Stereoselective synthesis of chiral organophosphorus compounds for the structure-activity relationship investigation at the front-end of the fuel cycle
The recovery of uranium by hydrometallurgical means involves a liquid-liquid extraction (LLE) step. During this step, the uranium extracted in the aqueous phase after crushing, grinding, and leaching of the rocks is selectively transferred to an immiscible oil phase containing a lipophilic ligand that enables this transfer. As part of the CEA's accelerated program on scientific and technical research for the nuclear energy front-end, this doctoral project aims to complete previous studies carried out at the laboratory on the relationship between the stereochemistry of certain organophosphorus ligands carrying stereogenic centers and their uranium extraction properties. Since these ligands, which are phosphoric diesters or amido- and aminophosphonates, could previously only be obtained under their stereo-enriched form, the Ph. D. student will have to synthesize their diastereopure forms sensu stricto. He will evaluate the affinity of the latter for uranium and their selectivity with respect to competing ions. He will then analyze the molecular and supramolecular mechanisms of each of the diastereoisomers (coordination, aggregation) using state-of-the-art methods such as UV, IR, multinuclear NMR, DFT, X-ray scattering, and neutron scattering. The doctoral program will enable the Ph. D. student to easily join academic or industrial environments, particularly in the fields of the nuclear fuel cycle and separation chemistry. The research will be conducted at the LTSM laboratory of the Marcoule Institute of Separative Chemistry, renowned for its expertise in the chemistry and physical chemistry of extractants for hydrometallurgy. The Ph. D. student will benefit from high-quality supervision and a collaborative working environment, surrounded by Ph. D. students, post-doctoral researchers, and engineers, in a calm and stimulating framework.
EFFECT OF ULTRASOUND ON THE URANIUM EXTRACTION PERFORMANCE OF MONOAMIDES
Liquid-liquid extraction of uranium using monoamides can be limited by complex phenomena, such as third-phase formation or precipitation. This third phase contains a very high concentration of uranium complexes, strongly reducing extraction efficiency and hindering extractant reuse.
The aim of the present PhD is to investigate whether ultrasound (US) can limit third-phase formation and improve uranium extraction. Sonication generates micrometric cavitation bubbles that oscillate and collapse violently, producing intense mixing and shear forces. Cavitation is known to enhance mass transfer and, in many systems, reaction kinetics. However, to the best of our knowledge, it has not yet been applied to uranium liquid-liquid extraction.
The influence of US parameters (frequency, power, irradiation time, etc.) will be investigated using a two-scale approach:
- Nanoscale: effect of US on the size and interactions of organic-phase aggregates and their relationship with extraction and third-phase formation;
- Macroscale: effect of US on mixing, viscosity, extraction kinetics, and phase separation.
Complementary characterization techniques will be used to assess the effect of US on uranium extraction. ICP-OES will quantify uranium concentrations and determine extraction yields and distribution ratios. SAXS/SANS will characterize organic-phase aggregates, while rheology will probe changes in viscosity and flow properties. NMR, IR, and UV–vis spectroscopy will provide complementary information on molecular interactions, uranium speciation, and the chemical environment of the extracting species. Together, these techniques will correlate molecular-scale organization, macroscopic properties, and uranium extraction performance.
The work will also include an instrumentation component, involving the design and development of an experimental cell suitable for in situ studies under US irradiation.
Chemical Engineering of Active Surfaces in II–V Material Technologies for Cooled Infrared Detection
Voici la traduction anglaise complète, avec un vocabulaire scientifique adapté à un résumé de thèse.
Écriture
This PhD thesis builds on previous research aimed at improving the passivation of HgCdTe photodiodes, particularly those based on P-i-N architectures. It seeks to understand the physicochemical mechanisms responsible for the degradation of interfaces between the semiconductor material and the passivation layer. Previous studies have highlighted the influence of residual contaminants, surface oxidation, and excess tellurium on the electrical properties of devices.
