Le palladium est un métal rare dont la demande mondiale est en forte augmentation. Or, il est présent en tant que produit de fission dans les combustibles nucléaires usés qui sont retraités en France. Il serait donc intéressant de recycler ce métal. Pour cela, il est nécessaire de procéder à une épuration isotopique, afin de supprimer un des isotopes du palladium, le 107, qui est un radionucléide artificiel à vie longue émetteur béta. Dans le cadre d'un nouveau projet sur 4 ans construit en réponse à l'appel d'offre du Plan d'Investissement et d'Avenir de l’État, le Service d’Etude des Procédés d’Enrichissement propose un contrat post-doctoral portant sur le développement d’un système laser dans l’UV pour le procédé de séparation isotopique du palladium par Lasers actuellement en cours de développement. L’objectif principal du projet est la démonstration finale de la faisabilité de séparation de palladium naturel (et non radioactif) pour la phase suivante de développement d’un premier pilote.
Le post-doctorant devra développer des lasers prototypes de procédé à haute cadence en partant du visible (système lasers colorant) jusqu’à l'UV. Le passage dans l’UV se fait par doublage de fréquence avec des objectifs élevés en terme de performance. Il s’agit d’utiliser un cristal doubleur de fréquence de type BBO, LBO, KDP ou autre. Pour ce faire, le post-doctorat participera à la définition de ce cristal, mais aussi au développement de l’environnement du cristal doubleur (comportement, performances attendues et la tenue au flux des différents matériels). Des échanges seront mis en place sur ce sujet spécifique avec des spécialistes reconnus au sein de la Direction de la Recherche Fondamentale du CEA. La programmation (en Python et/ou sous Labview) de ces outils ou asservissements est à développer également. Une attention particulière sera portée sur les publications à réaliser essentiellement dans le cadre du doublage de fréquence, sujet complexe très étudié mondialement.
The control of the dynamic response of complex materials (foam, ceramic, metal, composite) subjected to intense solicitations (energy deposition, hypervelocity impact) is a major issue for many applications developed and carried out French Atomic Energy Commission (CEA). In this context, CEA CESTA is developing mathematical models to depict the behavior of materials subjected to hypervelocity impacts. Thus, in the context of the ANR ASTRID SNIP (Numerical Simulation of Impacts in Porous Media) in collaboration with the IUSTI (Aix-Marseille Université), studies on the theme of modeling porous materials are conducted. They aim to develop innovative models that are more robust and overcome the theoretical deficits of existing methods (thermodynamic consistency, preservation of the entropy principle). In the context of this post-doc, the candidate will first do a literature review to understand the methods and models developed within IUSTI and CEA CESTA to understand their differences. Secondly, he will study the compatibility between the model developed at IUSTI and the numerical resolution methods used in the hydrodynamics computing code of the CEA CESTA. He will propose adaptations and improvements of this model to take into account all the physical phenomena that we want to capture (plasticity, shear stresses, presence of fluid inclusions, damage) and make its integration into the computation code possible. After a development phase, the validation of all this work will be carried out via comparisons with other existing models, as well as the confrontation with experimental results of impacts from the literature and from CEA database.
Laser fusion facilities, like LMJ, require the use of large optical components. Some of them are large KDP or DKDP (KDP partially deuterated) plates extracted from single crystals.
Currently, DKDP single crystals are produced a by slow growth method were the growth time exceeds two years.
Here, we proposed to study a rapid growth method to reducing the growth time to a few months.
A post-doctoral position is opened at the Interdisciplinary Research Institute of Grenoble (IRIG) of the CEA Grenoble (France) on the theory and modeling of silicon spin quantum bits (qubits). The selected candidate is expected to start at the beginning of year 2022, for up to two years.
