activity
20202026
most citedExcited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential

94 citations · 274 across the 10 of their papers we have counts for

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Showing 2022Show all

2 papers · 1 filter

cond-mat.mtrl-sci2022★ 15 cited

Learned Force Fields Are Ready For Ground State Catalyst Discovery

Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose +6

We present evidence that learned density functional theory (``DFT'') force fields are ready for ground state catalyst discovery. Our key finding is that relaxation using forces fro…

physics.chem-ph2022

Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential

Simon Axelrod, Eugene Shakhnovich, Rafael Gomez-Bombarelli

Molecular photoswitches are the foundation of light-activated drugs. A key photoswitch is azobenzene, which exhibits trans-cis isomerism in response to light. The thermal half-life…