Transport mechanism in Lithium thiophosphate*

Lithium ortho-thiophosphate (Li₃PS₄) has emerged as a promising candidate for solid-state-electrolyte batteries. The microscopic mechanisms of Li-ion transport in Li₃PS₄ are, still, far from being fully understood, and no computational work has computed the thermal conductivity at DFT level.

In this talk, I will show how we build machine learning potentials targeting state-of-the-art DFT references (PBEsol, SCAN, and PBE0), to study the electrical and thermal conductivity of all the known phases of Li₃PS₄ (α, β and γ), for large system sizes and timescales.

I will discuss the physical origin of the observed superionic behaviour of Li₃PS_4: the activation of PS₄ flipping drives a structural phase transition to a highly conductive phase, characterised by an enhancement of Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. I will show the effect of the phase transition on both the electrical and thermal conductivity. We finally elucidate the role of inter-ionic dynamical correlations in charge transport, by highlighting the failure of the Nernst-Einstein approximation to estimate the electrical conductivity.

Our results show a dependence on the target DFT reference, with PBE0 yielding the best quantitative agreement with experimental measurements.