A representation-independent electronic charge density database for crystalline materials

Shen, Jimmy-Xuan; Munro, Jason M.; Horton, Matthew K.; Huck, Patrick; Dwaraknath, Shyam; Persson, Kristin A.

doi:10.1038/s41597-022-01746-z

A representation-independent electronic charge density database for crystalline materials

Journal Article · Fri Oct 28 00:00:00 EDT 2022 · Scientific Data

DOI:https://doi.org/10.1038/s41597-022-01746-z· OSTI ID:1895535

Shen, Jimmy-Xuan; Munro, Jason M.; ; ; ; Persson, Kristin A.

Abstract

In addition to being the core quantity in density-functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With the increasing prevalence of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1895535

Alternate ID(s):: OSTI ID: 1992319

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 9; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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