457724 Bottom-up Approach to Constructing a Polymerization Process Model: Leveraging New Insights for Improved Manufacturing Performance

Wednesday, November 16, 2016: 8:30 AM
Yosemite A (Hilton San Francisco Union Square)
Andrew J. Adamczyk1, Agnes Derecskei-Kovacs1, James R. Boulton2 and Michael P. Popule2, (1)Advanced Analytical, Materials Technology, Air Products and Chemicals, Inc., Allentown, PA, (2)Process R&D, Materials Technology, Air Products and Chemicals, Inc., Allentown, PA

Synthetic polymer materials are commonly used in textiles, automotive applications, carpets, and sportswear due to their high durability and strength. Scale-up and commercial production of these polymer materials is an active research field that has been around for decades and thus spans many types of chemistries. As computational resources are becoming more readily available, new methods are being applied to this broad field to improve manufacturing performance. This presentation summarizes key learnings of a joint effort between process technology and computational modeling groups to provide new insights to aid process improvements. Detailed discussion will be focused on how computational modeling efforts supported by experimental kinetics studies have been leveraged to contribute to process development. At the atomistic level, Density Functional Theory (DFT) was employed to deliver insights into the underlying reaction kinetics and thermochemical properties. Also, kinetic model building and validation schemes will be explained to demonstrate how first-principles-based quantum chemical calculations have been incorporated to construct a predictive process model for polymer chemistry.

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