Kinetic Analysis and Modeling of Poly(Vinyl Butyral)/Glass Ceramic/Metal Thermal Oxidative Degradation Using Thermogravimetric Analysis and Neural Networks

Abstract

Kinetic model of poly(vinyl butyral) (PVB)/glass ceramic/silver thermal degradation was built using thermogravimetry (TG) data and an artificial neural network (ANN) algorithm. An experimental design method with different material compositions was utilized to demonstrate the effects of the polymer binder burnout with the glass ceramic and Ag. The reaction parameters of PVB thermal oxidative degradation affected by glass ceramic and Ag were obtained by analyzing TG data with a decomposition kinetic equation. From the kinetic analysis, the activation energy (E a ) values of thermal degradation of PVB and the PVB composites are found quite different. In addition, the analysis revealed that PVB thermal degradation is much affected by the existence of the glass ceramic and Ag. The ANN modeling approach was introduced to construct the overall relationships between the different compositions (input) and the estimated kinetic parameters (output). The built ANN model can represent the kinetics of PVB thermal oxidative degradation with respect to the material composition. From this ANN model, the lower E a appears in the lower composition of PVB and Ag but higher composition of glass ceramic situation.