Selection of Property Methods and Estimation of Physical Properties for Polymer Process Modeling

Abstract

This chapter introduces novel methodologies for characterizing phase equilibrium and estimating physical properties crucial to polyolefin manufacturing. It presents an in-depth discussion on the polymer nonrandom two-liquid (POLYNRTL) activity coefficient model (ACM), and the polymer Sanchez-Lacombe (POLYSL) and the polymer perturbed-chain statistical fluid theory (POLYPCSF) equations of state (EOS). These innovative approaches offer specific guidelines for selecting the appropriate polymer ACM or EOS tailored to specific polyolefin processes. A significant highlight is the detailed coverage of the POLYNRTL ACM, including a practical workshop for estimating POLYNRTL binary interaction parameters using the UNIFAC method. The chapter also explores the prediction of polymer physical properties through the Van Krevelen group contribution method, providing a hands-on workshop for estimating the physical properties of copolymers. Additionally, it introduces advanced techniques for parameter estimation using data regression tools, applied to both the POLYSL and POLYPCSF EOS models. Furthermore, the chapter addresses the correlation of critical polyolefin product quality indices, such as melt flow rate or melt index and polymer density, providing insights that enhance the understanding and optimization of polyolefin manufacturing processes. This is a preprint version of a chapter from our book - Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing. Please cite the original work if referenced [52,56]