Regensburg 2022 – wissenschaftliches Programm

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MM: Fachverband Metall- und Materialphysik

MM 2: Computational Materials Modelling: Energy Materials

MM 2.7: Vortrag

Montag, 5. September 2022, 12:00–12:15, H44

High-throughput computational screening of fast Li-ion conductors — •Tushar Thakur, Loris Ercole, and Nicola Marzari — THEOS, EPFL, Switzerland

We present a high-throughput computational screening to find fast Li-ion conductors to identify promising candidate materials for application in solid-state electrolytes. Starting with ~30,000 experimental structures sourced from COD, ICSD and MPDS repositories, we performed highly automated calculations using AiiDA at the level of Density Functional Theory (DFT) to identify electronic insulators and to estimate lithium ion diffusivity using the pinball model [1] which describes the potential energy landscape of diffusing lithium at near DFT level accuracy while being orders of magnitude faster. We present the workflow where the accuracy of the pinball model is improved self-consistently and which is necessary in automatically running the thousands of required calculations and analysing their results. Promising conductors are further studied with first principles Molecular Dynamics simulations.

[1] Kahle, L. et al Modeling lithium-ion solid-state electrolytes with a pinball model. Phys. Rev. Mater. 2, 65405 (2018)