3 papers
cond-mat.mtrl-sci2026
Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations
Sushree Jagriti Sahoo, Mikael Maraschin, Joel B Varley +7
Catalysis at solid-liquid interfaces underpins many energy technologies, yet ab initio simulations that capture interfacial dynamics remain prohibitively expensive. Here we introdu…
physics.chem-ph2026
Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces
Lucas B. T. de Kam, Jia-Xin Zhu, Ankit Mathanker +2
Atomistic simulations of electrochemical interfaces remain challenging due to the long time scales required to adequately sample the structure of the electric double layer. The eme…
physics.chem-ph2026
Optimized tandem catalyst patterning for CO reduction flow reactors
Jack Guo, Thomas Roy, Nitish Govindarajan +7
Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts' reaction pathways to…