Kinetic modeling frameworks for the chemical recycling of polyolefins
Ge, Jiankai
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https://hdl.handle.net/2142/132535
Description
Title
Kinetic modeling frameworks for the chemical recycling of polyolefins
Author(s)
Ge, Jiankai
Issue Date
2025-12-01
Director of Research (if dissertation) or Advisor (if thesis)
Peters, Baron G
Doctoral Committee Chair(s)
Peters, Baron G
Committee Member(s)
Schweizer, Kenneth S
Mironenko, Alexander V
Bickel Rogers, Elizabeth
Department of Study
Chemical & Biomolecular Engr
Discipline
Chemical Engineering
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Chemical recycling
Kinetics
Modeling
Polyolefins
Language
eng
Abstract
Plastics have become essential to modern life, yet their durability has led to a global waste challenge (> 360 Mt per year). Among this gigantic among of plastic wastes, most of them have been landfilled, incinerated, or even mismanaged. Only a small portion of them have been recycled. However, current mechanical recycling cannot solve the issue that material properties will degrade during the recycling process. Chemical recycling offers new pathways by converting polymers back into valuable molecules selectively, but the underlying reactions are extremely complex due to a wide range of chain lengths in polymers, different features and functional groups among products, and different phases in a reactor scale that stretch traditional kinetic tools past their limits.
This dissertation develops a set of kinetic modeling frameworks for the chemical recycling of polyolefins. First, we examine mass-transfer limits using a diffusion–reaction model that describes how processive catalysts perform inside stagnant and stirred polymer melts. The core of the dissertation then advances the mechanistic modeling for polyethylene (PE) and polypropylene (PP) depolymerization. We begin with a length-agnostic microkinetic model (MKM) that includes all surface and bulk species for a model compound, allowing extraction of rate constants and validation of mechanistic hypotheses from experiments. Then, we started with PP pyrolysis mechanism to build a continuous feature x population balance models (PBMs) that resolve the realistic molecular weight distribution (MWD) while keeping track of the evolution of functional motifs such as double bonds or end groups with a feature balance framework (FBM). We show how FBMs can be coupled to PBMs to follow both detailed kinetics and evolving MWDs across multiple species and predict experimental observables and MWDs.
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