Four generations of high-dimensional neural network potentials
J Behler - Chemical Reviews, 2021 - ACS Publications
Since their introduction about 25 years ago, machine learning (ML) potentials have become
an important tool in the field of atomistic simulations. After the initial decade, in which neural …
an important tool in the field of atomistic simulations. After the initial decade, in which neural …
General-purpose machine learning potentials capturing nonlocal charge transfer
Conspectus The development of first-principles-quality machine learning potentials (MLP)
has seen tremendous progress, now enabling computer simulations of complex systems for …
has seen tremendous progress, now enabling computer simulations of complex systems for …
A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer
Abstract Machine learning potentials have become an important tool for atomistic
simulations in many fields, from chemistry via molecular biology to materials science. Most of …
simulations in many fields, from chemistry via molecular biology to materials science. Most of …
Development of an efficient charge equilibration method for nonlocal neural network potentials with applications in redox chemistry
E Kocer - 2025 - ediss.uni-goettingen.de
This thesis focuses on the development and application of new methodologies for machine
learning potentials in atomistic simulations. The primary contribution of this work is the …
learning potentials in atomistic simulations. The primary contribution of this work is the …