31 citations · 81 across the 11 of their papers we have counts for
4 papers · 1 filter
Accelerating fourth-generation machine learning potentials by quasi-linear scaling particle mesh charge equilibration
Moritz Gubler, Jonas A. Finkler, Moritz R. Schäfer +2
Machine learning potentials (MLP) have revolutionized the field of atomistic simulations by describing the atomic interactions with the accuracy of electronic structure methods at…
Performing highly efficient Minima Hopping structure predictions using the Atomic Simulation Environment (ASE)
Marco Krummenacher, Moritz Gubler, Jonas A. Finkler +3
In the dynamic field of materials science, the quest to find optimal structures with low potential energy is of great significance. Over the past two decades, the minima hopping al…
Targeting high symmetry in structure predictions by biasing the potential energy surface
Hannes Huber, Martin Sommer, Moritz Gubler +1
Ground state structures found in nature are in many cases of high symmetry. But structure prediction methods typically render only a small fraction of high symmetry structures. Esp…
Efficient variable cell shape geometry optimization
Moritz Gubler, Marco Krummenacher, Hannes Huber +1
A fast and reliable geometry optimization algorithm is presented that optimizes atomic positions and lattice vectors simultaneously. Using a series of benchmarks, it is shown that…