High-throughput computational screening for solid-state Li-ion conductors

DOI

We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.

Identifier
DOI https://doi.org/10.24435/materialscloud:2019.0077/v1
Related Identifier https://arxiv.org/abs/1909.00623
Related Identifier https://doi.org/10.1039/C9EE02457C
Related Identifier https://pubs.rsc.org/en/content/articlelanding/2020/ee/c9ee02457c
Related Identifier https://renkulab.io/projects/new?data=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
Related Identifier https://archive.materialscloud.org/communities/mcarchive
Related Identifier https://doi.org/10.24435/materialscloud:jk-9v
Metadata Access https://archive.materialscloud.org/oai2d?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:256
Provenance
Creator Kahle, Leonid; Marcolongo, Aris; Marzari, Nicola
Publisher Materials Cloud
Contributor Kahle, Leonid; Marzari, Nicola
Publication Year 2019
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type info:eu-repo/semantics/other
Format text/plain; application/octet-stream; text/markdown
Discipline Materials Science and Engineering