The main objective is to develop surface engineering processes that enable better control of the chemical composition and defects at these interfaces. Various chemical and electrochemical treatments will be investigated to limit oxidation, reduce contamination, and improve surface stability. Characterization will rely on advanced techniques such as X-ray Photoelectron Spectroscopy (XPS), Hard X-ray Photoelectron Spectroscopy (HAXPES), and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), complemented by electrical and electrochemical measurements. Particular attention will be paid to establishing quantitative correlations between the chemical composition of interfaces, their electrochemical properties, and their electrical behavior. These results will help identify the key parameters governing photodiode performance and optimize passivation treatments. The developed processes will then be evaluated on structures representative of P-i-N photodiodes, particularly with a view to operation at elevated temperatures. Finally, this thesis incorporates an eco-innovation component aimed at making manufacturing processes more environmentally friendly. The development of in-situ electrochemical treatments and new, so-called “green” chemistries could make it possible to replace certain conventional bromine-based solutions. Ultimately, this research will contribute to the development of higher-performance, more stable infrared detectors that require less demanding cooling systems, while potentially reducing the environmental impact of manufacturing processes.
Nucleation and Growth of Actinide Oxide Nanoparticles : Multiscale Modeling Using Molecular Dynamics and Machine Learning
The formation of actinide oxide nanoparticles (Th, U, Pu) in aqueous solution is a major scientific challenge, both for understanding their behaviour under environmental conditions and for better controlling the properties of future-generation nuclear fuels. The nucleation-growth mechanisms of these nanostructures remain poorly understood at the molecular level: experimental studies have revealed a growth mechanism that differs from classical nucleation theory, without being able to identify it. This thesis in theoretical and computational chemistry aims to model this process through a multiscale approach. Ab initio molecular dynamics simulations (DFT+U, VASP/CP2K) will be devoted to studying the structure, diffusion and condensation of solvated actinide(IV) hydroxo complexes, the precursors of nucleation. These results will also be used to train classical machine-learning potentials, in order to simulate large-scale systems (with LAMMPS). Biased sampling methods will finally make it possible to access rare events (high activation barriers, collective effects). The project will be carried out in collaboration with the LSFC laboratory at ICSM, who performed the experimental measurements (EXAFS/XANES, SAXS and DLS) needed to validate the models. This thesis will allow the candidate to acquire fundamental skills in ab initio simulation and machine learning. Beyond these technical skills, the candidate will also be able to develop valuable experience in scientific communication, as well as in collaborative work with experimental teams. This experience will thus be an asset for a future career, in both academia and industry.
Towards an advanced modelisation of actinide oxides through dielectric aware machine-learning potentials
Actinide oxides, such as UO2, PuO2, and their mixed oxide(MOX), are fundational fuel materials for existing and next-generation nuclear reactors where their thermomechanical properties dictate fuel safety and operational performance. These materials are polar ionic crystals, and their dielectric properties therefore play a central role in their physical behavior. For instance, long range electrostatic interactions and dynamical polarizabilities shape the phonon spectrum, control the thermodynamic properties and impact the heat transport of the solids. From a simulation point-of-view, neglecting these effects risks systematic error in the prediction of properties that matter for fuel performance.
This project will develop and apply novel machine-learning atomistic simulation methodologies that explicitly incorporate dielectric properties into the description of actinide oxides, bridging a critical gap between current frameworks and the physic of polar materials.
In the first phase of this work, you will train a machine-learning interatomic potential with explicit long-range electrostatic capability for UO2, PuO2 and MOX. The potential will then be applied in large-scale finite-temperature simulations to quantify the impact of electrostatic interactions on elastic properties, thermal expansion, thermal conductivity and key thermodynamic properties such as heat capacity. The same potential will be used to compute infrared spectra, which are directly sensitive to the dynamic charge response of the material. Comparison with available experimental measurement will serve as an assessment of the accuracy of the atomistic model for actinide oxides.
Building on this framework, the second phase will extend the MLIP architecture to couple explicitly to external electric fields, enabling the direct simulation of polarizability derivatives and Raman-active vibrational modes. This will allow the computation of Raman spectra directly from molecular dynamics, providing a link between spectroscopic signatures and atomic structure.
The results produced at each stage of this project will constitute original contributions to the field and will be disseminated through publications in international peer-reviewed journals and presentations at international scientific conferences.
