Water Modeled As an Intermediate Element between Carbon and Silicon

TLDR

Water, silicon, and carbon share tetrahedral coordination, leading to similar physical properties such as a temperature of maximum density, enhanced diffusivity under compression, and tetrahedral crystal and amorphous phases. The study aims to create a coarse‑grained water model (mW) that captures tetrahedrality between carbon and silicon. mW achieves water‑like tetrahedral structure by adding a nonbond angular term that promotes tetrahedral configurations, relying solely on short‑range interactions rather than long‑range electrostatics. mW reproduces water’s energetics, density, structure, anomalies, and phase transitions with comparable or superior accuracy to popular atomistic models while using less than 1 % of the computational cost, demonstrating that molecular connectivity—not interaction type—governs water’s behavior and enabling efficient studies of slow processes, ice nucleation, wetting‑drying transitions, and coarse‑grained biomolecular simulations.

Abstract

Water and silicon are chemically dissimilar substances with common physical properties. Their liquids display a temperature of maximum density, increased diffusivity on compression, and they form tetrahedral crystals and tetrahedral amorphous phases. The common feature to water, silicon, and carbon is the formation of tetrahedrally coordinated units. We exploit these similarities to develop a coarse-grained model of water (mW) that is essentially an atom with tetrahedrality intermediate between carbon and silicon. mW mimics the hydrogen-bonded structure of water through the introduction of a nonbond angular dependent term that encourages tetrahedral configurations. The model departs from the prevailing paradigm in water modeling: the use of long-ranged forces (electrostatics) to produce short-ranged (hydrogen-bonded) structure. mW has only short-range interactions yet it reproduces the energetics, density and structure of liquid water, and its anomalies and phase transitions with comparable or better accuracy than the most popular atomistic models of water, at less than 1% of the computational cost. We conclude that it is not the nature of the interactions but the connectivity of the molecules that determines the structural and thermodynamic behavior of water. The speedup in computing time provided by mW makes it particularly useful for the study of slow processes in deeply supercooled water, the mechanism of ice nucleation, wetting-drying transitions, and as a realistic water model for coarse-grained simulations of biomolecules and complex materials.