Processing-Structure-Microstructure-Property Relationships in Polymer Nanocomposites

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2008-01-31

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The optimal development of polymer nanocomposites using carbon nanotube (CNTs) and carbon nanofiber (CNFs) fillers requires a complete understanding of processing-structure-property relationships. The purpose of this understanding is to determine the optimal approach for processing polymer nanocomposites with engineered microstructures and enhanced material properties. In this research, two processing techniques were investigated: solvent processing and twin screw extrusion. The former is a batch process which employs mixing a polymer solution with a filler suspension using long mixing times and low levels of shear mixing. The latter is a continuous process that mixes polymer melts with solid nanoscale ingredients using high levels of shear mixing for a short mixing time. Previous studies conducted on polymer-CNT/CNF using these processes have focused mainly on processing-microstructure and structure-property relationships using one technique or the other. This research focuses on understanding the processing-property relationships by comparing the structure-property relationships resulting from the two processes. Furthermore, the effect of ingredients and processing parameters within each process on microstructure and structure-property relationships was investigated. The microstructural features, namely, distribution of agglomerates, dispersion, alignment, and aspect ratio of the filler were studied using optical, scanning electron, confocal and transmission electron microscopy, respectively. The composition of the filler was determined using thermogravimetric analysis. The electrical, rheological, thermo-oxidative and mechanical properties of the composites were also investigated. Many significant insights related to processing-structure-property relationships were obtained including: (a) deagglomeration is a critical combination of the magnitude of shear rate and the residence time, (b) the structure-property relationships can be modeled using a new methodology based on the degree of percolation by representing the material as an interpenetrating phase composite, (c) annealing can re-establish interconnectivity and improve electrical properties, (d) the degree of dispersion can be resolved using thermogravimetric analysis, and (e) increasing extrusion speed inhibits thermal decomposition and begins to asymptotically increase strength and stiffness through reduction in aspect ratio and size of agglomerates. Finally, a new combinatorial approach was developed for rapidly determining processing-structure relationships of polymer nanocomposites. This dissertation has broad implications in the processing of high performance and multifunctional polymer nanocomposites, combinatorial materials science, and histopathology.

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