Fusion method of model-free and model-fitting for complex reactions in accelerating rate calorimetry

At present, the kinetic approaches of accelerating rate calorimetry (ARC) are restricted to model-fitting methods, and the n -order reaction model is mainly used to estimate the kinetic parameters. However, the model-fitting method has the problems related to model selection and falling into a local optimum. To address these issues, kinetic analysis methods are introduced into ARC data treatment, and the kinetic parameters of complex reactions are solved by a model-free and model-fitting fusion method. First, the Friedman method is used to calculate the activation energy E α . Then, A α and the overall mathematical function f ( α ) are obtained through the compensation effect. It provides references for the selection of the reaction model and initial values of model fitting, and the kinetic parameters are estimated through two-step model fitting. The fitting in steps realizes the decoupling of E and A and reduces the data dimensions. These help to reduce the chance of falling into a local optimum and lower the experience requirements. Finally, numeric simulations and the experimental results showed the effectiveness of the method.