Ab initio thermodynamics of liquid and solid water

Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proton disorder. This is made possible by combining advanced free-energy methods and state-of-the-art machine-learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments and reliable estimates of the melting points of light and heavy water. We observe that nuclear-quantum effects contribute a crucial 0.2 meV/H2O to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine-learning potentials as an intermediate step.

基于杂化泛函水平的密度泛函理论，并严格考虑量子核运动、非谐涨落和质子无序，对液态水以及六方（Ih）冰和立方（Ic）冰的热力学性质进行了预测。这是通过结合先进的自由能方法和最先进的机器学习技术实现的。从头算描述得出的结构性质与实验结果高度吻合，并对轻水和重水的熔点进行了可靠估算。我们观察到核量子效应对冰Ih的稳定性有至关重要的贡献，为每分子水0.2毫电子伏特，使其比冰Ic更稳定。我们的计算方法具有通用性和可转移性，为使用机器学习势作为中间步骤对从头算热力学性质进行定量预测提供了一个综合框架。