解耦(概率)
冰晶
材料科学
化学物理
表面粗糙度
增长率
表面光洁度
氢键
晶体生长
结晶学
化学
物理
分子
光学
复合材料
几何学
数学
工程类
控制工程
有机化学
作者
Xuan Zhang,Yifeng Yao,Hongyi Li,André Python,Kenji Mochizuki
标识
DOI:10.1038/s42005-023-01285-y
摘要
Abstract 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI