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Data from: 2DMatPedia, An open computational database of two-dimensional...
- figshare.com
txtUpdated Jun 2, 2023
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EmailClick to copy linkLink copiedCiteJUN ZHOU; LEI SHEN; MIGUEL DIAS COSTA; Kristin Persson; Shyue Ping Ong; Patrick Huck; YUNHAO LU; XIAOYANG MA; YIMING CHEN; HANMEI TANG; YUANPING FENG (2023). 2DMatPedia, An open computational database of two-dimensional materials from top-down and bottom-up approaches [Dataset]. http://doi.org/10.6084/m9.figshare.7699910.v3txtAvailable download formatsUnique identifierhttps://doi.org/10.6084/m9.figshare.7699910.v3Dataset updatedJun 2, 2023Dataset provided byfigshareAuthorsJUN ZHOU; LEI SHEN; MIGUEL DIAS COSTA; Kristin Persson; Shyue Ping Ong; Patrick Huck; YUNHAO LU; XIAOYANG MA; YIMING CHEN; HANMEI TANG; YUANPING FENGLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionWe present a large dataset of 2D materials, with more than 6,000 monolayer structures, obtained from both top-down and bottom-up discovery procedures. First, we screened all bulk materials in the database of Materials Project for layered structures by a topology-based algorithm and theoretically exfoliate them into monolayers. Then, we generated new 2D materials by chemical substitution of elements in known 2D materials by others from the same group in the periodic table. The structural, electronic and energetic properties of these 2D materials are consistently calculated, to provide a starting point for further material screening, data mining, data analysis and artificial intelligence applications.
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JARVIS_2DMatPedia
- huggingface.co
ShareFacebookTwitterEmailClick to copy linkLink copiedCiteColabFit, JARVIS_2DMatPedia [Dataset]. https://huggingface.co/datasets/colabfit/JARVIS_2DMatPediaDataset authored and provided byColabFitLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionCite this dataset
Zhou, J., Shen, L., Costa, M. D., Persson, K. A., Huck, S. P. O. "., Lu, Y., Ma, X., Chen, Y., Tang, H., and Feng, Y. P. JARVIS 2DMatPedia. ColabFit, 2023. https://doi.org/10.60732/a2df077f
View on the ColabFit Exchangehttps://materials.colabfit.org/id/DS_hdv6si8yu2mv_0
Dataset NameJARVIS 2DMatPedia
DescriptionThe JARVIS-2DMatPedia dataset is part of the joint automated repository for various integrated simulations (JARVIS)… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/JARVIS_2DMatPedia.
twodmatpd.json
- figshare.com
zipUpdated Mar 13, 2021ShareFacebookTwitterEmailClick to copy linkLink copiedCiteKamal Choudhary (2021). twodmatpd.json [Dataset]. http://doi.org/10.6084/m9.figshare.14205083.v1zipAvailable download formatsUnique identifierhttps://doi.org/10.6084/m9.figshare.14205083.v1Dataset updatedMar 13, 2021Dataset provided byfigshareAuthorsKamal ChoudharyLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescription2DMatPedia in JARVIS format (https://www.nature.com/articles/s41597-019-0097-3)
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FacebookTwitterEmailData from: 2DMatPedia, An open computational database of two-dimensional materials from top-down and bottom-up approaches
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
We present a large dataset of 2D materials, with more than 6,000 monolayer structures, obtained from both top-down and bottom-up discovery procedures. First, we screened all bulk materials in the database of Materials Project for layered structures by a topology-based algorithm and theoretically exfoliate them into monolayers. Then, we generated new 2D materials by chemical substitution of elements in known 2D materials by others from the same group in the periodic table. The structural, electronic and energetic properties of these 2D materials are consistently calculated, to provide a starting point for further material screening, data mining, data analysis and artificial intelligence applications.