Beyond its scientific outcomes, the project will provide you with a versatile skill set applicable to many areas of materials science: ab initio electronic-structure calculations, the development of machine-learning interatomic potentials, classical molecular dynamics, and the key concepts of statistical physics and condensed-matter physics. You will also receive training in high-performance computing, with direct access to CEA supercomputing facilities. The supervising team includes recognized experts in all of these fields.
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:
• 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] King, D. S., Kim, D. Zhong, P., & Cheng, B. (2025). Machine learning of charges and long range interactions from energies and forces. Nature Communications 16, 8763.
Molecular Understanding of Liquid Hybrid Nanoparticles for Targeted Rare Earth Metal Separation
Rare earth metals are vital for high-tech applications in batteries, electronics, and in other devices linked to renewable energy. Due to rising demand and the associated supply risks, recycling has be-come a strategic priority. Liquid-liquid extraction is a key process for metal separation, but it faces sustainability challenges, including the use of volatile, non-sustainable solvents.
Liquid hybrid nanoparticles (LHNs) are an emerging class of next-generation systems that combine fluidity with the permanent porosity of solid adsorbents. Also referred as Type I porous liquids in the context of gas separation, they consist of hollow silica nanospheres, externally grafted with an organic corona for fluidity and compatibility, and that are internally functionalized with selective groups to target the capture of specific cations. Exploring such complex systems is challenging using purely experimental and trial-and-error approaches, so this PhD project aims to design LHNs using state-of-the-art molecular dynamics simulations, enabling detailed study of solvation, interfaces, and confinement at relevant time and size scales.
The key objectives of this PhD thesis are:
- To reveal the structural features of the organic corona determining the viscosity and hydrophobicity of LHNs;
- To study the interfaces between LHNs and aqueous solutions of metal ions to resolve liquid-liquid interfacial structure and transport across phases;
- To explore pore accessibility and preferential ab-sorption sites for the cations.
The methods used will include simulations with polarizable force fields, machine-learning interaction potentials, and quantum chemical calculations. The outcome of the project is expected to address important societal challenges related to sustainability, resource efficiency, and circular economy strategies.
(U, Pu)O2 fuel for 4th generation reactors: the impact of the porosity on the thermal conductivity.
Thermal conductivity is a key property governing the thermomechanical behaviour of nuclear fuels. It depends, in particular, on their microstructure and porosity, which can reach high levels in MOX fuels (mixed uranium and plutonium oxides) used in fast neutron reactors (FNRs).
This PhD aims to understand and quantify the influence of porosity on the thermal conductivity of MOX fuels, with the objective of establishing a predictive law that accounts for pore fraction, size, shape and interconnectivity. The study will build on recent experimental measurements performed at the European Commission’s Joint Research Centre (JRC) in Karlsruhe, at temperatures of up to 2700K, and on comparisons between these measurements and numerical simulations at the microstructural scale.
The PhD will be carried out at CEA Cadarache, within IRESNE, in the Laboratory for Expertise and Validation of Multi-Reactor-Technology Applications (LEVA). The collaboration with the JRC will provide an international scientific environment. The research will lead to scientific publications and conference presentations. It will also provide the opportunity to develop skills in experimental data analysis and numerical modelling, which are transferable to other areas of materials science and engineering.
Thermal conductivity of mixed oxide fuel (MOX): effect of temperature, elementary chemical composition, microstructure and burn-up in reactor, PhD thesis by Plamen Bonev at CEA, DEC/SESC/LEVA (2023), available through the TEL – Thèses en ligne portal.
uantification of the Thermophysical Properties of Molten Salts at High Temperatures: New insight gained of Laser Techniques
Molten-salt reactors are the subject of significant research at the national and international levels, particularly to assess their potential for actinide and nuclear waste management. In this context, the knowledge of corresponding salt properties and their evolution as a function of temperature and composition is crucial. This includes melting point, viscosity, surface tension, density and thermal conductivity quantification in the temperature range of 600-800°C, that require specific and complex experiments for their determination. To overcome the current limitations of measurement techniques and gain new insight into these critical properties we propose to develop an original set of experiments and methodologies relying on laser and optical techniques. Specifically, high power lasers will be used to drive the “salts” at high temperature, and imaging, spectrometry, thermography and pyrometric techniques will be deployed to determine the properties of interest thanks to the great flexibility offered with these optical and laser-based techniques. The proposed approach to reach the objectives goes from the conceptual designs tested in a photonics laboratory to the application in a hot cell laboratory, which is the final targeted point, thanks to a coupled modelling approach [see for example: 1, 2, 3].
