Doctoral Dissertations

Date of Award

8-2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Energy Science and Engineering

Major Professor

Chad Duty

Committee Members

Brett Compton, Vlastimil Kunc, Mark Dadmun

Abstract

Although additive manufacturing (AM) has revolutionized the manufacturing industry through rapid and complex geometry fabrication capabilities at a fraction of the cost, only a small fraction of the materials used for traditional manufacturing are compatible with AM. Emerging applications in polymer AM motivate the need for production and development of new materials with a broader range of thermal and mechanical properties. Advancements in AM have also led to new system development such as Big Area Additive Manufacturing (BAAM) systems at Oak Ridge National Laboratory, capable of processing high-performance thermoplastics and composites. As the application space for three-dimensional printed components continues to grow, it is necessary to identify appropriate processing conditions and expand the current selection of high-performance thermoplastics and fiber reinforced composites for AM systems. However, there is no formal process for designing, screening, and evaluating the printability of these high-performance thermoplastics and composite systems. Traditional polymer characterization techniques utilizing thermal and rheological material properties have been effectively employed in other polymer processing methods such as injection molding to identify suitable processing conditions. Therefore, to expand the current high-performance material selection for BAAM using industrial grade pellets, these techniques are employed to establish the relationships between fundamental material properties such as thermal and rheological properties and AM processing parameters. Overall, this work is an attempt to expand the current selection of highperformance feedstock on large format AM systems such as BAAM using thermal and rheological characterization techniques. This is achieved by predicting their extrudability through the nozzle, quantifying the impact of pressure transients on extrusion, and identifying appropriate processing conditions for these materials to provide a basis for optimizing the use of current high-performance materials as AM feedstock.

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