Fast crystal growth of ice VII owing to the decoupling of translational and rotational ordering

• Published in: Communications physics Vol. 6; no. 1; pp. 164 - 11
• Main Authors: Zhang, Xuan, Yao, Yifeng, Li, Hongyi, Python, Andre, Mochizuki, Kenji
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 04.07.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/638/440/94; 639/638/563/981; Cooling; Crystal growth; Crystal structure; Crystals; Decoupling; Hydrogen; Hydrogen bonds; Machine learning; Molecular dynamics; Physics; Physics and Astronomy; Simulation; Surface roughness; Unsupervised learning
• ISSN: 2399-3650; 2399-3650
• DOI: 10.1038/s42005-023-01285-y

Despite the abundance of water’s crystalline polymorphs, the growth mechanisms of most ice forms remain poorly understood. This study applies extensive molecular dynamics (MD) simulations to examine the growth of ice VII, revealing a fast growth rate comparable to pure metals while maintaining robust hydrogen-bond networks. The results from an unsupervised machine learning applied to identify local structure suggest that the surface of ice VII consistently exhibits a body-centered cubic (bcc) plastic ice layer, indicating the decoupling of translational and rotational orderings. The study also uncovers the ultrafast growth rate of pure plastic ice, indicating that orientational disorder in the crystal structure may be associated with faster kinetics. Additionally, we discuss the impacts of interfacial plastic layer width and surface roughness on growth mode. The authors combine molecular dynamics (MD) simulations and machine learning (ML) to study the melt growth of three ice polymorphs, Ih, VII and plastic ice. MD data indicate much faster growth rates for ice VII and plastic Approved ice, while the ML analysis suggests that ice VII grows via a thin ice plastic layer, which is formed at its growth front.