Use of neural network to characterize temperature effects on refractive property of silicon nitride film deposited by PECVD

Summary form only given, as follows. Deposition of silicon nitride (SiN) film is one of the most critical processes that determine the efficiency of solar cells. Qualities of SiN film deposited by a plasma-enhanced chemical vapor deposition depend on many process parameters. Predicting film properties is very important to their optimization as well as to gain insight into underlying deposition mechanisms. For plasma-driven processes, however, it has been a difficult task to construct prediction models due to complexity within a plasma. In this study, a predictive model for a SiN PECVD process was constructed and used to understand physical deposition mechanisms. The interpretation was mainly focused on the refractive index, particularly with respect to the substrate temperature.