Polymer particle size distribution optimization

Research on the modelling, optimization and control of emulsion polymerization (latex) reactors and processes has been expanding rapidly as the chemistry and physics of these systems become better understood, and as the demand for new and improved latex products increases. The objectives are usually to optimize production rates and/or to control product quality variables such as polymer particle size distribution (PSD), particle morphology, copolymer composition, molecular weights (MW s), long chain branching (LCB), crosslinking frequency and gel content. 

These models require information about mean velocity and the turbulence field within the stirred vessels. Computational flow models can be developed to provide such fluid dynamic information required by the reactor models. Although in principle, it is possible to solve the population balance model equations within the CFM framework, a simplified compartment-mixing model may be adequate to simulate an industrial reactor. In this approach, a CFD model is developed to establish the relationship between reactor hardware and the resulting fluid dynamics. This information is used by a relatively simple, compartment-mixing model coupled with a population balance model (Vivaldo-Lima et al., 1998). The approach is shown schematically in Fig. 9.2. Detailed polymerization kinetics can be included. Vivaldo-Lima et a/. (1998) have successfully used such an approach to predict particle size distribution (PSD) of the product polymer. Their two-compartment model was able to capture the bi-modal behavior observed in the experimental PSD data. After adequate validation, such a computational model can be used to optimize reactor configuration and operation to enhance reactor performance. 

Research in this area shows great potential. Over the past 30 years, dual systems have been applied mainly in the paper industry. The applicatimi of PECs, described as particle-forming flocculants, provides new possibilities in solid-liquid separation processes. For an effective system, the application parameters have to be optimized (e.g. polymer type, cmicentratiOTi, charge, molecular weight). Therefore, direct and efficient methods for the characterization of the flocculation behavior (sedimentation velocity, packing density of the sludge, particle size distribution) are necessary and will be described. 

For bright masstone appUcations, it is important to optimize the cleanness or color purity of a pigment The cleaimess can be roughly interpreted from the reflectance spectra by the difference between the maximum and rriinimum reflectances. A more accurate approach is to develop modified color values. Correlations can be developed from grind studies to account for changes in scatter due to differences in particle size distributions. For the NiSbTi yellows, a formula to calculate b values (e.g. b =b -3AL ) can be developed for a particular polymer system to account for the increased scatter and whiteness from finer-sized pigments. 

This parameter is closely related to the economics of any type of industrial process. An optimized size, shape and bulk density of the polymer powder allows the highest polymer content and thus the highest reactor throughput. A correct particle size distribution without fines or coarse particles will simplify many industrial operations like centrifugation, drying, fluidization or transportation of the powder. 

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