Machine learning based MD for two temperature metals
The advent of femtosecond lasers has shed new light on non-equilibrium physics. The rapid energy
absorption by electrons and their subsequent energy transfer to the lattice results in non-equilibrium states of matter, initiating a new class of non-thermal processes from ambient solids to extreme conditions of temperature and pressure. The dynamic interplay between electrons and the atomic structure is the centralissue driving ultrafast phase transitions. However, the time scale of phase transitions and the microscopic mechanism driving melting are still not well understood. Classical molecular dynamics is well-suited to address this question, but classical potentials are limited in their ability to describe phenomena induced by electronic structure. DFT-based molecular dynamics could overcome this limitation, but it cannot reach the number of atoms necessary to provide a realistic picture. Machine learning potentials fitted on DFTsimulations can bridge this gap. As the interation potential between atoms depend ontheir electronic temperature we propose to learn and incorporate this dependance directly into the MLIP. Then, the Two-Temperature Model, where the diffusion equation for the electronic temperature is solved on a grid and the ionic motion is solved using MD will be employed to investigate out-of-equilibrium effects on the melting dynamics. In particular large scale MD will be used to simulate the melting of a full gold target(few tens of nm length) under laser absorption.
Method for dimensionality reduction applied to deformed coupled cluster theory
Ab initio calculations in nuclear physics have undergone considerable progress over the past 20 years, enabling the study of several hundred nuclei with approximately 5% precision, notably through the PAN@CEA collaboration (A-Nucleon Problem at CEA) between DAM, DRF, and DES. These methods connect nuclear phenomenology to QCD theory via chiral effective field theory (cEFT) and find applications in both nuclear structure and particle physics.
Despite these advances, the majority of the Segrè chart remains inaccessible, with limitations to nuclei of mass A~100. This limitation stems from the computational and memory costs that scale with the desired mass and precision, related to the storage of large tensors. Recent research has demonstrated that a significant portion of the information in these tensors can be compressed through dimensionality reduction methods without significant loss of precision.
The postdoctoral project aims to extend these methods to the non-perturbative framework of deformed coupled cluster theory (dCC). The objectives are: 1) to implement the dCCSD method for nuclei up to A~80, 2) to develop its factorized version (TF-dCCSD) and validate it, 3) to extend it either to excited states (EOM-dCCSD) or to sub-percent precision (dCCSDT).
Simulation of landslides and the associated water waves by a 3D code
Until now, tsunamis generated by underwater landslides were modelled at the CEA using a 2D long wave code (Avalanche) that was adapted to the computing resources available at the time but now seems obsolete in the literature. An initial post-doctoral study (2023-2025) showed that the 3D OpenFoam tool could accurately simulate a landslide and the associated waves in the generation zone. During this post-doctoral fellowship, a coupling between the CEA's ‘2D’ propagation code (Taitoko) and the 3D code was developed in order to propagate waves over long distances. The work carried out will be continued. The first objective will be to familiarise with the tools developed and to publish the work carried out on the 80 Mm3 collapse that occurred in Mururoa in 1979. The main objective is then to carry out simulations of potential collapses in the northern zone, bearing in mind that the main difficulty lies in defining the geometry of these potential collapses. The propagation of waves over long distances is simulated by a ‘2D’ tsunami code coupled with the OpenFoam code.
Multipoint initiation of explosives. Experiments and simulations.
The design of high-performance and increasingly safe systems requires new solutions for initiating the explosives that make up their charge. One possible approach is to replace the electrical ignition of detonators with optical ignition in order to eliminate the risks associated with parasitic electrical sources.
Another possible way to improve safety is to use multipoint initiation so that the explosive only detonates when all initiation points are activated synchronously.
The objective of the postdoctoral contract will be to conduct an in-depth study of the mechanisms governing multipoint optical initiation. To this end, after conducting exhaustive bibliographic research, the candidate will propose the most relevant configurations and test them both experimentally and by performing hydrodynamic simulations using a code developed at the CEA. Understanding the phenomena involved is essential in order to be able to choose an initiation configuration suited to each need.
Development and characterization of an oxide/oxide composite material
Fiber-reinforced ceramic matrix composites (CMCs) are a class of materials that combine good specific mechanical properties (properties relative to their density) with excellent high-temperature resistance (> 1000 °C), even in an oxidizing atmosphere. They generally consist of a carbon or ceramic fiber reinforcement and a ceramic matrix (carbide or oxide).
The proposed study focuses on the development of a fabrication process for oxide/oxide CMCs with long and/or short fibers that possess suitable dielectric, thermal, and mechanical properties.
Particle-in-cell modeling of elastic collisions in dense and cold plasmas with applications to ultrafast beam-plasma and laser-plasma interactions
The particle-in-cell (PIC) method is widely employed to simulate the kinetics of plasmas subjected to intense laser or particle beams. Modern PIC codes now routinely include additional modules describing atomic physics processes, but their accuracy is questionable in relatively cold (at temperatures below a few tens of eV) and dense (close to the density of a solid) media.
This postdoctoral project aims to improve the treatment of elastic collisions in PIC simulations by drawing on transport theories derived for liquid metals and dense plasmas, i.e. by taking into account electronic degeneracy, electronic screening and atomic ordering effects. This model will be implemented into the PIC CALDER code developed at CEA. Once validated, this new model will be used in PIC simulations to examine its influence in setups involving solid targets exposed to ultraintense and ultrashort electron or laser beams.
Dimensionality reduction and meta-modelling in the field of atmospheric dispersion
Modelling and simulation of atmospheric dispersion are essential to ensure the safety of emissions emitted into the air by the authorized operation of industrial facilities and to estimate the health consequences of accidents that could affect these facilities. Over the past twenty years, physical dispersion models have undergone significant improvements in order to take into account the details of topography and land use that make real industrial environments complex. Although 3D models have seen their use increase, they have very significant calculation times, which hinders their use in multi-parametric studies and the assessment of uncertainties that require a large number of calculations. It would therefore be desirable to obtain the very precise results of current models or similar results in a much shorter time. Recently, we have developed a strategy consisting of reducing the dimension of distribution maps of an atmospheric pollutant obtained using a reference 3D physical model for different meteorological conditions, then having these maps learned by an artificial intelligence (AI) model which is then used to predict maps in other meteorological situations. The postdoctoral project will focus on complementing the research started by evaluating the performance of dimension reduction and model substitution methods already explored and by studying other methods. Applications will concern, in particular, the simulation of concentrations around an industrial production site that emits gaseous emissions into the atmosphere. The developments will aim to obtain an operational meta-modelling tool.
Preparation and characterization of an oxide/oxide composite
Fiber-reinforced ceramic matrix composites (CMCs) are a class of materials that combine good specific mechanical properties (properties relative to their density) with resistance to high temperatures (> 1000 °C), even in oxidizing atmospheres. They are typically composed of a carbon or ceramic fiber reinforcement and a ceramic matrix (carbide or oxide.
The proposed study focuses on the development of a low-matrix oxide/oxide CMC with suitable dielectric, thermal, and mechanical properties.
This study will be conducted in collaboration with several laboratories at CEA Le Ripault.