Computational Prediction of Novel Ice Phases: A Perspective

Area of Science:

• Physical Chemistry
• Water Science
• Computational Materials Science

Background:

• Computational prediction of novel ice phases is a specialized area within water science.
• This field draws on statistical thermodynamics and molecular simulations, attracting public interest since the 1980s.
• Recent laboratory confirmations of low-dimensional "computer ice" phases have spurred further research.

Purpose of the Study:

• To review recent advancements in the computational prediction of novel ice phases.
• To focus on new ice phases with distinct physical properties or dimensional structures compared to conventional bulk ices.
• To discuss ongoing challenges and future opportunities in predicting new ice phases.

Main Methods:

• Review of computational studies, including classical molecular dynamics simulations and high-level ab initio computations.
• Analysis of specific novel ice phases: superionic ices, electrofreezing under extreme conditions, low-density porous ice, and two-dimensional (2D) ices.

Main Results:

• Identification of several novel ice phases with unique characteristics, such as superionic states and low-density porous structures.
• Exploration of 2D ice formation under nanoscale confinement and on solid surfaces near ambient temperatures.
• Emphasis on the requirement of extreme conditions (high pressure, electric fields, negative pressure) for the formation of most novel ice phases.

Conclusions:

• Computational predictions have revealed a diverse range of novel ice phases beyond conventional bulk forms.
• The formation of these new phases often necessitates extreme environmental conditions.
• Continued advancements in computational techniques offer significant opportunities for discovering and understanding new ice phases.