Electron dynamics mediate the water-carbon {\pi} bond

TL;DR

This study uses infrared spectroscopy and machine learning to explore how water interacts electronically with aromatic { extpi} systems, revealing complex vibrational-electronic interplay.

Contribution

It introduces new machine-learning methods to model water-{ extpi} interactions and uncovers how electron dynamics influence vibrational signals.

Findings

Electron dynamics quench some water vibrational signals.

Machine-learning potentials accurately model water-{ extpi} interactions.

Electronic and vibrational motions are strongly coupled in water-aromatic systems.

Abstract

The intermolecular interaction between a water molecule and the electrons in aromatic {\pi} systems--the water-{\pi} bond--lies at the heart of many chemical processes, yet its properties remain challenging to measure experimentally and model computationally. Infrared spectroscopy of pyrene anions hydrated by a single water molecule reveals vibrational and electronic motions that are often hidden in condensed phase measurements. Results from new machine-learning approaches to potentials and dipole moments show that the electron dynamics of the aromatic {\pi} cloud quench signals from some of water's vibrations and amplify others. The observed interplay between electronic and vibrational motions has general implications for modeling intermolecular interactions between water and aromatic systems in clusters, solutions, and at interfaces.