Chapter 13: Applications of Differential Evolution in Polymerization Reaction Engineering

This chapter focuses on applications of differential evolution (DE) in the field of polymerization reaction engineering. DE can be applied for modeling and for process optimization; it is being used in different variants, according to the specific characteristics of the system and the required accuracy. First, difficulties in modeling the polymerization processes are presented to justify the use of artificial intelligence tools, particularly artificial neural networks (ANN) and DE. These difficulties are related to the complexity of the reaction medium, lack of complete knowledge of the reaction mechanism, problems in developing and solving phenomenological models, their accuracy and/or potential for inclusion in on-line control procedures. Neuro-evolutive techniques are recommended methodologies for modeling and optimizing such complex polymerization processes. A special section is dedicated to general aspects of how DE can be used in combination with ANN for developing optimal neural models and for determining optimal operating conditions. Two applications: synthesis of polyacrylamide based hydrogels and of siloxane-siloxane copolymers, are discussed in detail.