MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art

dc.contributor.authorHu, Jianjun
dc.contributor.authorStefanov, Stanislav
dc.contributor.authorSong, Yuqi
dc.contributor.authorOmee, Sadman Sadeed
dc.contributor.authorLouis, Steph-Yves
dc.contributor.authorSiriwardane, Edirisuriya M. Dilanga
dc.contributor.authorZhao, Yong
dc.contributor.authorWei, Lai
dc.date.accessioned2022-10-19T04:44:50Z
dc.date.available2022-10-19T04:44:50Z
dc.date.issued2022
dc.descriptionThe views, perspectives, and content do not necessarily represent the official views of the NSF. We appreciate the help from Xerrak Agha, Daniel Varivoda, Sourin Dey for proofreading.en_US
dc.description.abstractThe availability and easy access of large-scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and generative design of materials. However, the lack of user-friendly materials informatics web servers has severely constrained the wide adoption of such tools in the daily practice of materials screening, tinkering, and design space exploration by materials scientists. Herein we first survey current materials informatics web apps and then propose and develop MaterialsAtlas.org, a web-based materials informatics toolbox for materials discovery, which includes a variety of routinely needed tools for exploratory materials discovery, including material’s composition and structure validity check (e.g. charge neutrality, electronegativity balance, dynamic stability, Pauling rules), materials property prediction (e.g. band gap, elastic moduli, hardness, and thermal conductivity), search for hypothetical materials, and utility tools. These user-friendly tools can be freely accessed at http://www.materialsatlas.org. We argue that such materials informatics apps should be widely developed by the community to speed up materials discovery processes.en_US
dc.description.sponsorshipThe research reported in this work was supported in part by National Science Foundation under the grant and 1940099, 1905775, and OIA-1655740.en_US
dc.identifier.citationHu, J., Stefanov, S., Song, Y., Omee, S. S., Louis, S.-Y., Siriwardane, E. M., Zhao, Y., & Wei, L. (2022). Materialsatlas.org: A materials informatics web app platform for materials discovery and survey of state-of-the-art. Npj Computational Materials, 8(1). https://doi.org/10.1038/s41524-022-00750-6en_US
dc.identifier.otherhttps://doi.org/10.1038/s41524-022-00750-6
dc.identifier.urihttp://archive.cmb.ac.lk/handle/70130/6918
dc.language.isoenen_US
dc.publisherNPJ Computational Materialsen_US
dc.subjectMachine Learningen_US
dc.subjectDeep Learningen_US
dc.subjectMaterials Scienceen_US
dc.subjectMaterials Informaticsen_US
dc.titleMaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-arten_US
dc.typeArticleen_US

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