Optimal Control of SiC Crystal Growth in the RF-TSSG System Using Reinforcement Learning
We have developed a reinforcement learning (RL) model to control the melt flow in the radio frequency (RF) top-seeded solution growth (TSSG) process for growing more uniform SiC crystals with a higher growth rate. In the study, the electromagnetic field (EM) strength is controlled by the RL model to...
Main Authors: | Lei Wang, Atsushi Sekimoto, Yuto Takehara, Yasunori Okano, Toru Ujihara, Sadik Dost |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Crystals |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4352/10/9/791 |
Similar Items
-
Numerical Study of Three-Dimensional Melt Flows during the TSSG Process of SiC Crystal for the Influence of Input Parameters of RF-Coils and an External Rotating Magnetic Field
by: Lei Wang, et al.
Published: (2020-02-01) -
Modélisation des procédes de croissance de SiC en phase gazeuse (PVT) et en phase liquide (TSSG)
by: Ariyawong, Kanaparin
Published: (2015) -
Étude du procédé de croissance en solution à haute température pour le développement de substrats de 4H-SiC fortement dopes
by: Shin, Yun ji
Published: (2016) -
Improvement of SiC Crystal Growth Rate and Uniformity via Top-Seeded Solution Growth under External Static Magnetic Field: A Numerical Investigation
by: Minh-Tan Ha, et al.
Published: (2020-02-01) -
Recent advances in joining of SiC-based materials (monolithic SiC and SiCf/SiC composites): Joining processes, joint strength, and interfacial behavior
by: Guiwu Liu, et al.
Published: (2019-03-01)