Date of Award

1-1-2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Mechanical Engineering and Applied Mechanics

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Yang Lin

Abstract

Microplastics (MPs) pose a growing challenge to the ecological system, prompting increasing research efforts in diverse directions. Accurate characterization of MPs is essential for understanding their properties, relying on efficient sampling and detection techniques. Additionally, studying the cytotoxic effects of MPs is critical for evaluating their impact on biological systems. Lab-on-chip (LoC) systems offer significant advantages for precise particle manipulation and compatibility with advanced analytical instrumentation, making them valuable for MP detection and characterization. Microfluidic-based on-chip cell-culturing systems provide a controllable, physiologically relevant microenvironment for more realistic in vitro tissue modeling. By leveraging advanced LoC concepts and integrating state-of-the-art machine learning models, cutting-edge material characterization, sustainable materials, and interdisciplinary design principles, this dissertation introduces innovative, cost-effective, and scalable LoC systems for MP detection, characterization, and cytotoxicity evaluation. We designed two microfluidic chips to sample MPs of different size ranges, one utilizing hydrodynamic trapping for MPs >5 μm and another employing tunable passive filtration for MPs >5 μm. Raman spectroscopy combining a convolutional neural network (CNN)-based model was used to identify MPs. For cytotoxicity evaluation, laboratory-controlled weathered MPs were tested on RAW264.7 and Caco-2 cells. Additionally, a physiologically relevant biaxial stretching microfluidic system was developed to assess cellular responses under long-term exposure to environmentally relevant MP concentrations. The systems presented in this dissertation have broad applications across various research fields and contribute valuable insights to the MP research community.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.