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 …

Deep learning has led to a paradigm shift in artificial intelligence, including web, text, and
image search, speech recognition, as well as bioinformatics, with growing impact in …

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 …

Chemical reactions on surfaces play central roles in heterogeneous catalysis, and most
reactions involve the formation and/or the cleavage of bonds. At present, density functional …

Water (H2O) is of great societal importance, and there has been a significant amount of
research on its fundamental properties and related physical phenomena. Deuterium dioxide …

A comprehensive microscopic understanding of ambient liquid water is a major challenge
for ab initio simulations as it simultaneously requires an accurate quantum mechanical …

Metal–organic frameworks show both fundamental interest and great promise for
applications in adsorption-based technologies, such as the separation and storage of gases …

We explore how anharmonicity, nuclear quantum effects (NQE), many-body dispersion
interactions, and Pauli repulsion influence thermal properties of dispersion-bound molecular …

In this article, we investigate the influence of anharmonicities and nuclear quantum effects
(NQEs) in modelling the structural properties and thermal expansion of the empty MOF-5 …

Imaginary time path-integral (PI) simulations that account for nuclear quantum effects (NQE)
beyond the harmonic approximation are increasingly employed together with modern …