Multiscale models for polymer upcycling

Millions of tons of plastic waste are discarded every year, most of it ending up in landfills or the ocean. While some is recycled, the most common plastic recycling techniques used today either involve simple burning of plastic waste, or mechanically breaking down waste into small pellets that may be repurposed in less valuable products with lower engineering demands. Chemical and catalytic upcycling processes could help to realize a circular plastics economy, by breaking down plastic waste into products that may be reused in products of equal or greater value, such as lubricants, oils, and chemical feedstocks. However, existing models for testing mechanistic hypotheses and designing catalysts remain primitive. Coarse-graining and other molecular simulation techniques can capture the interactions between polymer chains and a catalyst surface but cannot explore the time and length scales of depolymerization experiments. Numerical techniques such as population balance models are easily extended to these scales, but in turn often avoid introducing polymer-surface interactions that complicate their development and solution. In this thesis, we develop new methods for modeling the depolymerization of linear polymers. These models incorporate catalytic mechanisms to predict the time evolution of molecular weight distributions. We consider models for homogeneous and heterogeneous catalysts, including catalysts that cut at random locations, catalysts that cut at chain ends, and catalysts that incorporate processive motifs. We develop solutions to the models, illustrate the effect of adsorption parameters on the evolving molecular weight distribution, identify signatures of heterogeneous mechanisms, and provide a framework for analysis of experimental data to obtain underlying catalytic rate parameters. Where population balance methods are unsuitable, we develop models at alternative scales that better align with experimental observables. These models incorporate unique catalytic mechanisms such as tandem aromatization and competitive adsorption to predict reaction products and extract kinetic parameters.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Chemical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Yappert, Ryan Davis

Contributors dc:contributor

• Peters, Baron G
• Moore, Jeffrey S
• Sing, Charles E
• Statt, Antonia

• polymer upcycling
• processive catalysis
• population balance models
• mathematical modeling
• lumped models

Statement dc:rights

• Copyright 2022 Ryan Yappert

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/116204

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F116204