Simulating the ghost: quantum dynamics of the solvated electron

The solvated electron's nature poses challenges for experimental and theoretical studies due to its short lifespan, high reactivity, and the need for advanced electronic structure theory for accurate predictions. This research uses a machine-learning model to overcome the difficulty of modeling the solvated electron without explicitly including it, focusing on the electron's impact on the surrounding water's structure. The resulting potential accurately reproduces the stable cavity structure and localization dynamics, achieving the accuracy of the correlated wave function method used for training. This allows for an accurate determination of the solvated electron's structure, diffusion mechanisms, and vibrational spectroscopy.

Jinggang Lan, Venkat Kapil, Piero Gasparotto, Michele Ceriotti, Marcella Iannuzzi, Vladimir V. Rybkin