Zeng, Quan, Rezaei, Shahed, Carrillo, Luis, Davidson, Rachel, Xu, Bai-Xiang, Banerjee, Sarbajit, and Ding, Yu. Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology. Retrieved from https://par.nsf.gov/biblio/10559007. iScience 27.9 Web. doi:10.1016/j.isci.2024.110822.

Zeng, Quan, Rezaei, Shahed, Carrillo, Luis, Davidson, Rachel, Xu, Bai-Xiang, Banerjee, Sarbajit, & Ding, Yu. Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology. iScience, 27 (9). Retrieved from https://par.nsf.gov/biblio/10559007. https://doi.org/10.1016/j.isci.2024.110822

Zeng, Quan, Rezaei, Shahed, Carrillo, Luis, Davidson, Rachel, Xu, Bai-Xiang, Banerjee, Sarbajit, and Ding, Yu. "Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology". iScience 27 (9). Country unknown/Code not available: Cell Press. https://doi.org/10.1016/j.isci.2024.110822. https://par.nsf.gov/biblio/10559007.

@article{osti_10559007,
place = {Country unknown/Code not available}, title = {Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology}, url = {https://par.nsf.gov/biblio/10559007}, DOI = {10.1016/j.isci.2024.110822}, abstractNote = {}, journal = {iScience}, volume = {27}, number = {9}, publisher = {Cell Press}, author = {Zeng, Quan and Rezaei, Shahed and Carrillo, Luis and Davidson, Rachel and Xu, Bai-Xiang and Banerjee, Sarbajit and Ding, Yu}, }