Abstract

The Computational 2D Materials Database (C2DB) is a highly curated open database organising 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 spectra 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.

Highlights

  • The discovery of new materials, or new properties of known materials, to meet a specific industrial or scientific requirement, is an exciting intellectual challenge of the utmost importance for our environment and economy

  • The dynamically stable materials derived from parent bulk structures in the Inorganic Crystal Structure Database (ICSD) and Crystallography Open Database (COD) may serve as a useful subset of the Computational 2D Materials Database (C2DB) that are likely to be exfoliable from known compounds and facilitate experimental verification

  • We have documented a number of extensions and improvements of the C2DB made in the period 2018– 2020

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Summary

15 July 2021

Morten Niklas Gjerding , Alireza Taghizadeh1,2 , Asbjørn Rasmussen , Sajid Ali , Fabian Bertoldo , Thorsten Deilmann , Nikolaj Rørbæk Knøsgaard , Mads Kruse , Ask Hjorth Larsen , Simone Manti , Thomas Garm Pedersen , Urko Petralanda , Thorbjørn Skovhus , Mark Kamper Svendsen , Jens Jørgen Mortensen , Thomas Olsen.

Introduction
Method
Improved property methodology
New materials in the C2DB
New properties in the C2DB
Machine learning properties
Findings
Summary and outlook

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