@misc{indiciaed17f6e3cb0dc,
  title = {Development of Machine-Learned Interatomic Potentials to Predict Structure, Transport, and Reactivity in Platinum-Based Fuel Cells},
  author = {Fazel, Kamron [Rensselaer Polytechnic Institute, Troy, NY (United States)] and Brown, Sam [New Mexico State University, Las Cruces, NM (United States)] and Clary, Jacob [National Laboratory of the Rockies (NLR), Golden, CO (United States)] (ORCID:000000026144759X) and Bose, Pritom [Rensselaer Polytechnic Institute, Troy, NY (United States)] and Karimitari, Nima [University of South Carolina, Columbia, SC (United States)] and Frischknecht, Amalie L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000321122587) and Sundararaman, Ravishankar [Rensselaer Polytechnic Institute, Troy, NY (United States)] (ORCID:0000000206254592) and Vigil-Fowler, Derek [National Laboratory of the Rockies (NLR), Golden, CO (United States)] (ORCID:0000000246132784)},
  year = {2026},
  doi = {10.1021/acsomega.6c01745},
  url = {https://www.osti.gov/biblio/3377318},
  note = {Source identifier: 3377318}
}