and local quantities of the chemical phases formed in the fuel pellet as well as the phases constituting the JOG and those resulting from the FCCI.
Thus, based on those results, it will be possible to evaluate precisely the chemical composition of the irradiated fuel, of the JOG and of the corrosion compounds by using the FPC GERMINAL, from which the input inventory in chemical elements will be estimated in function of burnup at the different radial and axial localisations.
The PhD student will be attached both to a multi-scale modeling group and to an experimental team having sophisticated tools. Furthermore, academic or international collaborations are possible, in particular in the frame of the OECD/NEA with the development of the TAFID database. The student will have the opportunity to enhance the skills learned in the field of nuclear materials characterisation as well as in the field of thermodynamic calculations and irradiated fuel behaviour simulation.
To this end, the research will be developed along three lines:
- Further development of the radial migration methodology adopted in the GERMINAL code through comparison with existing and recently obtained experimental results. This is based on a coupling with a thermochemistry module in which several hypotheses for the release of volatile fission products created in the pellet towards the pellet-cladding gap can be considered.
- Further development of a [simplified] model for the axial redistribution of caesium and, by extension, of volatile fission products, leading to an initial implementation in the GERMINAL code for testing and preliminary validation of the axial inventories estimated by calculation by comparison with experimental results,
- Finally, thermodynamic calculations to determine the nature and local quantity of the chemical phases formed in the fuel pellet and the constituent phases of the JOG and ROG will be carried out on the basis of the axial inventories estimated by the GERMINAL code.
This will enable a more accurate assessment of the chemical composition of the irradiated fuel, the JOG and the ROG products as a function of the burn-up rate using the GERMINAL OCS as a function of time at the various radial and axial locations.
The PhD student will be integrated into the fuel behaviour study and simulation group(IRESNE Institute, CEA CAdarache) which has or is developing various simulation tools, and will also be able to interact with a characterisation laboratory with cutting-edge experimental tools. Academic and international collaborations are also possible, particularly within the OECD/NEA framework with the development of TAFID database. These will enable the PhD student to make the most of the skills he or she has acquired in the field of characterisation of nuclear materials, as well as in thermodynamic calculations and simulation of the physico-chemical behaviour of irradiated nuclear fuel.
Nucleation, Growth, and Multi-Scale Structural Properties of Colloidal Nanoparticles of Actinide Oxides (Pu, U, Th)
Nanocrystalline oxides possess unique physicochemical properties, modulated by their size and local structure, making them promising for various technological applications. However, actinide oxide nanoparticles remain underexplored due to their radioactivity and toxicity. Nonetheless, studies dedicated to these species are growing, driven by environmental and industrial considerations, particularly for their involvement in current and future nuclear fuel cycles. This thesis focuses on plutonium, a key element in nuclear reactors. Its behavior in solution is complex, particularly due to hydrolysis reactions that lead to the formation of highly stable colloidal PuO2 nanoparticles. Although these species are now better described, the mechanisms leading to their formation remain largely unexplored.
The ambitious goal of this thesis is to uncover the fundamental mechanisms involved in the formation of these nanoparticles by adopting a systematic approach that combines a wide range of experimental parameters. These include the synthesis medium, temperature, reactant concentration, reaction time, and the contribution of sonochemistry. The focus will be on studying the nucleation and growth stages of these nanoparticles, as well as their structural properties in relation to the physicochemical conditions that influence their formation. Studies will be conducted at ICSM with Th, U, and Zr as analogs, and at the Atalante facility for Pu. In addition to standard laboratory techniques necessary for characterizing these systems, complementary experiments will be carried out on synchrotron lines (SOLEIL and ESRF) to thoroughly investigate the structural and reactive properties of these species and their precursors.
AI based prediction of solubilities for hydrometallurgy applications
Finding a selective and efficient extractant is one of the main challenges of hydrometallurgy. A comprehensive screening is impossible by the synthesis/test method due to the high number of possible molecules. Instead, more and more studies use quantum calculations to evaluate the complexes stabilities. Still, some important parameters such as solubility are lacking in this model.
This project thus aims to develop an AI based tool that provides solubility values from the molecular structure of any ligand. The study will first focus on 3 solvants: water, used as a reference as AI tools already exist, 3 M nitric acid to mimic nuclear industry applications and n-octanol, organic solvent used to measure the partition coefficient logP. The methodology follows 4 steps:
1) Bibliography on existing AI tools for solubility prediction yielding the choice of the most promising method(s)
2) Bibliography on existing databases to be complemented by the student's in-lab solubility experiments
3) Code generation and training of the neural network on the step 2 databases
4) Checking the accuracy of the predictions on molecules not included in the databases by comparing the calculated results with in-lab experiments
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.