材料科学
位错
星团(航天器)
硅
工程物理
结晶学
冶金
复合材料
计算机科学
工程类
化学
程序设计语言
作者
Kazuma Torii,Takuto Kojima,Kentaro Kutsukake,Hiroaki Kudo,Noritaka Usami,Kazuma Torii,Takuto Kojima,Kentaro Kutsukake,Hiroaki Kudo,Noritaka Usami
标识
DOI:10.1080/14686996.2025.2512703
摘要
We utilized twin network analysis of polycrystalline materials through graph theory to visualize microstructures and examine the behavior of dislocation cluster generation in multicrystalline silicon grown by directional solidification. This approach allows for a rapid and statistical understanding of microstructures and their correlations by representing these features and their changes as network graphs. Our analysis revealed that dislocation clusters are formed at asymmetric Σ27a grain boundaries, which result from a specific twinning process. Gaining this knowledge is expected to assist in identifying grain boundary groups that can minimize the formation of dislocation clusters.
科研通智能强力驱动
Strongly Powered by AbleSci AI