University of Illinois at Chicago
Browse
- No file added yet -

Photopolymerization-based Additive Manufacturing of Multimaterial Objects with Multiscale Features

Download (10.39 MB)
thesis
posted on 2023-08-01, 00:00 authored by Ketki Mahadeo Lichade
Additive manufacturing (AM) is a class of technology in which three-dimensional (3D) structures can be fabricated directly from a digital model by joining material from the bottom to the top, usually in a layer-by-layer fashion. However, current AM processes are mainly limited to single material and micro to mesoscale features. Recent design and advanced manufacturing research showed that objects with spatially-varied material compositions and multiscale features possess enhanced or even new superb properties, enabling a wide range of applications in biomedical, electronics, and mechanical fields. To realize such multimaterial multiscale manufacturing capabilities, extensive research efforts have been made to investigate the material distribution control strategies and nano-/micro-/meso- scale feature fabrication approaches. In particular, the photopolymerization-based AM processes (e.g., digital light processing, stereolithography, and two-photon polymerization) have been widely investigated, considering their ease of fabrication and high temporal and spatial control with micro- to nano-scale resolution. Despite recent advances, the full potential of current photopolymerization-based AM technologies has been restricted by several challenges. For instance, owing to the limited availability of photosensitive materials with contrasting properties, the use of particle-polymer composite with external field-assisted localized particle distribution has emerged as an alternative approach to engineer composites with desired functionalities. However, it is challenging or even impractical to apply these fields at the nano-/micro-scale, resulting in low accuracy and resolution in particle distribution control. Additionally, most of these approaches focus on fabricating either only spatially-varied particle-polymer composition or multiscale features, but not both simultaneously. In addition, the literature reported enhanced electrical and mechanical properties of the particle-polymer composites, but little was known about wetting properties and hydrodynamic functions. To close the aforementioned research gaps and facilitate the adoption of multimaterial multiscale AM techniques for a wide range of applications, this Ph.D. dissertation is conducted to (1) design surfaces with five-dimensional (5D) complexity (i.e., 3D geometry, 1D material composition, and 1D surface structure), (2) develop novel acoustic field-assisted photopolymerization-based additive manufacturing techniques for fabricating particle-polymer composite objects with spatially-varied compositions and multiscale surface structures. The acoustic field enables localized control of particle-polymer composite compositions, while the polymerization process enables multiscale curing, (3) model effects of process parameters on 5D printing accuracy to assist the determinations of process parameter settings in respective AM processes, and (4) validate the effectiveness of proposed multimaterial multiscale designs and the novel AM techniques in various applications, including fog harvesting, self-driven microfluidics devices, antireflective coatings, and microreactors. The outcomes of this Ph.D. dissertation will contribute to the advanced manufacturing of next-generation devices and surface engineering. This work not only brings a novel strategy to design and fabricate multimaterial multiscale polymer composite surfaces with preprogrammed functionalities but also paves the way for product innovations in a wide range of hydrodynamic, biomedical, electrical, or mechanical applications.

History

Advisor

Pan, Yayue

Chair

Pan, Yayue

Department

Mechanical and industrial engineering

Degree Grantor

University of Illinois at Chicago

Degree Level

  • Doctoral

Degree name

PhD, Doctor of Philosophy

Committee Member

Darabi, Houshang Li, Lin Anand, Sushant Ozevin, Didem

Submitted date

August 2023

Thesis type

application/pdf

Language

  • en

Usage metrics

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC