<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Kahle, Leonid</dc:creator> <dc:creator>Marcolongo, Aris</dc:creator> <dc:creator>Marzari, Nicola</dc:creator> <dc:date>2019-10-28</dc:date> <dc:description>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. </dc:description> <dc:identifier>https://archive.materialscloud.org/record/2019.0077/v1</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:2019.0077/v1</dc:identifier> <dc:identifier>mcid:2019.0077/v1</dc:identifier> <dc:identifier>oai:materialscloud.org:256</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>first-principles molecular dynamics</dc:subject> <dc:subject>Li-ion conductors</dc:subject> <dc:subject>solid-state electrolytes</dc:subject> <dc:subject>computational high-throughput screening</dc:subject> <dc:subject>MARVEL/Inc1 </dc:subject> <dc:subject>BIG-MAP</dc:subject> <dc:title>High-throughput computational screening for solid-state Li-ion conductors</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>