Process modeling for the synthesis of unsaturated polyester

This work presents a dynamic model for a polyesterfication reaction in a system containing a batch‐wise operating reaction vessel connected to a flash separation unit. This model includes kinetics, description of the change of rate order during the reaction, the polymer nonrandom theory of liquid (N...

Full description

Saved in:
Bibliographic Details
Published in:Polymer engineering and science 2011-12, Vol.51 (12), p.2495-2504
Main Authors: Shah, M., Zondervan, E., de Haan, A.B
Format: Article
Language:English
Subjects:
Applied sciences
Chemical properties
Chemical synthesis
Distillation
Dynamical systems
Exact sciences and technology
Glycols
Kinetics
Mathematical models
Methods
Organic polymers
Physicochemistry of polymers
Polycondensation
Polyester resins
Polyesters
Preparation, kinetics, thermodynamics, mechanism and catalysts
Production processes
Propylene
Regression analysis
Ring opening
Thermodynamic models
Thermodynamics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work presents a dynamic model for a polyesterfication reaction in a system containing a batch‐wise operating reaction vessel connected to a flash separation unit. This model includes kinetics, description of the change of rate order during the reaction, the polymer nonrandom theory of liquid (NRTL) nonideal thermodynamic model based on NRTL and mass balances. The reaction between maleic anhydride and propylene glycol has been taken as a case study. The reaction scheme is complex, and the proposed model takes four types of reactions into account, ring opening, polyesterfication, isomerization, and saturation reactions. The acid value of the polyester, number–average molecular weight, distilled mass, and glycol concentration in the distillate have been subsequently used to validate the model, and the model predicts these important variables reliably. The process description is improved by using the vapor–liquid equilibrium data predicted from the polymer NRTL model. Particularly, the prediction of distilled mass [regression coefficient (R2) = 0.995] and the prediction of propylene glycol concentration (R2 = 0.97) in the distillate are significantly improved. POLYM. ENG. SCI., 2011. © 2011 Society of Plastics Engineers
ISSN:0032-3888
1548-2634
DOI:10.1002/pen.22038