A review of the simulation studies on the bulk growth of silicon carbide single crystals

Silicon carbide (SiC) is a wide-bandgap semiconductor material that is viable for the next generation of high-performance and high-power electrical devices. In general, bulk SiC single crystals have been grown at very high temperatures in a closed reactor; hence, the growth process is difficult to monitor using in situ techniques. Consequently, computational simulations have been utilized to understand, validate, and design crystal growth processes. In this review, we summarize the results of computational simulations of SiC bulk crystal growth using three primary methods: physical vapor transport, high-temperature chemical vapor deposition, and top-seeded solution growth. The simulations reveal the effects of physicochemical phenomena, such as temperature distribution, fluid flow, and chemical reactions, on crystal growth behaviors. Process parameters for high-quality and high-yield crystal growth have been realized with the aid of simulations. Furthermore, recent advances in machine learning techniques for accelerating the design of crystal growth parameters and enabling real-time parameter optimization are introduced. Overall, computational simulations are a crucial tool for the development of SiC bulk crystal growth and its applications.