The top-seeded solution growth (TSSG) method for SiC crystals is proposed as a promising alternative to the conventional physical vapor transport (PVT) method, offering a scalable approach to obtaining SiC crystals of superior quality. The primary advantage of the TSSG method lies in its ability to achieve defect conversion through macro steps, effectively eliminating the original TSD and TED defects present in the seed crystal.[1] However, the successful elimination of defects requires appropriate step height and slope.[2] In our previous research, we observed that step height and slope have a significant impact on the formation of solvent inclusion.[3-4] Solvent inclusion is the heterogeneous substance contained within the grown crystals. It not only causes damage to the electrical and mechanical properties of crystal but also becomes a source of dislocation defects, spreading harmful effects to epitaxial layers. Solvent inclusions in SiC crystals include two types: cellular structure and overhanging structure. To suppress two types of solvent inclusion defects in SiC solution crystal growth, this study first established a local three-dimensional phase field (PF) model capable of simulating both cellular and overhanging structures simultaneously. Secondly, the local PF model was coupled with the global computational fluid dynamic (CFD) model. The local velocity and supersaturation near the crystal surface from the global CFD model were applied to multiple local three-dimensional PF models. Various crucible and seed rotation patterns are compared to design the optimal growth process. This simulation method enables the evaluation of the global crystal surface morphology and the proposal of practical optimized growth processes. To verify the simulation results, 1.6-inch SiC TSSG growth experiments were conducted. Firstly, the outward flow and inward solution flow patterns are compared. The temperature and solution flow velocity distribution of outward and inward flow from CFD simulation are shown in Fig. 1. (a) and (b) respectively. Four points on the crystal surface are selected, and the CFD calculation results at these four points are input to the PF model to calculate step morphologies. Results indicate that outward flow tends to produce cellular and overhanging structure type inclusions in the parallel flow area, while inward flow suffers from the issue of low crystal growth rate. Secondly, cases with various seed rotation speeds are compared by this simulation method and TSSG experiment. Both results indicate that the optimal rotation speed is 30 rpm in the outward flow pattern. Finally, this simulation method is used to design a switching flow pattern, which can suppress the formation of cellular and overhanging type inclusions on the overall crystal surface, and maintain a high growth rate at the same time. The PF simulation results of switching flow case for various time steps are presented in Fig.2. The PF results demonstrate that the step morphology changes as the flow pattern changes. The first 100000 timesteps is inward flow and anti-parallel flow, the step movement rate is slow, the step morphology in Fig.2 (b) is similar with initial state. The solution flow pattern changes to outward flow and parallel flow in 100000 ~ 200000 timesteps, the step morphology in Fig.2 (c) become instable, the overhanging structure and cellular structure are formed. When timestep in 200000 ~ 300000, solution changes to inward flow and anti-parallel flow again, the overhanging structure is suppressed, and cellular structure changes to zig-zag shape. Fig. 3. shows the crystal morphology in the experiment with the switching flow pattern. The experiments verified that the optimized growth process proposed by the simulation effectively reduced the inclusion density and kept a high crystal growth rate. This method can also be applied to optimize the liquid phase growth process of other crystals. [1] S. Yamaguchi, N. Naganawa and M. Nakamura, J. Appl. Phys. 58(6), 060901 (2019). [2] S. Xiao, S. Harada, K. Murayama, M. Tagawa, and T. Ujihara, Cryst. Growth Des. 16(11), 6436-6439 (2016). [3] H. Zhou, H. Miura, Y. Fukami, Y. Dang, K. Kutsukake, S. Harada, and T. Ujihara, Cryst. Growth Des (2024). [4] H. Zhou, H. Miura, Y. Dang, Y. Fukami, K. Kutsukake, S. Harada, and T. Ujihara, Cryst. Growth Des. 23(5), 3393-3401 (2023).