Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds
DownloadPublished version (3.430Mb)
Publisher with Creative Commons License
Publisher with Creative Commons License
Creative Commons Attribution
Terms of use
Metadata
Show full item recordDate issued
2021Department
Massachusetts Institute of Technology. Department of Materials Science and EngineeringJournal
Chemistry of Materials
Publisher
American Chemical Society (ACS)
Citation
Georgescu, Alexandru B, Ren, Peiwen, Toland, Aubrey R, Zhang, Shengtong, Miller, Kyle D et al. 2021. "Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds." Chemistry of Materials, 33 (14).
Version: Final published version