5 citations · 5 across the 4 of their papers we have counts for
4 papers
Neural-network-enabled molecular dynamics study of HfO phase transitions
Sebastian Bichelmaier, Jesús Carrete, Georg K. H. Madsen
The advances of machine-learned force fields have opened up molecular dynamics (MD) simulations for compounds for which ab-initio MD is too resource-intensive and phenomena for whi…
A neural-network-backed effective harmonic potential study of the ambient pressure phases of hafnia
Sebastian Bichelmaier, Jesús Carrete, Ralf Wanzenböck +2
Phonon-based approaches and molecular dynamics are widely established methods for gaining access to a temperature-dependent description of material properties. However, when a comp…
Accurate effective harmonic potential treatment of the high-temperature cubic phase of Hafnia
Sebastian Bichelmaier, Jesús Carrete, Michael Nelhiebel +1
HfO is an important high- dielectric and ferroelectric, exhibiting a complex potential energy landscape with several phases close in energy. It is, however, a strongly anhar…
A Differentiable Neural-Network Force Field for Ionic Liquids
Hadrián Montes-Campos, Jesús Carrete, Sebastian Bichelmaier +2
We present NeuralIL, a model for the potential energy of an ionic liquid that accurately reproduces first-principles results with orders-of-magnitude savings in computational cost.…