Afflerbach, Benjamin T., Francis, Carter, Schultz, Lane E., Spethson, Janine, Meschke, Vanessa, Strand, Elliot, Ward, Logan, Perepezko, John H., Thoma, Dan, Voyles, Paul M., Szlufarska, Izabela, and Morgan, Dane. Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features. Retrieved from https://par.nsf.gov/biblio/10392040. Chemistry of Materials 34.7 Web. doi:10.1021/acs.chemmater.1c03542.

Afflerbach, Benjamin T., Francis, Carter, Schultz, Lane E., Spethson, Janine, Meschke, Vanessa, Strand, Elliot, Ward, Logan, Perepezko, John H., Thoma, Dan, Voyles, Paul M., Szlufarska, Izabela, & Morgan, Dane. Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features. Chemistry of Materials, 34 (7). Retrieved from https://par.nsf.gov/biblio/10392040. https://doi.org/10.1021/acs.chemmater.1c03542

Afflerbach, Benjamin T., Francis, Carter, Schultz, Lane E., Spethson, Janine, Meschke, Vanessa, Strand, Elliot, Ward, Logan, Perepezko, John H., Thoma, Dan, Voyles, Paul M., Szlufarska, Izabela, and Morgan, Dane. "Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features". Chemistry of Materials 34 (7). Country unknown/Code not available. https://doi.org/10.1021/acs.chemmater.1c03542. https://par.nsf.gov/biblio/10392040.

@article{osti_10392040,
place = {Country unknown/Code not available}, title = {Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features}, url = {https://par.nsf.gov/biblio/10392040}, DOI = {10.1021/acs.chemmater.1c03542}, abstractNote = {}, journal = {Chemistry of Materials}, volume = {34}, number = {7}, author = {Afflerbach, Benjamin T. and Francis, Carter and Schultz, Lane E. and Spethson, Janine and Meschke, Vanessa and Strand, Elliot and Ward, Logan and Perepezko, John H. and Thoma, Dan and Voyles, Paul M. and Szlufarska, Izabela and Morgan, Dane}, }