7 papers
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models
Isabel Creed, Tim Rein, Ingvars Vitenburgs +21
Machine-learned interatomic potentials (MLIPs) have had a profound impact on molecular modelling in recent years, promising to resolve the long-standing tension between the scale a…
Role of anisotropic electronic friction in laser-driven hydrogen recombination on copper
Alexander Spears, Wojciech G. Stark, Reinhard J. Maurer
Ultrafast light-driven chemical dynamics at surfaces are governed by energy transfer from excited electrons to vibrational degrees of freedom. When this nonadiabatic energy transfe…
Fine-tuning foundation models of materials interatomic potentials with frozen transfer learning
Mariia Radova, Wojciech G. Stark, Connor S. Allen +2
Machine-learned interatomic potentials are revolutionising atomistic materials simulations by providing accurate and scalable predictions within the scope covered by the training d…
Nonadiabatic reactive scattering of hydrogen on different surface facets of copper
Wojciech G. Stark, Connor L. Box, Matthias Sachs +2
Dissociative chemisorption is a key process in hydrogen-metal surface chemistry, where nonadiabatic effects due to low-lying electron-hole-pair excitations may affect reaction outc…
Machine Learning and Data-Driven Methods in Computational Surface and Interface Science
Lukas Hörmann, Wojciech G. Stark, Reinhard J. Maurer
Nanoscale design of surfaces and interfaces is essential for modern technologies like organic LEDs, batteries, fuel cells, superlubricating surfaces, and heterogeneous catalysis. H…
Room Temperature Hydrogen Atom Scattering Experiments Are Not a Sufficient Benchmark to Validate Electronic Friction Theory
Connor L. Box, Nils Hertl, Wojciech G. Stark +1
In the dynamics of atoms and molecules at metal surfaces, electron-hole pair excitations can play a crucial role. In the case of hyperthermal hydrogen atom scattering, they lead to…