Title
Distribution of functional groups in starved-feed semi-batch free radical copolymerization: An accelerated stochastic modeling approach
Conference Dates
May 20-25, 2018
Abstract
Maintaining the quality and cost-efficiency of industrialized materials often requires tradeoffs. For instance, while the majority of chains must be functionalized for end-use applications, there is also a desire to minimize the fraction of functional monomer used in the production of low molecular-weight resins for solvent-borne coatings. To address these questions, kinetic models must not only predict the overall copolymer composition and reaction rates but describe how the reactive groups are distributed as a function of polymer chain-length. In this work, a Kinetic Monte Carlo (KMC) approach is taken to construct a radical copolymerization model. While KMC provides a suitable description of the explicit sequence of chains, the time-consuming computational calculations often hinder the utilization of the method. It is shown that application of scaling methods introduced by Gao et al.1 combined with optimization of the information storage described by Chaffey-Millar et al.2 decreases drastically the computational time to a few minutes (i.e., ~40 times faster). Therefore, this approach allows computation of the complete copolymer composition distribution along with standard model output (average MWs and monomer concentration profiles) in a time not much greater than that required by a deterministic model, providing a solid foundation for optimization of the desired population of polymer chains under industrial conditions. The improved solution of the KMC is demonstrated through consideration of a previously published example of the radical copolymerization of glycidyl methacrylate (GMA) and butyl methacrylate (BMA) in which the average number of GMA units per chain is unity;3 as shown in Figure 1, the accelerated model provides the same accuracy in a fraction of the simulation time. In addition, the influence of methacrylate depropagation will be shown through the application of the model to the high-temperature copolymerization of BMA with 2-hydroxyethyl acrylate in a starved-feed semi-batch reactor.
Please click Additional Files below to see the full abstract.
Recommended Citation
Amin Nasresfahani and Robin A. Hutchinson, "Distribution of functional groups in starved-feed semi-batch free radical copolymerization: An accelerated stochastic modeling approach" in "Polymer Reaction Engineering X (PRE 10) (2018)", John Tsavalas, University of New Hampshire, USA Fouad Teymour, Illinois Institute of Technology, USA Jeffrey Stubbs, HP Inc., USA Jose R. Leiza, University of the Basque Country, Spain Eds, ECI Symposium Series, (2018). https://dc.engconfintl.org/prex/48