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

Leonid Kahle1*, Aris Marcolongo1, Nicola Marzari1*

1 Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland

* Corresponding authors emails: leonid.kahle@epfl.ch, nicola.marzari@epfl.ch
DOI10.24435/materialscloud:2019.0077/v1 [version v1]

Publication date: Oct 28, 2019

How to cite this record

Leonid Kahle, Aris Marcolongo, Nicola Marzari, High-throughput computational screening for solid-state Li-ion conductors, Materials Cloud Archive 2019.0077/v1 (2019), https://doi.org/10.24435/materialscloud:2019.0077/v1

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.

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Files

File name Size Description
README.txt
MD5md5:3adef433ac13a114c8d9d8f95571d917
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/)
19.8 GiB The AiiDA-export file screening.aiida contains the first-principles molecular dynamics simulations and results trajectories as described in the README.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Preprint (Preprint where the data is discussed)
Journal reference (Paper in which the method and data are described)

Keywords

first-principles molecular dynamics Li-ion conductors solid-state electrolytes computational high-throughput screening MARVEL/Inc1 BIG-MAP

Version history:

2019.0077/v1 (version v1) [This version] Oct 28, 2019 DOI10.24435/materialscloud:2019.0077/v1