Georgescu, Alexandru B., et al. "Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds." Chemistry of Materials, vol. 33, no. 14, Jul. 2021. https://doi.org/10.1021/acs.chemmater.1c00905
Georgescu, Alexandru B., Ren, Peiwen, Toland, Aubrey R., Zhang, Shengtong, Miller, Kyle D., Apley, Daniel W., Olivetti, Elsa A., Wagner, Nicholas, & Rondinelli, James M. (2021). Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds. Chemistry of Materials, 33(14). https://doi.org/10.1021/acs.chemmater.1c00905
Georgescu, Alexandru B., Ren, Peiwen, Toland, Aubrey R., et al., "Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds," Chemistry of Materials 33, no. 14 (2021), https://doi.org/10.1021/acs.chemmater.1c00905
@article{osti_1805317,
author = {Georgescu, Alexandru B. and Ren, Peiwen and Toland, Aubrey R. and Zhang, Shengtong and Miller, Kyle D. and Apley, Daniel W. and Olivetti, Elsa A. and Wagner, Nicholas and Rondinelli, James M.},
title = {Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds},
annote = {Not Available},
doi = {10.1021/acs.chemmater.1c00905},
url = {https://www.osti.gov/biblio/1805317},
journal = {Chemistry of Materials},
issn = {ISSN 0897-4756},
number = {14},
volume = {33},
place = {United States},
publisher = {American Chemical Society},
year = {2021},
month = {07}}
Yao, Benzhen; Kuznetsov, Vladimir L.; Xiao, Tiancun
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 378, Issue 2180https://doi.org/10.1098/rsta.2020.0213