화학공학소재연구정보센터
Polymer Reaction Engineering, Vol.11, No.4, 737-814, 2003
Modelling and simulation of complex aspects of multicomponent emulsion polymerization
The focus of this work is the refinement of a general mechanistic simulator for multi-component free radical emulsion polymerization. The effort includes three main areas of simulator development, namely, model development, database development and simulator verification. The model is general and can predict the dynamic evolution of emulsion polymerizations for a variety of monomer systems while giving the user as many "model options" as possible for fine tuning. The model has been extensively tested for several copolymerization systems including combinations of the monomers, styrene, methyl methacrylate, methyl acrylate, butyl acrylate, acrylonitrile, 2-ehtyl hexyl acrylate and vinyl acetate. The simulator has been developed using a mechanistic framework that is analogous to the multicomponent free radical bulk and solution polymerization model developed in Gao and Penlidis (1996, 1998) and is a continuation of Gao and Penlidis (2002), which explored emulsion homopolymerization and preliminary copolymerization modelling. The model includes a rigorous thermodynamic approach for determining monomer partitioning, the inclusion of both homogeneous and micellar particle nucleation as well as the ability to simulate various reactor configurations including batch and semi-batch operation. Database items used in the simulator are chosen based on direct experimental data (when available) or from analogous situations and parameter estimations. The model has been developed in a general fashion such that a monomer, initiator, emulsifier, transfer agent etc. can be added to the database at any time. Furthermore, the model has been extended to predict particle size distribution of the resulting emulsion. This model has been tested with many case studies against a variety of experimental data. and can be used for design of experiments for production of emulsions with customized distributions.