arXiv subjects

Johann Bouchet

Publications and source records attributed to Johann Bouchet.

6 recordsLinked to original sources

arXiv2026

Fully anharmonic calculations of the free energy of migration of point defects in UO2 and PuO2

Calculating diffusion rates of point defects in materials typically relies on the harmonic approximation to estimate migration free energies. However, anharmonic effects can have a large impact on diffusion properties, and explicitly accounting for them is usually computationally demanding and difficult to achieve in practice. In this work, we investigate the role of anharmonic effects on defect migration in UO2 and PuO2 using the potential of average force integration (PAFI) method. Fully anharmonic migration free energies are computed for several cation and anion defect types, using the Cooper-Rushton-Grimes (CRG) potential and a recently developed machine learning spectral neighbour analysis potential (SNAP) for UO2. Results are systematically compared to harmonic estimates based on attempt frequencies and the Debye approximation. Our results reveal that the validity of the harmonic approximation strongly depends on the defect type and the underlying potential, with significant deviations observed in several cases. In particular, defect migration barriers are found to decrease strongly with increasing temperature (up to 1 eV between 0 and 1200 K), and anharmonic contributions can substantially modify migration entropies and, consequently, diffusion coefficients. Comparing defect migration in UO2 and PuO2 using the CRG potential reveals that PuO2 has lower migration enthalpies at 0~K for all considered defects, but this is compensated by higher attempt frequencies, resulting in similar overall jump frequencies in UO2 and PuO2. These findings provide insight into the limitations of commonly used approximations and highlight the importance of anharmonic effects for predictive modeling of diffusion in nuclear fuels as well as in other classes of materials.

cond-mat.mtrl-sci↗

arXiv2025

Abinit 2025: New Capabilities for the Predictive Modeling of Solids and Nanomaterials

Abinit is a widely used scientific software package implementing density functional theory and many related functionalities for excited states and response properties. This paper presents the novel features and capabilities, both technical and scientific, which have been implemented over the past 5 years. This evolution occurred in the context of evolving hardware platforms, high-throughput calculation campaigns, and the growing use of machine learning to predict properties based on databases of first principles results. We present new methodologies for ground states with constrained charge, spin or temperature; for density functional perturbation theory extensions to flexoelectricity and polarons; and for excited states in many-body frameworks including GW, dynamical mean field theory, and coupled cluster. Technical advances have extended abinit high-performance execution to graphical processing units and intensive parallelism. Second principles methods build effective models on top of first principles results to scale up in length and time scales. Finally, workflows have been developed in different community frameworks to automate \abinit calculations and enable users to simulate hundreds or thousands of materials in controlled and reproducible conditions.

cond-mat.mtrl-sci↗

arXiv2024

Machine learning assisted canonical sampling (MLACS)

The acceleration of material property calculations while maintaining ab initio accuracy (1 meV/atom) is one of the major challenges in computational physics. In this paper, we introduce a Python package enhancing the computation of (finite temperature) material properties at the ab initio level using machine learning interatomic potentials (MLIP). The Machine-Learning Assisted Canonical Sampling (MLACS) method, grounded in a self-consistent variational approach, iteratively trains a MLIP using an active learning strategy in order to significantly reduce the computational cost of ab initio simulations. MLACS offers a modular and user-friendly interface that seamlessly integrates Density Functional Theory (DFT) codes, MLIP potentials, and molecular dynamics packages, enabling a wide range of applications, while maintaining a near-DFT accuracy. These include sampling the canonical ensemble of a system, performing free energy calculations, transition path sampling, and geometry optimization, all by utilizing surrogate MLIP potentials, in place of ab initio calculations. This paper provides a comprehensive overview of the theoretical foundations and implementation of the MLACS method. We also demonstrate its accuracy and efficiency through various examples, showcasing the capabilities of the MLACS package.

cond-mat.mtrl-sci↗

arXiv2022

Ab initio Canonical Sampling based on Variational Inference

Finite temperature calculations, based on ab initio molecular dynamics (AIMD) simulations, are a powerful tool able to predict material properties that cannot be deduced from ground state calculations. However, the high computational cost of AIMD limits its applicability for large or complex systems. To circumvent this limitation we introduce a new method named Machine Learning Assisted Canonical Sampling (MLACS), which accelerates the sampling of the Born--Oppenheimer potential surface in the canonical ensemble. Based on a self-consistent variational procedure, the method iteratively trains a Machine Learning Interatomic Potential to generate configurations that approximate the canonical distribution of positions associated with the ab initio potential energy. By proving the reliability of the method on anharmonic systems, we show that the method is able to reproduce the results of AIMD with an ab initio accuracy at a fraction of its computational cost.

cond-mat.mtrl-sci↗

arXiv2022

Structure and Phase Transitions of Metastable Hexagonal Uranium Thin Films

We report a simple technique for the synthesis of uniaxially textured, metastable hexagonal close-packed-like uranium thin films with thicknesses between 175-2800 Å. The initial structure and texture of the layers have been studied via X-ray diffraction and reflectivity and the time-dependent transitions of the samples into various orientations of orthorhombic $α$-U have been mapped by similar techniques. The final crystallographic orientations of each system and the timescales on which the transitions occur are found to depend on the lattice parameters of the original layer. The absence of the $α$-U (001) orientation in the transition products suggests that the transitions in these layers are mediated by mechanisms other than the [110] transverse acoustic phonon mode previously suggested for the cubic $γ$-U(110) to hcp-U(00.1) to $α$-U(001) displacive phase transition. Alternative transition pathways are discussed.

cond-mat.mtrl-sci↗

arXiv2005

Ab-initio Gutzwiller method: first application to Plutonium

Except for small molecules, it is impossible to solve many electrons systems without imposing severe approximations. If the configuration interaction approaches (CI) or Coupled Clusters techniques \cite{FuldeBook} are applicable for molecules, their generalization for solids is difficult. For materials with a kinetic energy greater than the Coulomb interaction, calculations based on the density functional theory (DFT), associated with the local density approximation (LDA) \cite{Hohenberg64, Kohn65} give satisfying qualitative and quantitative results to describe ground state properties. These solids have weakly correlated electrons presenting extended states, like $sp$ materials or covalent solids. The application of this approximation to systems where the wave functions are more localized ($d$ or $f$-states) as transition metals oxides, heavy fermions, rare earths or actinides is more questionable and can even lead to unphysical results : for example, insulating FeO and CoO are predicted to be metalic by the DFT-LDA...

cond-mat.str-el↗