2011
DOI: 10.1002/mren.201100004
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Modeling of Phase Inversion and Particle Stability in the Dispersion Polymerization of Methyl Methacrylate in a Non‐polar Hydrocarbon Solvent

Abstract: A detailed model is presented to analyze the phase inversion in the dispersion polymerizations of methyl methacrylate (MMA) in non‐polar solvents. The reaction conditions under which the polymer particles lose stability and the reaction system phase inverts are investigated. At high solvent/monomer ratios, well‐defined micron‐sized polymer particles are produced even in the absence of stabilizer. However, low solvent/monomer ratios or stabilizer concentrations yield porous structures after a massive agglomerat… Show more

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Cited by 5 publications
(6 citation statements)
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“…Therefore, the development of a mathematical model is essential to predict the morphological characteristics of the arils of the pomegranate‐like structure. In a previous work, we have investigated the evolution of particle size distributions for a regular dispersion polymerization of MMA in n ‐hexane through a dynamic population balance equation (PBE) . The same approach is applied here to study the heterogeneous region of the suspended droplets.…”
Section: Mathematical Modelmentioning
confidence: 99%
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“…Therefore, the development of a mathematical model is essential to predict the morphological characteristics of the arils of the pomegranate‐like structure. In a previous work, we have investigated the evolution of particle size distributions for a regular dispersion polymerization of MMA in n ‐hexane through a dynamic population balance equation (PBE) . The same approach is applied here to study the heterogeneous region of the suspended droplets.…”
Section: Mathematical Modelmentioning
confidence: 99%
“…Considering only homogeneous nucleation of primary sub‐particles, S 0 ( t ) can be expressed in terms of the polymerization rate in the solvent‐rich phase (i.e., Rp,1=knormalp[M]1[normalR]1) and of the volume of the primary sub‐particles ( v 0 ), as follows: S0=Rp,1MnormalMρtrue‾normalP(1φM,2)v02 …”
Section: Mathematical Modelmentioning
confidence: 99%
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