Modeling the Effect of the Most Important Factors on the Kinetics Behavior of Silicon Nitration Reaction Based on Group Method of Data Handling

In the present study, a soft computing method namely the group method of data handling (GMDH) is applied to develop a new and efficient predictive model for prediction of kinetics   silicon nitridation. 1186 data point is obtained from experimental results and other studies in literatures. Several effective parameters like time, temperature, nitrogen percentage, pellet size and silicon particle size are considered. The silicon nitridation was performed in 1573 k and results were evaluated against model results for validation of the model. The performance of the model is evaluated through statistical analysis. Furthermore, the performance and efficiency of the GMDH model is confirmed against the two most common analytical models. Using sensitivity analysis, nitrogen pressure with  0.27 was the most effective parameter in nitridation.