Large-scale Integration of Experimental and Computational Data for 2D Materials

TL;DR

This paper introduces X2DB, an open database integrating experimental and computational data on 2D materials, facilitating comprehensive analysis and discovery of new materials through community contributions.

Contribution

It establishes a large, integrated database linking experimental and computational data for 2D materials, enabling data-driven research and predictive synthesis.

Findings

Identified 370 unique 2D materials from literature

Linked experimental data with computational databases

Supports community uploads and hierarchical classification

Abstract

The past decade has seen rapid growth in the number of experimentally realized two-dimensional (2D) materials with diverse chemical and physical properties. However, information on their crystal structure, synthesis routes, and measured or predicted properties, remains scattered across thousands of publications. Here we consolidate this fragmented knowledge by establishing X2DB - an open infrastructure that integrates experimental and computational data on 2D materials. Using extensive literature mining and direct community uploads, we identify 370 unique 2D materials that have been realized in monolayer or few-layer form, and link them to their digital counterparts in computational databases, enabling consistent ab initio characterization of their properties across monolayer, bilayer and bulk forms. We describe the structure and content of the database highlighting its support for community uploads, illustrate how it can be used to generate new scientific insight and introduce a hierarchical classification of the known set of 2D materials. Our work provides a foundation for the integration and cross-fertilization of experimental and theoretical knowledge, opening new avenues for data-driven, predictive synthesis of novel 2D materials.