Liu, Chaoyi, Wang, Yuchu, Wang, Yuchi, Islam, Minhazul, Hwang, Jinwoo, Wang, Yunzhi, and Fan, Yue. Concurrent prediction of metallic glasses’ global energy and internal structural heterogeneity by interpretable machine learning. Retrieved from https://par.nsf.gov/biblio/10540576. Acta Materialia 259.C Web. doi:10.1016/j.actamat.2023.119281.

Liu, Chaoyi, Wang, Yuchu, Wang, Yuchi, Islam, Minhazul, Hwang, Jinwoo, Wang, Yunzhi, & Fan, Yue. Concurrent prediction of metallic glasses’ global energy and internal structural heterogeneity by interpretable machine learning. Acta Materialia, 259 (C). Retrieved from https://par.nsf.gov/biblio/10540576. https://doi.org/10.1016/j.actamat.2023.119281

Liu, Chaoyi, Wang, Yuchu, Wang, Yuchi, Islam, Minhazul, Hwang, Jinwoo, Wang, Yunzhi, and Fan, Yue. "Concurrent prediction of metallic glasses’ global energy and internal structural heterogeneity by interpretable machine learning". Acta Materialia 259 (C). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.actamat.2023.119281. https://par.nsf.gov/biblio/10540576.

@article{osti_10540576,
place = {Country unknown/Code not available}, title = {Concurrent prediction of metallic glasses’ global energy and internal structural heterogeneity by interpretable machine learning}, url = {https://par.nsf.gov/biblio/10540576}, DOI = {10.1016/j.actamat.2023.119281}, abstractNote = {}, journal = {Acta Materialia}, volume = {259}, number = {C}, publisher = {Elsevier}, author = {Liu, Chaoyi and Wang, Yuchu and Wang, Yuchi and Islam, Minhazul and Hwang, Jinwoo and Wang, Yunzhi and Fan, Yue}, }