Abstract

Abstract This article presents a novel simulation approach for solving the inverse problem of kinetic heterogeneity in polymerization processes, specifically focusing on the production of polyisoprene using a gadolinium chloride solvate-based catalytic system. The proposed method is based on the assumption that the distribution of active centers (ACs) can be described by model distributions. By utilizing primary physicochemical data, such as the polymerization rate and molecular weight distribution, the simulation approach automatically identifies the kinetic parameters, determining the Frenkel statistical parameter and solving the problem of kinetic heterogeneity. The experimental results revealed the presence of at least three distinct types of ACs, each contributing different proportions to the polymerization process. The simulation approach offers valuable insights into the complexities of catalytic systems and their role in polymerization, paving the way for optimizing reaction conditions and advancing industrial polymer synthesis processes. This study marks a significant step forward in understanding and controlling polymerization reactions, with potential implications for the development of innovative materials and industrial applications.

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