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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:vg-ya [version v2]

Publication date: Apr 26, 2024

How to cite this record

Leonid Kahle, Aris Marcolongo, Nicola Marzari, High-throughput computational screening for solid-state Li-ion conductors, Materials Cloud Archive 2024.65 (2024), https://doi.org/10.24435/materialscloud:vg-ya


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. Update April 2024: Files are added that facilitate the Materials Cloud Archive OPTIMADE service to serve the structural data of this Archive entry via an OPTIMADE API. The molecular dynamics trajectories are served as individual structures per time-step.

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File name Size Description
908 Bytes README where the content of the aiida-export file is explained in more detail, including the group names.
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.
7.9 GiB JSON Lines file containing the data served by the OPTIMADE API.
238 Bytes Configuration file for the Materials Cloud Archive OPTIMADE service.


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)


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