Abstract
Step-growth polymerization (SGP) products are ubiquitous, but the theoretical understanding of SGP reactions has stagnated since the introduction of Flory's classical theory. Flory's model based on two key assumptions-equal reactivity of functional groups and the absence of cyclization-falls short in guiding real-world polymerization processes. In this work, we extend Flory's model by accounting for individual reaction probabilities and cyclization tendencies, making it applicable to real SGP situations. Moreover, we have developed a top-down algorithm capable of extracting crucial information about polymer growth and cyclization from molecular weight data during the SGP process. By applying this expanded model to real SGP experiments, we reveal their kinetic mechanisms and demonstrate how concentration affects polymerization kinetics, offering valuable insights for predicting and controlling the polymer structure.