Abstract
Driven by the big data science, material informatics has attracted enormous research interests recently along with many recognized achievements. To acquire knowledge of materials by previous experience, both feature descriptors and databases are essential for training machine learning (ML) models with high accuracy. In this regard, the electronic charge density ρ(r), which in principle determines the properties of materials at their ground state, can be considered as one of the most appropriate descriptors. However, the systematic electronic charge density ρ(r) database of inorganic materials is still in its infancy due to the difficulties in collecting raw data in experiment and the expensive first-principles based computational cost in theory. Herein, a real space electronic charge density ρ(r) database of 17,418 cubic inorganic materials is constructed by performing high-throughput density functional theory calculations. The displayed ρ(r) patterns show good agreements with those reported in previous studies, which validates our computations. Further statistical analysis reveals that it possesses abundant and diverse data, which could accelerate ρ(r) related machine learning studies. Moreover, the electronic charge density database will also assists chemical bonding identifications and promotes new crystal discovery in experiments.
Highlights
Background & SummaryThe electronic charge density (ECD) in real space, denoted as ρ(r), is a basic yet informative observable quantity of materials in physics
Dated back to 1964, density functional theory (DFT) was discovered by Hohenberg and Kohn, who proved that the properties of materials at their ground state can be entirely and exclusively determined by ρ(r)[1,2]
Because of the expensive yet limited computational resources, we focus on materials in cubic symmetry where the ρ(r) are more efficient to calculate
Summary
The electronic charge density (ECD) in real space, denoted as ρ(r), is a basic yet informative observable quantity of materials in physics. Dated back to 1964, density functional theory (DFT) was discovered by Hohenberg and Kohn, who proved that the properties of materials at their ground state can be entirely and exclusively determined by ρ(r)[1,2] This theorem has been widely used and applied to multiple physical systems from microscale molecules to macroscale crystals, significantly accelerating our understanding and manipulation of the nature of the world. The flaw of such technique resides in collecting raw and accurate metadata of inorganic materials, especially for those high-symmetric dense solids with extended structures and heavy atoms This is because, in such materials, the scattering from the valence electrons is minute compared to that from core electrons. It will provides good opportunities to crystal engineering and gives better guidance for the chemical bonding identifications in experiments
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