Healing-on-Demand Polymer Composites Based on Shape Memory Polyurethane Fibers and Polymeric Artificial Muscles

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.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

Mechanical Engineering

Year dc:date.available

2015

Author dc:creator

• Zhang, Pengfei

• polymer composites
• bio-materials
• artificial muscle
• shape memory effect
• healing-on-demand
• self-healing

Statement dc:rights

• unrestricted
• Release the entire work immediately for access worldwide.

Identifier

etd-07022015-173357
https://repository.lsu.edu/gradschool_dissertations/352

OAI identifier oai:identifier

oai:repository.lsu.edu:gradschool_dissertations-1351