Seebeck coefficient of ionic conductors from Bayesian regression analysis

Autor:	Drigo, Enrico, Baroni, Stefano, Pegolo, Paolo
Rok vydání:	2024
Předmět:	Condensed Matter - Materials Science
Druh dokumentu:	Working Paper
Popis:	We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the probability distribution of the off-diagonal elements of a Wishart matrix, we develop a consistent and unbiased estimator for the Seebeck coefficient whose statistical uncertainty can be arbitrarily reduced in the long-time limit. To validate the effectiveness of our method, we benchmark it against extensive equilibrium molecular dynamics simulations conducted on molten $\mathrm{CsF}$ using empirical force fields. We then employ this procedure to calculate the Seebeck coefficient of molten $\mathrm{NaCl}$, $\mathrm{KCl}$ and $\mathrm{LiCl}$ using neural-network force fields trained on ab initio data over a range of pressure-temperature conditions. Comment: 9 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.04873 Zobrazit plný text záznamu View this record from Arxiv