Doctor of Philosophy (PhD)
In this dissertation, the healing-on-demand polymer composites based on shape memory polyurethane fibers and artificial muscles are investigated, for understanding and developing a novel healing-on-demand composite so that it would be used for industrial applications that could heal structural-length scale damage and leaking autonomously, repeatedly, efficiently, timely, and molecularly. Firstly, the structural relaxation behavior of shape memory polyurethane (SMPU) fiber was studied by theoretical analysis and experimental test. Then, a self-healing composite based on cold-drawn short SMPU fiber was prepared and tested for evaluating its crack-healing performance. After that, polymer artificial muscle based healing-on-demand composite was developed and characterized. Based on the systematic research results, the study on fishing line artificial muscle reinforced composite for impact mitigation and on-demand damage healing was conducted. Future studies to grow this research area are discussed.
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Zhang, Pengfei, "Healing-on-Demand Polymer Composites Based on Shape Memory Polyurethane Fibers and Polymeric Artificial Muscles" (2015). LSU Doctoral Dissertations. 352.