A reduced-order multiscale model of a free-radical semibatch emulsion polymerization process

Free-radical emulsion polymerization is a heterogeneous process where simultaneous and competitive physicochemical events occur over a wide range of time/length scales. Although a highly accurate representation of the process is possible by multiscale modeling, common approaches face several issues, including the stochastic nature of finer scales, the timely exchange of information between scales, and the high computational load for the model solution. In this work, a reduced-order computationally-tractable multiscale model is proposed while preserving a good predictive capability. The model integrates microscopic-scale calculations based on kinetic Monte Carlo simulations (stochastic), a mesoscopic-scale representation of the particle size distribution through a novel statistical approach and a deterministic description of the macroscopic-scale. The proposed model resulted in faster satisfactory predictions (compared to the model based on the Fokker Planck Equation) of traditional macro and mesoscopic variables, along with the average number of free radicals and secondary nucleation on a microscopic scale.