In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

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

In recent years, various metaheuristic optimization methods have been proposed in scientific
and engineering fields. In this study, a novel physics-inspired metaheuristic optimization …

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 on-the-fly generation of machine-learning force fields by active-learning schemes
attracts a great deal of attention in the community of atomistic simulations. The algorithms …

One of Feynman's early applications of path integrals was to superfluid He 4. He showed
that the thermodynamic properties of Bose systems are exactly equivalent to those of a …

Explicit reversible integrators, suitable for use in large-scale computer simulations, are
derived for extended systems generating the canonical and isothermal-isobaric ensembles …

Hydrogen and helium are the most abundant elements in the Universe. They are also, in
principle, the most simple. Nonetheless, they display remarkable properties under extreme …

Neat liquid phosphoric acid (H3PO4) has the highest intrinsic proton conductivity of any
known substance and is a useful model for understanding proton transport in other …

We have developed a method to study transition pathways for rare events in complex
systems. The method can be used to determine rate constants for transitions between stable …