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Publication date: Oct 28, 2019
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.
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File name | Size | Description |
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README.txt
MD5md5:3adef433ac13a114c8d9d8f95571d917
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908 Bytes | README where the content of the aiida-export file is explained in more detail, including the group names. |
screening.aiida
MD5md5:99de1623cf3f1b73e0055e6fe0e45ebe
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
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19.8 GiB | The AiiDA-export file screening.aiida contains the first-principles molecular dynamics simulations and results trajectories as described in the README. |
2024.65 (version v2) | Apr 26, 2024 | DOI10.24435/materialscloud:vg-ya |
2019.0077/v1 (version v1) [This version] | Oct 28, 2019 | DOI10.24435/materialscloud:2019.0077/v1 |