arXiv subjects

Benoit Sklénard

Publications and source records attributed to Benoit Sklénard.

3 recordsLinked to original sources

arXiv2026

Critical role of phase-dependent properties in modeling photothermal sintering of LiCoO2 cathodes

Photothermal (photonic) sintering crystallizes as-deposited amorphous LiCoO2 (LCO) cathodes for solid-state thin-film batteries using millisecond, surface-localized heating. However, process design often relies on 1D models with phase-averaged, temperature-independent properties, which can mispredict peak temperatures and thermal damage margins. Here we develop a multiscale, data-driven framework that provides phase- and grain size-resolved thermophysical inputs for stoichiometric LCO. We train an Allegro neural network potential with near-ab initio accuracy, enabling Green-Kubo calculations of thermal conductivity for crystalline and amorphous phases. The low, weakly density-dependent conductivity of amorphous LCO motivates its use as an effective intergranular phase in a thin-interface model that reproduces observed grain-size-dependent thermal transport. Combined with measured wavelength-resolved optical properties in 1D multiphysics simulations, we show amorphous LCO absorbs more strongly and reaches higher peak temperatures than crystalline LCO; thus crystalline, constant-property models systematically overestimate safe operating windows.

cond-mat.mtrl-sci↗

arXiv2025

Revisiting the Extraction of Coupling Strength for Polaron Hopping from $ab~initio$ Approach

Accurately determining the coupling strength between polaron states is essential to describe charge-hopping transport in materials. In this work, we revisit methodologies to extract coupling strengths using ab initio approaches. Our findings underscore the critical role of incorporating anharmonic effects in the model Hamiltonian when analyzing total energy variations along reaction coordinates. Furthermore, we demonstrate that coupling strength extraction based on total energy calculated from ab initio approaches is fundamentally limited due to the stabilization of diabatic states, which do not involve coupling strength. We demonstrate that such limitation exists in both DFT+U and HSE hybrid functionals, which are widely used in the study of polaron transport. Instead, we suggest extracting coupling strength directly from the electronic structure of a system in neutral conditions. The neutral condition avoids overestimating coupling strength due to additional energy splitting between bonding and anti-bonding states from the charging energy. This study highlights the limitations of existing methods and introduces a robust framework for accurately extracting coupling parameters, paving the way for improved modeling of charge transport in complex materials.

cond-mat.mtrl-sci↗

arXiv2024

Equivariant graph neural network interatomic potential for Green-Kubo thermal conductivity in phase change materials

Thermal conductivity is a fundamental material property that plays an essential role in technology, but its accurate evaluation presents a challenge for theory. In this work, we demonstrate the application of $E(3)$-equivariant neutral network interatomic potentials within Green-Kubo formalism to determine the lattice thermal conductivity in amorphous and crystalline materials. We apply this method to study the thermal conductivity of germanium telluride (GeTe) as a prototypical phase change material. A single deep learning interatomic potential is able to describe the phase transitions between the amorphous, rhombohedral and cubic phases, with critical temperatures in good agreement with experiments. Furthermore, this approach accurately captures the pronounced anharmonicity that is present in GeTe, enabling precise calculations of the thermal conductivity. In contrast, the Boltzmann transport equation including only three-phonon processes tends to overestimate the thermal conductivity by approximately a factor of 2 in the crystalline phases.

cond-mat.mtrl-sci↗