Atomistic simulations of chemical, biological and materials systems have become
increasingly precise and predictive owing to the development of accurate and efficient …

Nuclear quantum effects influence the structure and dynamics of hydrogen-bonded systems,
such as water, which impacts their observed properties with widely varying magnitudes. This …

The nature of hydrated proton on solid surfaces is of vital importance in electrochemistry,
proton channels, and hydrogen fuel cells but remains unclear because of the lack of atomic …

Progress in the atomic-scale modeling of matter over the past decade has been tremendous.
This progress has been brought about by improvements in methods for evaluating …

Water is one of the most important, yet least understood, liquids in nature. Many anomalous
properties of liquid water originate from its well-connected hydrogen bond network …

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 …

Preserving the correct dynamics at the coarse-grained (CG) level is a pressing problem in
the development of systematic CG models in soft matter simulation. Starting from the seminal …

SchNetPack is a versatile neural network toolbox that addresses both the requirements of
method development and the application of atomistic machine learning. Version 2.0 comes …

Lithium ortho-thiophosphate (Li3PS4) has emerged as a promising candidate for solid-state
electrolyte batteries, thanks to its highly conductive phases, cheap components, and large …

Recent developments in path integral methodology have significantly reduced the
computational expense of including quantum mechanical effects in the nuclear motion in ab …