Thermodynamic and electronic properties of water and ice: joining machine learning and manybody perturbation theory

Water and ice are fundamental substances for life on Earth: the relations among water's molecular structure, electronic structure, and anomalous thermodynamic properties have been extensively investigated.

Modeling through accurate computer simulations is essential to connect experimental observation with the molecular-level picture of water and ice. It is by now established that nuclear quantum effects (NQEs) play a crucial role in determining the structural and thermodynamic properties of water. However, to date the understanding of how NQEs influence the electronic structure of water systems is limited, in particular in bulk ice, and in interfacial and confined water and ice systems.

Here, we conducted a systematic comparison of both the structural and electronic properties for various

water systems, including water clusters, liquid water, and hexagonal ice simulated at the level of classical molecular dynamics (MD) and quantum path-integral MD. These simulations leverage the efficiency and accuracy of machine learning potentials fitted to state-of-the-art density functional theory calculations. Electronic structure calculations using GW manybody perturbation theory provide a detailed insight of the distinct impact that NQEs have on different aqueous systems.