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In the present study, a soft computing method namely the group method of data handling (GMDH) was applied to develop a new and efficient predictive model for prediction of conversion percentage of silicon. A comprehensive database was obtained from experimental studies in the literature. Several effective parameters like time, temperature, nitrogen percentage, pellet size, and silicon particle size were considered. The performance of the model was evaluated through statistical analysis. Moreover, the silicon nitridation was performed in 1573 k and the experimental results were evaluated against model results for validation of the model. Furthermore, the performance and efficiency of the GMDH model were confirmed against the two most common analytical models. The most effective parameters in estimating the conversion percentage were determined through sensitivity analysis based on the Gamma Test. Finally, the robustness of the developed model was verified through parametric analysis. [ABSTRACT FROM AUTHOR]

An accurate prediction of reaction kinetics during silicon nitridation is of great importance in designing procedure of both material production and controlling of reaction. The key purpose of the current research is to study the consequence of temperature on the formation kinetics of reaction bonded silicon nitride (RBSN). To do so, nitrogen diffusion in the silicon nitride layer is deliberated as a reaction controlling factor and sharp interface technique based on this theory is used to improve the analytical model. In this developed model, the variations in the size of silicon particles are considered for the entire reaction. In the experimental phase, the extent of nitridation is measured for different reaction temperatures and 4 different reaction times and at that time, the incidence of full nitridation is shown by EDS analysis. Furthermore, an analytical approach was established for describing the kinetics of compound formation and the performance of the developed model evaluated through statistical analysis. There was good superposition among experimental data and calculations of the developed model which establishes the accuracy of considered presumptions and reaction mechanisms. [ABSTRACT FROM AUTHOR]