High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning
Published in JOURNAL OF CHEMICAL PHYSICS, 2022
Recommended citation: Quach, Co D. Gilmer, Justin B. Pert, Daniel Mason-Hogans, Akanke Iacovella, Christopher R. Cummings, Peter T. McCabe, Clare (2022). "High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning ." JOURNAL OF CHEMICAL PHYSICS. 156 (154902).
Quach, Co D. Gilmer, Justin B. Pert, Daniel Mason-Hogans, Akanke Iacovella, Christopher R. Cummings, Peter T. McCabe, Clare (2022). “High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning .” JOURNAL OF CHEMICAL PHYSICS. 156 (154902), pp .
DOI: 10.1063/5.0080838
Funding source: National Science Foundation (NSF) [OAC-1835874]; National Science Foundation [DMR-1852157]; Office of Science of the Department of Energy at the Oak Ridge Leadership Computing Facility [DE-AC05-00OR22725]; INCITE program; National Energy Research Scientific Computing Center (NERSC) [DE-AC02-05CH11231]