Investigating the Growth of GaSb Single Crystals through Optimized LEC Method Utilizing Finite Element Simulation and Machine Learning Techniques.

ABSTRACT: In this study, CGsim and liquid-encapsulated Czochralski (LEC) growth experiments were employed to handle the challenges associated with growing large-sized compound semiconductor single crystals. CGsim, a simulation software integrating the finite element method with machine learning (ML) techniques, was utilized to optimize the heat flux and crystallization front morphology at the solid-liquid interface during GaSb crystal growth. ML validation, performed across various crucible rotation speeds and crystal position (CP) configurations, enabled the optimization of the moving front shape at the solid-liquid interface, reducing the protrusion angle to 0.086°. The crystal quality of GaSb single crystal slices was evaluated through X-ray double crystal rocking curves and optical microscopy. T

SUBMITTER: Han J 

PROVIDER: S-EPMC12809291 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature