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O: Fachverband Oberflächenphysik

O 83: Frontiers of Electronic Structure Theory: Focus on Artificial Intelligence Applied to Real Materials 4

O 83.7: Vortrag

Freitag, 9. September 2022, 12:00–12:15, S054

Predicting hot electrons free energies from ground-state data — •Chiheb Ben Mahmoud, Federico Grasselli, and Michele Ceriotti — EPFL, Lausanne, Switzerland

Machine-learning potentials, while extremely successful in describing the stability of condensed phases, are usually trained on ground-state electronic-structure calculations depending exclusively on the atomic positions and ignoring the electronic temperature. Hence, they are limited in their ability to describe hot electrons. We introduce a rigorous framework to calculate the finite-temperature electron free energy based exclusively on ground-state total energy and electronic density of states, while allowing to sample on-the-fly the electronic free energy at any temperature [1]. Our physically-motivated approach facilitates modeling material properties in extreme conditions with a fraction of the usual cost. We demonstrate it by computing the equation of state and heat capacity of hydrogen in planetary conditions. This approach demonstrates the impact of a universal model describing structural and electronic properties inexpensively and its ability to enable more accurate and predictive materials modeling and design.

[1]: C Ben Mahmoud, F Grasselli, M Ceriotti*- arXiv preprint arXiv:2205.05591, 2022