ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials.

The emergence of artificial intelligence is profoundly impacting computational chemistry, particularly through machine-learning interatomic potentials (MLIPs). Unlike traditional potential energy surface representations, MLIPs overcome the conventional computational scaling limitations by offering an effective combination of accuracy and efficiency for calculating atomic energies and forces to be used in molecular simulations. These MLIPs have significantly enhanced molecular simulations across various applications, including large-scale simulations of materials, interfaces, chemical reactions, and beyond.

Dissecting the hydrogen bond network of water: Charge transfer and nuclear quantum effects.

The molecular structure of water is dynamic, with intermolecular hydrogen (H) bond interactions being modified by both electronic charge transfer and nuclear quantum effects (NQEs). Electronic charge transfer and NQEs potentially change under acidic or basic conditions, but such details have not been measured. In this work, we developed correlated vibrational spectroscopy, a symmetry-based method that separates interacting from noninteracting molecules in self- and cross-correlation spectra, giving access to previously inaccessible information.

Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange.

The transport of excess protons in water is central to acid-base chemistry, biochemistry and energy production. However, elucidating its mechanism has been challenging. Recent nonlinear vibrational spectroscopy experiments could not be explained by existing models.

Impact of interfacial curvature on molecular properties of aqueous interfaces.

The curvature of soft interfaces plays a crucial role in determining their mechanical and thermodynamic properties, both at macroscopic and microscopic scales. In the case of air/water interfaces, particular attention has recently focused on water microdroplets, due to their distinctive chemical reactivity. However, the specific impact of curvature on the molecular properties of interfacial water and interfacial reactivity has so far remained elusive.

Competing Reaction Mechanisms of Peptide Bond Formation in Water Revealed by Deep Potential Molecular Dynamics and Path Sampling.

The formation of an amide bond is an essential step in the synthesis of materials and drugs, and in the assembly of amino acids to form peptides. The mechanism of this reaction has been studied extensively, in particular to understand how it can be catalyzed, but a representation capable of explaining all the experimental data is still lacking. Numerical simulation should provide the necessary molecular description, but the solvent involvement poses a number of challenges.