Date Approved

3-5-2021

Embargo Period

3-8-2022

Document Type

Dissertation

Degree Name

PhD Doctor of Philosophy

Department

Biomedical Engineering

College

Henry M. Rowan College of Engineering

Advisor

Beachley, Vincent Z.

Committee Member 1

Stanzione, Joseph F.

Committee Member 2

Galie, Peter

Keywords

Electrospinning, Nanofiber, Polymer

Subject(s)

Nanofibers; Electrospinning

Disciplines

Biomedical Engineering and Bioengineering | Chemical Engineering

Abstract

Electrospinning is an alternative manufacturing method, capable of producing fibers with nanoscale diameters from a wide range of different polymers in a process which is relatively simple and inexpensive in comparison to other forms of nanofiber production. This has made electrospinning the subject a great deal of research as a method of producing nanofibers for various high-performance applications. However, electrospun nanofiber tensile strength is weak in comparison to conventional fibers of the same material, preventing widespread use and marketization. This disparity in mechanical strength is attributed to poor polymer chain alignment in individual fibers, caused by the absence of a post-drawing stage which is critical to conventional fiber manufacture. In this work, the use of an automated track processing system for post-drawing electrospun nanofibers is investigated with regards to its effects on polymer chain orientation, fiber crystallinity, tensile strength, and fiber morphology. Results illustrated that automated track post-drawing improved polymer chain alignment to the fiber axis, increased tensile strength, and was compatible with various polymers. In addition, the post-drawn fibers were able to retain a greater degree of mass and tensile strength during enzymatic degradation. This work represents the development of a novel method of electrospun nanofiber processing that potentially overcomes the obstacles of poor polymer chain alignment and tensile strength which prevent their utilization and market availability.

Download

Share

COinS