Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

The unprecedented ability of computations to probe atomic-level details of catalytic systems
holds immense promise for the fundamentals-based bottom-up design of novel …

Safe and rechargeable lithium metal batteries have been difficult to achieve because of the
formation of lithium dendrites. Herein an emerging electrolyte based on a simple solvation …

Optically active molecular materials, such as organic conjugated polymers and biological
systems, are characterized by strong coupling between electronic and vibrational degrees of …

The lithium–sulfur (Li–S) battery is a promising high‐energy‐density storage system. The
strong anchoring of intermediates is widely accepted to retard the shuttle of polysulfides in a …

Herein, an unprecedented synthetic route to sulfilimines via a copper-catalyzed Chan–Lam-
type coupling of sulfenamides is presented. A key to success in this novel transformation is …

Digital quantum computers provide a computational framework for solving the Schrödinger
equation for a variety of many‐particle systems. Quantum computing algorithms for the …

Large-scale ammonia synthesis via the electrochemical nitrogen reduction reaction (eNRR)
under mild reaction conditions represents a green prospect for agriculture, industry, and …

Computational chemistry provides a versatile toolbox for studying mechanistic details of
catalytic reactions and holds promise to deliver practical strategies to enable the rational in …

This review describes the theory and implementation of implicit solvation models based on
continuum electrostatics. Within quantum chemistry this formalism is sometimes …