High-throughput computational screening for solid-state Li-ion conductors
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{
"revision": 7,
"id": "256",
"created": "2020-05-12T13:53:26.890402+00:00",
"metadata": {
"doi": "10.24435/materialscloud:2019.0077/v1",
"status": "published",
"title": "High-throughput computational screening for solid-state Li-ion conductors",
"mcid": "2019.0077/v1",
"license_addendum": "",
"_files": [
{
"description": "README where the content of the aiida-export file is explained in more detail, including the group names.",
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"checksum": "md5:3adef433ac13a114c8d9d8f95571d917"
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{
"description": "The AiiDA-export file screening.aiida contains the first-principles molecular dynamics simulations and results trajectories as described in the README.",
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"owner": 381,
"_oai": {
"id": "oai:materialscloud.org:256"
},
"keywords": [
"first-principles molecular dynamics",
"Li-ion conductors",
"solid-state electrolytes",
"computational high-throughput screening",
"MARVEL/Inc1 ",
"BIG-MAP"
],
"conceptrecid": "255",
"is_last": false,
"references": [
{
"type": "Preprint",
"doi": "",
"url": "https://arxiv.org/abs/1909.00623",
"comment": "Preprint where the data is discussed",
"citation": "L. Kahle, A. Marcolongo, N. Marzari, arXiv:1909.00623 [cond-mat], September 2019"
},
{
"type": "Journal reference",
"doi": "10.1039/C9EE02457C",
"url": "https://pubs.rsc.org/en/content/articlelanding/2020/ee/c9ee02457c",
"comment": "Paper in which the method and data are described",
"citation": "L. Kahle, A. Marcolongo, N. Marzari, Energy & Environmental Science 13, 928-948 (2020)"
}
],
"publication_date": "Oct 28, 2019, 00:00:00",
"license": "Creative Commons Attribution 4.0 International",
"id": "256",
"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. ",
"version": 1,
"contributors": [
{
"email": "leonid.kahle@epfl.ch",
"affiliations": [
"Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"
],
"familyname": "Kahle",
"givennames": "Leonid"
},
{
"affiliations": [
"Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"
],
"familyname": "Marcolongo",
"givennames": "Aris"
},
{
"email": "nicola.marzari@epfl.ch",
"affiliations": [
"Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015 Lausanne, Switzerland"
],
"familyname": "Marzari",
"givennames": "Nicola"
}
],
"edited_by": 98
},
"updated": "2024-04-26T16:23:46.976058+00:00"
}