Recent Progress of the Computational 2D Materials Database (C2DB)

TL;DR

The C2DB is an extensive, open database of over 4000 2D materials, now expanded with new materials, properties, and improved methodologies, serving as a vital resource for 2D materials research.

Contribution

This work updates the C2DB with new materials, properties, and computational methods, enhancing its scope and utility for 2D materials science.

Findings

Addition of hundreds of new 2D materials and properties.

Refinements in classification and computational techniques.

Demonstration of Gaussian process regression for property prediction.

Abstract

The C2DB is a highly curated open database organizing a wealth of computed properties for more than 4000 atomically thin two-dimensional (2D) materials. Here we report on new materials and properties that were added to the database since its first release in 2018. The set of new materials comprise several hundred monolayers exfoliated from experimentally known layered bulk materials, (homo)bilayers in various stacking configurations, native point defects in semiconducting monolayers, and chalcogen/halogen Janus monolayers. The new properties include exfoliation energies, Bader charges, spontaneous polarisations, Born charges, infrared polarisabilities, piezoelectric tensors, band topology invariants, exchange couplings, Raman- and second harmonic generation spectra. We also describe refinements of the employed material classification schemes, upgrades of the computational methodologies used for property evaluations, as well as significant enhancements of the data documentation and provenance. Finally, we explore the performance of Gaussian process-based regression for efficient prediction of mechanical and electronic materials properties. The combination of open access, detailed documentation, and extremely rich materials property data sets make the C2DB a unique resource that will advance the science of atomically thin materials.