摘要

Conventional continuum mechanistic models for polymer degradation typically involve thousands of coupled differential-algebraic equations, requiring an efficient solver to solve the complex set of stiff model equations. This can be overcome by formulating the problem in terms of a stochastic simulation procedure, requiring only iterative operations to solve the model. The present work describes the detailed mechanistic modeling of pyrolysis of poly(styrene peroxide) (PSP) using kinetic Monte Carlo (KMC) simulation to predict the product yields and gain a better understanding of the product evolution pathways. The traditionally accepted mechanism of PSP pyrolysis proposed by Mayo and Miller, which involves the key reaction steps of peroxide bond fission, alkoxy radical recombination and disproportionation, and end chain beta-scission, was initially tested using the KMC model to predict the peroxide concentration profile and the product yields. This model was only qualitatively able to predict the major products, benzaldehyde and formaldehyde, while the formation of minor products like a-hydroxy acetophenone, phenyl glycol, and phenyl glyoxal was not captured at all. Hence, a new mechanism that also incorporated hydrogen abstraction and beta-scission was proposed and implemented in KMC. The final model tracked 949 reactions of 83 species. The rate coefficients for all the reaction steps were based on the existing literature reports, and hence no parameter estimation was done to fit the model against the experimental data. The revised model was quantitatively able to predict all the products of PSP pyrolysis, which was attributed to the stabilization of the alkoxy radicals by hydrogen abstraction, and the subsequent generation of additional alkoxy radicals by beta-scission. KMC allowed the dominant pathways for the formation of minor products and dimers to be identified explicitly. Finally, the implications of this study in understanding the effect of trace peroxide bonds on poly(styrene) pyrolysis are outlined.