Optimized species growth in epoxy polymerization with real-coded NSGA-II

Satisfaction of twin objectives of maximization of M_n along with minimization of PDI do not necessarily guarantee the maximization of concentration of desired species in a semibatch epoxy polymerization process. As the final product consists of a number of polymer species, a need is felt to perform an advanced optimization study to come up with such process conditions for which the selective growth of a particular polymer species is maximized in minimum possible processing time and the population of other species should be at their lowest values. These above-mentioned conflicting objectives frame the platform for a multi-objective optimization problem, which is solved here using a real-coded non-dominated sorting genetic algorithm or NSGA II and Pareto optimal solutions are obtained. The decision variables are discrete addition rates of various ingredients, e.g. the amount of addition of bisphenol-A (a monomer), sodium hydroxide and epichlorohydrin at different time steps. All species balance equations, bounds on M_n, PDI and addition amounts are treated as constraints. Results are very promising in terms of optimized operations for selective enhancement of desired polymer species for the epoxy polymerization process. Total additions are kept very close to available experimental conditions to minimize probable extrapolation errors. It has been observed that preferential oligomer production is extremely difficult for epoxy polymerization. Lower chain polymers are the only choice for a good quality, stable polymer product.