Industrial process of copolymerization and terpolymerization of acrylonitrile: experimental approach and statistic modeling. (4th November 2015)

• Record Type: Journal Article
• Authors: Marlet, J. M. F.; Bittencourt, E.
• Is Part Of: Advanced manufacturing. Volume 1:Number 3(2015)
• Publication Date: 2015-11-04
• Subjects: Acrylonitrile, -- Aqueous suspension copolymerization, -- Design of experiments, -- Statistic modeling, -- Simulation; Composite materials -- Periodicals; Polymers -- Periodicals; 620.19205
• DOI: 10.1080/20550340.2015.1114800
• Languages: English
• ISSNs: 2055-0340

Abstract

Graphical Abstract: The interest for models on a polymerization plant of acrylonitrile is (a) to predict the maximum capacity of an industrial reactor, (b) to increase the robustness of the process by defining stable operational conditions, and (c) to help the development of new copolymers. Using design of experiments (DOE), the copolymerization and terpolymerization of acrylonitrile with vinyl acetate and methyl-2 propene-1 sodium sulfonate were studied in aqueous suspension initiated by the redox system KClO3 /NaHSO3 /Fe 2+ . The molar fraction of the copolymers and terpolymers produced ranged from 93.0 to 98.2% for acrylonitrile, from 1.7 to 7.0% for vinyl acetate, and from 0.0 to 0.5% for sodium sulfonate. The mass molecular weight ranged from 76 000 to 419 000 g/gmol. Experiments were done in a pilot plant, consisting of 227 L of continuously stirred tank reactor, stripping and recycle systems, drum filter, and band dryer. The experiments were conducted according to a fractioned factorial 2 8 − 3 matrix with five central points. A statistic kinetic model was built, which explains well the copolymerization and terpolymerization of acrylonitrile. This model was applied with success on an industrial polymerization reactor, showing the potential of production increase, confirming the robustness of the process, and supporting the development of new copolymers of acrylonitrile. The focus of this paper is the development of a kinetic statistical polymerization model, the criteria to interrupt the regression analysis, and its application in the understanding of the polymerization phenomena.