2010
DOI: 10.1002/aic.12148
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Measurement based modeling and control of bimodal particle size distribution in batch emulsion polymerization

Abstract: In this article, a novel modeling approach is proposed for bimodal Particle Size Distribution (PSD) control in batch emulsion polymerization. The modeling approach is based on a behavioral model structure that captures the dynamics of PSD. The parameters of the resulting model can be easily identified using a limited number of experiments. The resulting model can then be incorporated in a simple learning scheme to produce a desired bimodal PSD while compensating for model mismatch and/or physical parameters va… Show more

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Cited by 9 publications
(5 citation statements)
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“…[1][2][3][4][5][6] Such models are not only useful for a better understanding of the underlying reaction mechanisms but also allow optimization and control of the product quality and process conditions. [7][8][9] Different stabilization systems have been proposed to prevent particle coagulation in conventional emulsion polymerization, using for instance anionic [10,11] or cationic [12,13] surfactants. Steric stabilizers can also be employed.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…[1][2][3][4][5][6] Such models are not only useful for a better understanding of the underlying reaction mechanisms but also allow optimization and control of the product quality and process conditions. [7][8][9] Different stabilization systems have been proposed to prevent particle coagulation in conventional emulsion polymerization, using for instance anionic [10,11] or cationic [12,13] surfactants. Steric stabilizers can also be employed.…”
Section: Introductionmentioning
confidence: 99%
“…[ 1–6 ] Such models are not only useful for a better understanding of the underlying reaction mechanisms but also allow optimization and control of the product quality and process conditions. [ 7–9 ]…”
Section: Introductionmentioning
confidence: 99%
“…To further assess the role of mixing, modeling of the particle size distribution of the precipitation process was performed via coupling of computational fluid dynamics (CFD) with the micromixing model and with the solid model of the direct numerical simulation–population balance equation (DNS–PBE) approach. Population balance equations (PBEs) have been successfully implemented to predict particle and crystal formation dynamics . Because mixing is an important aspect of precipitation modeling, several works have attempted to couple the PBEs with CFD to investigate the impact of various steps on the nanoparticle size distribution.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, it was developed as a population balance equation (PBE) . PBE has been applied successfully in simulating particle and crystal evolution, such as nucleation, growth, aggregation, and breakage in numerous studies. Computational fluid dynamics (CFD), an effective tool in revealing complex fluid behaviors, has also been employed in recent years to describe particle phenomena. Furthermore, by taking the respective advantages into consideration, some hybrid CFD–PBM (population balance model) coupled models have been put forward to describe particle formation in two-phase flow by solving the CFD model to obtain the entire flow behavior, as well as using PBE for the particle size distribution (PSD). , However, previous studies mainly focused on crystallization without involving the chemical reactions, ,, or a few others were limited to gas–liquid system. ,,,, The reason is that these two kinds of reaction follow certain classical kinetics. Therefore, the simulation of nanoparticle formation in a wet chemical continuous-flow synthesis process (liquid–solid system) is a novel field due to lack of appropriate reaction kinetics data.…”
Section: Introductionmentioning
confidence: 99%