The thesis work will be conducted in collaboration between the Fresnel Institute in Marseille and the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE) at CEA/Cadarache centre.
The thesis will enable the student to acquire skills in optical instrumentation, laser heating, high-temperature metrology, image processing, and numerical modelling. These skills can be applied in public or industrial research, particularly in the fields of instrumentation, materials, and nuclear energy.
Thesis supervisor (CEA): Y. Pontillon
Reference.
[1] Gabriel Aulanier, Matthieu Reymond, Thomas Doualle, Cihan Koc, Julien Lumeau, Yves Pontillon, Laurent Gallais, Development of a spectral ellipsometer for the investigation of the optical properties of mono- and polycrystalline UO2, Optics Continuum, vol. 5, 2647-2665, 2026
[2] Matthieu Reymonda,b, Thomas Douallea,b, Jerome Sercombea, Mathilde Roccaa, Mehdi Nasselahsena, Christian Colina, Yves Pontillona and Laurent Gallaisb, High power laser heating of nuclear ceramics for the generation of controlled spatio-temporal gradients, J. Appl. Phys. 134, 033101 (2023)
[3] T. Doualle, V. Le Guillous, V. Klosek, C. Onofri-Marroncle, M. Reymond, L. Gallais, Y. Pontillon, ‘Development of UO2 thermal diffusivity measurement with laser techniques’, EPJ Web of Conferences 253, 07005 (2021)
Structure-formulation-property relationships of bio-based eutectogel vitrimer electrolytes for next-generation batteries
Current batteries primarily rely on the use of liquid electrolytes composed of flammable solvents that are unstable in contact with lithium metal, posing safety issues. The development of gel polymer electrolytes (GPEs) is expected to lead to new generations of safer batteries. To maintain their environmental relevance, these new batteries should ideally be made of bio-based materials, have an extended lifespan, and be recyclable. In this context, this thesis aims to develop bio-based GPEs cross-linked by vitrimer chemistry that allows for their recyclability. The swelling of electrolytes in green, non-flammable deep eutectic solvents (DESs) is considered to achieve ionic conductivities greater than 10-4 S.cm-1 at room temperature. The PhD student will study the influence of the chemical structure of the polymer and the DES on the physicochemical, mechanical, and electrochemical properties of these eutectogels to optimize their formulation for integration into a complete pouch-cell system.
ENGINEERING SUPERCONDUCTING SURFACES FOR PARTICLE ACCELERATORS AND QUANTUM DEVICES
This project will establish atomic layer deposition (ALD) as a versatile surface engineering approach for superconducting resonators, addressing two complementary objectives for particle accelerators and quantum technologies.
The first objective is controlled doping of bulk niobium superconducting radiofrequency (SRF) cavities. Conformal films up to 10 nm thick will provide solid dopant sources, followed by high-vacuum annealing to tailor dopant profiles within the RF-active region. This strategy aims to improve uniformity, explore alternative dopants and eliminate subsequent electropolishing. Particular attention will focus on suppressing hydride formation while preserving the superconducting energy gap. Target performances include quality factors of 8 × 10¹° at 2 K and accelerating gradients of 40–45 MV/m. Supported by the European EPITA project, this work addresses requirements for future accelerators, including the Future Circular Collider.
The second objective is developing protective coatings with minimal dielectric losses by mitigating defects, particularly two-level systems. Building on CEA treatments combining dielectric oxide coatings and annealing that achieved record quantum-regime quality factors, alternative compounds will be investigated.
Ultimately, one treatment could enhance performance across quantum and accelerator operating regimes. Tunneling spectroscopy, X-ray spectroscopy and TOF-SIMS will correlate local superconducting properties with surface chemistry and dopant distributions. Two ALD systems will support development on coupons and transfer to resonators, building on demonstrated coating uniformity inside cavities. RF measurements will be conducted at CEA and partner laboratories, with Fermilab evaluating promising treatments at millikelvin temperatures. These investigations will clarify performance-limiting mechanisms and guide the rational design of optimized superconducting surfaces for both application domains.