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: ,
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), doi: 10.24435/materialscloud:2019.0077/v1.


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
908 Bytes README where the content of the aiida-export file is explained in more detail, including the group names.
19.8 GiB The AiiDA-export file screening.aiida contains the first-principles molecular dynamics simulations and results trajectories as described in the README.


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.

External references

Preprint (Preprint where the data is discussed)


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

Version history:

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