Date of Award
2023-05-01
Degree Name
Doctor of Philosophy
Department
Materials Science And Engineering
Advisor(s)
David A. Roberson
Abstract
This dissertation begins with an overview of novel polymer systems which have been developed by the Polymer Extrusion Lab at the University of Texas at El Paso. Many composite polymer systems have been created using many different polymers as well as ceramics and metals primarily in the form of powders added to the bulk polymer. The bulk of this work entails a study that was conducted to develop and characterize the mechanical, shape memory and self-healing properties of three polymer blends: polylactic acid (PLA) combined with maleated styrene-ethylene-butylene-styrene (SEBS-g-MA), acrylonitrile butadiene styrene (ABS) combined with maleated styrene-ethylene-butylene-styrene (SEBS-g-MA), and polylactic acid (PLA) combined with thermoplastic polyurethane (TPU). These blends were melt compounded at a 50% by weight ratio in a twin-screw extruder into filament for use in desktop FFF style 3D printers. Additively manufactured test samples were made using the extruded filament and injection molded samples were made after pelletizing the filament. The three polymer blends were evaluated in both 3D printed and injection molded forms to determine their mechanical and shape memory properties. To evaluate the shape memory properties, samples were tested for tensile strength in their as-fabricated forms and compared to their tensile strength after being subjected to 25%, 50%, and 100% elongation of their gauge length. This was done for samples in both additively manufactured and injection molded forms both with and without being allowed to dwell under load at the prescribed amount of elongation. The averages of the tensile strength for each polymer blend in both manufacturing forms were plotted against the amount of deformation from which they were recovered. A line of best fit was generated for each and the slope of the equation was divided by the y-intercept to generate a value we are calling the "self-healing parameter" that indicates the percent of baseline tensile strength which is lost after being recovered from 100% elongation.
Language
en
Provenance
Recieved from ProQuest
Copyright Date
2023-05-01
File Size
p.
File Format
application/pdf
Rights Holder
Truman James Word
Recommended Citation
Word, Truman James, "Characterization of novel self-healing polymer blends for additive manufacturing" (2023). Open Access Theses & Dissertations. 3871.
https://scholarworks.utep.edu/open_etd/3871