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 …

Almost 50 years have passed from the first computer simulations of water, and a large
number of molecular models have been proposed since then to elucidate the unique …

The MB-pol many-body potential has recently emerged as an accurate molecular model for
water simulations from the gas to the condensed phase. In this study, the accuracy of MB-pol …

The development of interatomic potentials employing artificial neural networks has seen
tremendous progress in recent years. While until recently the applicability of neural network …

The theory of intermolecular forces has advanced very greatly in recent years. It has become
possible to carry out accurate calculations of intermolecular forces for molecules of useful …

We review recent progress in developing potential energy and dipole moment surfaces for
polyatomic systems with up to 10 atoms. The emphasis is on global linear least squares …

Deep neural network (DNN) potentials have recently gained popularity in computer
simulations of a wide range of molecular systems, from liquids to materials. In this study, we …

We use the MB-pol theoretical/computational framework to introduce a new family of data-
driven many-body potential energy functions (PEFs) for water, named MB-pol (2023). By …

Over the past decade, about 50 potential energy surfaces (PESs) for polyatomics with 4–11
atoms and for clusters have been calculated using the permutationally invariant polynomial …

Modern simulation and modeling approaches to investigation of biomolecular structure and
function rely heavily on a variety of methods—water models—to approximate the influence …