arXiv subjects

Clovis Lapointe

Publications and source records attributed to Clovis Lapointe.

3 recordsLinked to original sources

arXiv2026

Systematic and accurate anharmonic formation free energies of metastable defects via a constrained Bayesian Adaptive Biasing Force framework

Computing the formation free energies of metastable defects at finite temperature remains challenging due to anharmonicity, the multiplicity of basins and the frequent occurrence of migration events. Using the previously introduced constrained Bayesian Adaptive Biasing Force method (BABFc), we establish a practical thermodynamic integration framework for computing restricted anharmonic formation free energies associated with individual metastable defect basins. We demonstrate that BABFc can be exploited as a robust, systematic and numerically efficient tool for addressing a long standing bottleneck in atomistic materials science: the finite temperature thermodynamic characterization of metastable defects in complex, highly anharmonic energy landscapes. The proposed workflow requires only a reference local minimum and a confinement strategy and does not rely on defect specific collective variables. It therefore provides a general route to assign well-defined free energies to individual metastable basins, even when these basins are separated by low barriers and embedded in a dense landscape of competing configurations. In this setting, BABFc enables stable, bias corrected free energy estimates with statistical accuracies at the meV/atom level and a very low failure rate, including for systems containing approximately one thousand atoms. We demonstrate this capability through thousands of independent free energy calculations covering hundreds of four-interstitial and four-vacancy configurations in bcc $\alpha$-Fe over a broad temperature range, using both a traditional empirical potential and a data driven force field.

cond-mat.mtrl-sci↗

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

Agnostic calculation of atomic free energies with the descriptor density of states

We present a new method to evaluate vibrational free energies of atomic systems without a priori specification of an interatomic potential. Our model-agnostic approach leverages descriptors, high-dimensional feature vectors of atomic structure. The entropy of a high-dimensional density, the descriptor density of states, is accurately estimated with conditional score matching. Casting interatomic potentials into a form extensive in descriptor features, we show free energies emerge as the Legendre-Fenchel conjugate of the descriptor entropy, avoiding all high-dimensional integration. The score matching campaign requires less resources than fixed-model sampling and is highly parallel, reducing wall time to a few minutes, with tensor compression schemes allowing lightweight storage. Our model-agnostic estimator returns differentiable free energy predictions over a broad range of potential parameters in microseconds of CPU effort, allowing rapid forward and back propagation of potential variations through finite temperature simulations, long desired for uncertainty quantification and inverse design. We test predictions against thermodynamic integration calculations over a broad range of models for BCC, FCC and A15 phases of W, Mo and Fe at high homologous temperatures. Predictions pass the stringent accuracy threshold of 1-2 meV/atom (1/40-1/20 kcal/mol) for phase prediction with propagated score uncertainties robustly bounding errors. We also demonstrate targeted fine-tuning, reducing the alpha-gamma transition temperature in a non-magnetic machine learning model of Fe from 2030 K to 1063 K through back-propagation, with no additional sampling. Applications to liquids and fine-tuning foundational models are discussed along with the many problems in computational science which estimate high-dimensional integrals.

cond-mat.mtrl-sci↗