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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.05083 |
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| _version_ | 1866916063063572480 |
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| author | Akhound, Mohammad A. Boland, Tara M. Sauer, Mikkel O. Batzill, Matthias Bokinala, Moses A. Canulescu, Stela Gogotsi, Yury Hofmann, Philip Kis, Andras Lu, Jiong Michely, Thomas Raza, Søren Ren, Wencai Robinson, Joshua A. Sofer, Zdenek Teng, Jing H. Ulstrup, Søren Zhao, Meng Zhao, Xiaoxu Mortensen, Jens J. Olsen, Thomas Thygesen, Kristian S. |
| author_facet | Akhound, Mohammad A. Boland, Tara M. Sauer, Mikkel O. Batzill, Matthias Bokinala, Moses A. Canulescu, Stela Gogotsi, Yury Hofmann, Philip Kis, Andras Lu, Jiong Michely, Thomas Raza, Søren Ren, Wencai Robinson, Joshua A. Sofer, Zdenek Teng, Jing H. Ulstrup, Søren Zhao, Meng Zhao, Xiaoxu Mortensen, Jens J. Olsen, Thomas Thygesen, Kristian S. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05083 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Large-scale Integration of Experimental and Computational Data for 2D Materials Akhound, Mohammad A. Boland, Tara M. Sauer, Mikkel O. Batzill, Matthias Bokinala, Moses A. Canulescu, Stela Gogotsi, Yury Hofmann, Philip Kis, Andras Lu, Jiong Michely, Thomas Raza, Søren Ren, Wencai Robinson, Joshua A. Sofer, Zdenek Teng, Jing H. Ulstrup, Søren Zhao, Meng Zhao, Xiaoxu Mortensen, Jens J. Olsen, Thomas Thygesen, Kristian S. Materials Science 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. |
| title | Large-scale Integration of Experimental and Computational Data for 2D Materials |
| topic | Materials Science |
| url | https://arxiv.org/abs/2603.05083 |