34 citations · 47 across the 4 of their papers we have counts for
3 papers · 1 filter
ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials
Rolf David, Miguel de la Puente, Axel Gomez +3
The emergence of artificial intelligence has profoundly impacted computational chemistry, particularly through machine-learned potentials (MLPs), which offer a balance of accuracy…
Liquid water under vibrational strong coupling: an extended cavity Born-Oppenheimer molecular dynamics study
Jessica Bowles, Damien Laage, Jaime De La Fuente Diez +3
A computational study of liquid water when the system is coupled with a (model) Fabry-Perot cavity is reported. At this end, the Cavity Born-Oppenheimer Molecular Dynamics approach…
Explicit models of motions to understand protein side-chain dynamics
Nicolas Bolik-Coulon, Olivier Languin-Cattoën, Diego Carnevale +5
Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forg…