Machine Learning Based Insights of Seeded Congruent Crystal Growth of LiNbO3 in Glass
Acta Materialia(2024)
摘要
The seeded crystal growth of LiNbO3 in glass under the isothermal conditions has been studied using a machine-learned clustering algorithm trained on a combination of static and dynamic structural features. Our findings contradict the sharp crystal-glass interface assumption of classical nucleation theory (CNT). The growth of the seed occurs via the attachment of a group of atoms rather than single atoms. The predictions from the machine-learned simulations helped us compare the growth rate of seeds across various initial seed-sizes and temperature. Simulations with multiple seeds show that the growth rate of a seed is enhanced by the presence of another seed in its vicinity.
更多查看译文
关键词
Crystallization,Seeded Crystal Growth,Diffuse Interface
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要