Large-scale computational polymer solubility predictions and applications to dissolution-based plastic recycling

Journal Article · 08 May 2023 · Green Chemistry

DOI: https://doi.org/10.1039/d3gc00404j · OSTI ID:1974463

Zhou, Panzheng ^[1]; Yu, Jiuling ^[2]; Sánchez-Rivera, Kevin L. ^[2]; Huber, George W.  ^[2]; Van Lehn, Reid C.  ^[2]

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1. Univ. of Wisconsin, Madison, WI (United States); University of Wisconsin-Madison
2. Univ. of Wisconsin, Madison, WI (United States)

Dissolution-based plastic recycling is a promising approach to separate and recover high quality pure polymer resins from multicomponent plastic waste by exploiting differences in polymer solubility. The design of a dissolution-based polymer recycling process requires the selection of appropriate solvent systems and operating temperatures to dissolve only target polymers. Determining these parameters experimentally is challenging due to the wide range of solvents and temperatures possible for a given set of target polymers. In this work, we report a computational scheme that employs molecular dynamics simulations and the Conductor-like Screening Model for Realistic Solvents to predict polymer solubilities. Using this scheme, we established a computational solubility database for 8 common polymers and 1007 solvents at multiple temperatures and measured selected solubilities experimentally to validate computational predictions. Analysis of functional groups within this large database then provides chemical heuristics relating the molecular structures of good and non-solvents for selected polymers. We further developed a tool that automates the selection of solvents for all possible sequences in which target polymers can be selectively dissolved to guide the design of dissolution-based plastic recycling processes. Here, we demonstrate the application of these methods via multiple experimental case studies of representative dissolution-based polymer recycling processes in which pure polymer resins were successfully recovered from physical mixtures of polymers.

• Research Organization: Univ. of Wisconsin, Madison, WI (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO)
• Grant/Contract Number: EE0009285
• OSTI ID: 1974463
• Alternate ID(s): OSTI ID: 1974308
• Journal Information: Green Chemistry, Journal Name: Green Chemistry Vol. 25; ISSN 1463-9262
• Publisher: Royal Society of ChemistryCopyright Statement
• Country of Publication: United States
• Language: English