Bayesian Modeling and Markov Chain Monte Carlo Simulations for a Kinetic Study of Homo- and Co- Polymerization Systems (original) (raw)

Bayesian modeling and Markov Chain Monte Carlo simulation were developed for a kinetic study of homopolymerization and copolymerization systems at the molecular scale. Two copolymerization models—the terminal unit model and the penultimate unit model—were considered, with prior estimates of kinetic parameters obtained through L1-norm robust statistics. The methodology was employed to update prior estimates using experimental data and likelihood functions, and the joint posterior probability regions for reactivity ratios were calculated. The method demonstrated effectiveness in distinguishing between copolymerization models and was validated in free radical polymerization for binary systems, ultimately providing insights into the evolution of species during polymerization while significantly reducing computational time by adapting Monte Carlo event steps.