512 citations · 592 across the 5 of their papers we have counts for
5 papers
Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
Emir Kocer, Andreas Singraber, Jonas A. Finkler +4
Machine learning potentials (MLP) allow to perform large-scale molecular dynamics simulations with about the same accuracy as electronic structure calculations provided that the se…
Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111)
Peitao Liu, Jiantao Wang, Noah Avargues +5
Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges t…
Improved Description of Atomic Environments using Low-cost Polynomial Functions with Compact Support
Martin P. Bircher, Andreas Singraber, Christoph Dellago
The prediction of chemical properties using Machine Learning (ML) techniques calls for a set of appropriate descriptors that accurately describe atomic and, on a larger scale, mole…
How van der Waals interactions determine the unique properties of water
Tobias Morawietz, Andreas Singraber, Christoph Dellago +1
While the interactions between water molecules are dominated by strongly directional hydrogen bonds (HBs), it was recently proposed that relatively weak, isotropic van der Waals (v…
Trimaximal lepton mixing with a trivial Dirac phase
W. Grimus, L. Lavoura, A. Singraber
We present a model which employs the seesaw mechanism with five right-handed neutrinos, leading to trimaximal and CP-conserving lepton mixing. Tri-bimaximal mixing is a natural lim…