Topology and complexity of the hydrogen bond network in classical models of water

TL;DR

This paper compares 11 classical water models by analyzing their hydrogen bond network topology, introducing a network complexity index that links network structure to water's dynamical properties and phase behavior.

Contribution

It introduces a novel network complexity index to quantify hydrogen bond network topology and relates it to water models' dynamical properties and phase transformations.

Findings

Network complexity index correlates with water model dynamics.

Topological features predict crystallization tendencies.

Benchmark for evaluating water models' performance.

Abstract

Over the years, plenty of classical interaction potentials for water have been developed and tested against structural, dynamical and thermodynamic properties. On the other hands, it has been recently observed (F. Martelli et. al, \textit{ACS Nano}, \textbf{14}, 8616--8623, 2020) that the topology of the hydrogen bond network (HBN) is a very sensitive measure that should be considered when developing new interaction potentials. Here we report a thorough comparison of 11 popular non polarizable classical water models against their HBN, which is at the root of water properties. We probe the topology of the HBN using the ring statistics and we evaluate the quality of the network inspecting the percentage of broken and intact HBs. For each water model, we assess the tendency to develop hexagonal rings (that promote crystallization at low temperatures) and pentagonal rings (known to frustrate against crystallization at low temperatures). We then introduce the \emph{network complexity index}, a general descriptor to quantify how much the topology of a given network deviates from that of the ground state, namely of hexagonal or cubic ice. Remarkably, we find that the network complexity index allows us to relate, for the first time, the dynamical properties of different water models with their underlying topology of the HBN. Our study provides a benchmark against which the performances of new models should be tested against, and introduces a general way to quantify the complexity of a network which can be transferred to other materials and that links the topology of the HBN with dynamical properties. Finally, our study introduces a new perspective that can help in rationalizing the transformations among the different phases of water and of other materials.