Afflerbach, Benjamin T., Schultz, Lane, Perepezko, John H., Voyles, Paul M., Szlufarska, Izabela, and Morgan, Dane. Molecular simulation-derived features for machine learning predictions of metal glass forming ability. Retrieved from https://par.nsf.gov/biblio/10297692. Computational Materials Science 199.C Web. doi:10.1016/j.commatsci.2021.110728.

Afflerbach, Benjamin T., Schultz, Lane, Perepezko, John H., Voyles, Paul M., Szlufarska, Izabela, & Morgan, Dane. Molecular simulation-derived features for machine learning predictions of metal glass forming ability. Computational Materials Science, 199 (C). Retrieved from https://par.nsf.gov/biblio/10297692. https://doi.org/10.1016/j.commatsci.2021.110728

Afflerbach, Benjamin T., Schultz, Lane, Perepezko, John H., Voyles, Paul M., Szlufarska, Izabela, and Morgan, Dane. "Molecular simulation-derived features for machine learning predictions of metal glass forming ability". Computational Materials Science 199 (C). Country unknown/Code not available. https://doi.org/10.1016/j.commatsci.2021.110728. https://par.nsf.gov/biblio/10297692.

@article{osti_10297692,
place = {Country unknown/Code not available}, title = {Molecular simulation-derived features for machine learning predictions of metal glass forming ability}, url = {https://par.nsf.gov/biblio/10297692}, DOI = {10.1016/j.commatsci.2021.110728}, abstractNote = {}, journal = {Computational Materials Science}, volume = {199}, number = {C}, author = {Afflerbach, Benjamin T. and Schultz, Lane and Perepezko, John H. and Voyles, Paul M. and Szlufarska, Izabela and Morgan, Dane}, editor = {null} }