Quantum information technologies on silicon have raised an increasing interest over the last few years. Grenoble is pushing forward an original platform based on the “silicon-on-insulator” (SOI) technology. In order to meet the challenges of quantum information technologies, is essential to support the experimental activity with state-of-the-art modeling. For that purpose, CEA is actively developing the “TB_Sim” code. TB_Sim is able to describe very realistic qubit structures down to the atomic scale when needed using atomistic tight-binding and multi-bands k.p models for the electronic structure of the materials. The aims of this postdoctoral position are to strengthen our understanding of spin qubits, and to progress in the design of efficient and reliable Si and Si/Ge spin qubit devices and arrays using a combination of analytical models and advanced numerical simulations with TB_Sim. Topics of interest include spin manipulation & readout in electron and hole qubits, exchange interactions in 1D and 2D arrays of qubits and operation of multi-qubit gates, sensitivity to noise (decoherence) and disorder (variability). This work takes place in the context of the EU QLSI project and will be strongly coupled to the experimental activity in Grenoble and among the partners of CEA in Europe.
The control of materials (mainly stainless steel) aging of the spent nuclear fuel reprocessing plant is the subject of permanent attention. Some installations at La Hague plant will have to be replaced very soon. In this context, it is important for the industry to develop sensors that are resistant to concentrated nitric acid (˜ 2.5 mol / L) and temperature (from ambient to 130 °C), allowing the online monitoring of the corrosion.
The aim of this work is to manufacture one sensor for the detection of corrosion of the steel intended for handling by the operators of the plant. In case of a positive response, the second sensor is used.
The challenges of this work are essentially technological since it will develop or use materials adapted to concentrated and hot nitric acid media.
The laboratory is specialized in the corrosion study in extreme conditions. It is composed of a very dynamic and motivated scientific team.
Modeling the alteration of spent nuclear fuel in the eventuality of an underwater interim storage in pools or a deep geologic disposal is essential for long-term prediction. In the event of a failed spent fuel assembly, corrosion processes can lead to a deterioration of the failed rod and to a radionuclide release into water. A geochemical model coupling chemistry to transport (reactive transport) was the subject of first developments in connection with deep geological disposal conditions using the CHESS-HYTEC code developed by the Ecole des Mines de Paris. This model makes it possible to take into account the main alteration mechanisms and associated kinetics while relying on robust thermodynamic data. It remains important to pursue these developments by studying the effect of temperature between 20 and 70 °C. Adapting this model to other alteration conditions like an underwater of spent fuel in dedicated pools for several decades is also a short-term objective.
The proposed research project is related to the search for hardware accelerators for solving NP-hard optimization problems. Such problems, for which finding exact solutions in polynomial time is out of reach for deterministic Turing machines, find many applications in diverse fields such as logistic operations, circuit design, medical diagnosis, Smart Grid management etc.
One approach in particular is derived from the Ising model, and is based on the evolution (and convergence) of a set of binary states within an artificial neural network (ANN).In order to improve the convergence speed and accuracy, the network elements may benefit from an intrinsic and adjustable source of fluctuations. Recent proof-of-concept work highlights the interest of implementing such neurons with stochastic magnetic tunnel junctions (MTJ).
The main goals will be the simulation, dimensioning and fabrication of hybrid CMOS/MTJ elements. The test vehicles will then be characterized in order to validate their functionality.
This work will be carried out in the frame of a scientific collaboration between CEA-Leti and Spintec.
Thanks to new supercomputer architectures, classical molecular dynamics simulations will soon enter the realm of a thousand billion atoms, never before achieved, thus becoming capable of representing the plasticity of metals at the micron scale. However, such simulations generate a considerable amount of data, and the difficulty now lies in their exploitation in order to extract the statistical ingredients relevant to the scale of "mesoscopic" plasticity (the scale of continuous models).
The evolution of a material is complex, as it depends on lines of crystalline defects (dislocations) whose evolution is governed by numerous mechanisms. In order to feed models at higher scales, the quantities to be extracted are the velocities and lengths of dislocations, as well as their evolution over time. These data can be extracted using specific analysis techniques based on characterization of the local environment ('distortion score', 'local deformation'), a posteriori or in situ during simulation. Finally, machine learning tools can be used to analyze the statistics obtained and extract and synthesize (by model reduction) a minimal description of plasticity for models at higher scales.