Kinetic predictions of accelerating rate calorimetry based on isoconversional methods

Abstract

Kinetic predictions are widely used in thermal runaway research. At present, the model-fitting method based on single experimental data is mainly adopted in the kinetic prediction of accelerating rate calorimetry (ARC), which has the problems related to difficult analysis of reaction mechanism and large uncertainty of kinetic parameters. The Kinetic Committee of the International Confederation for Thermal Analysis and Calorimetry has clearly proposed to avoid using this method. The development of prediction methods that use multiple temperature programs is essential in the field of ARC. To address these issues, the kinetic predictions based on isoconversional methods were studied. The data of the n-order reaction and autocatalytic reaction under adiabatic conditions were obtained by numerical simulations, and the kinetic parameters were estimated by the Vyazovkin and the Friedman methods. Then, the kinetic parameters are substituted into the equations for adiabatic and isothermal prediction. To solve the problem of large prediction error, a simple correction method of kinetic parameter was proposed. Finally, the kinetic prediction approaches were verified by experiments. The results show that the ARC can carry out model-free kinetic predictions based on the isoconversional methods. The Vyazovkin method has higher prediction accuracy than the Friedman method, and the simple correction method can effectively improve prediction accuracy. The kinetic prediction approaches based on the isoconversional methods are beneficial supplements and alternatives for traditional kinetic analysis method of the ARC.