ArticleACS nano2026
Large-Scale Integration of Experimental and Computational Data for 2D Materials.
Article in ACS nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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0 citing papers in PubMed.
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Authors and funding
22 authors.
Funding
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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, 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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