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Large-Scale Integration of Experimental and Computational Data for 2D Materials
Journal article   Open access   Peer reviewed

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

M Amin Akhound, Tara M Boland, Mikkel O Sauer, Matthias Batzill, B Moses Abraham, Stela Canulescu, Yury Gogotsi, Philip Hofmann, Andras Kis, Jiong Lu, …
ACS nano, Forthcoming
07 Apr 2026
DOI: https://doi.org/10.1021/acsnano.6c01514
PMID: 41945467
url
https://doi.org/10.1021/acsnano.6c01514View
Published, Version of Record (VoR) Open

Abstract

data-driven synthesis literature mining density functional theory (DFT) database infrastructure two-dimensional materials experimental data
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, highlight its support for community uploads, illustrate how it can be used to generate scientific insight, and introduce a hierarchical classification of the known set of 2D materials. Our work supports the integration and cross-fertilization of experimental and theoretical knowledge and contributes to data-driven and predictive synthesis of 2D materials.

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