Andolina, Christopher M., Bon, Marta, Passerone, Daniele, and Saidi, Wissam A. Robust, Multi-Length-Scale, Machine Learning Potential for Ag–Au Bimetallic Alloys from Clusters to Bulk Materials. Retrieved from https://par.nsf.gov/biblio/10417865. The Journal of Physical Chemistry C 125.31 Web. doi:10.1021/acs.jpcc.1c04403.

Andolina, Christopher M., Bon, Marta, Passerone, Daniele, & Saidi, Wissam A. Robust, Multi-Length-Scale, Machine Learning Potential for Ag–Au Bimetallic Alloys from Clusters to Bulk Materials. The Journal of Physical Chemistry C, 125 (31). Retrieved from https://par.nsf.gov/biblio/10417865. https://doi.org/10.1021/acs.jpcc.1c04403

Andolina, Christopher M., Bon, Marta, Passerone, Daniele, and Saidi, Wissam A. "Robust, Multi-Length-Scale, Machine Learning Potential for Ag–Au Bimetallic Alloys from Clusters to Bulk Materials". The Journal of Physical Chemistry C 125 (31). Country unknown/Code not available. https://doi.org/10.1021/acs.jpcc.1c04403. https://par.nsf.gov/biblio/10417865.

@article{osti_10417865,
place = {Country unknown/Code not available}, title = {Robust, Multi-Length-Scale, Machine Learning Potential for Ag–Au Bimetallic Alloys from Clusters to Bulk Materials}, url = {https://par.nsf.gov/biblio/10417865}, DOI = {10.1021/acs.jpcc.1c04403}, abstractNote = {}, journal = {The Journal of Physical Chemistry C}, volume = {125}, number = {31}, author = {Andolina, Christopher M. and Bon, Marta and Passerone, Daniele and Saidi, Wissam A.}, }