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Nanostructure-Based Modeling and Experimental Characterization of Electrical Conductivity of Carbon Nanotube Networks

Carbon nanotubes (CNTs) possess exceptional electrical properties. Networks of densely packed nanotubes that are formed by intercontacted or interconnected nanotubes and bundles were observed to form electrically conducting pathways over macroscopic dimensions and can be used for fabricating electronic devices and multifunctional composites. However, the electrical conductivity of these macroscopic networks is much less than the individual CNT's performance, primarily due to the large contact resistance between nanotubes. Many factors contribute to the contact resistance, and the majority of these factors are difficult to directly measure and control due to nanoscale dimensions. The approach of physics-based simulation would help to understand the dominating factors of carbon nanotube networks (CNNs) conductivity. In this thesis work, experimental characterization of the nanostructures and electrical properties of CNNs were carried out, and an equivalent electrical circuit model of CNNs was improved to study the electrical conduction mechanism and properties. To systematically investigate the structure-property relationship between the conductivity of CNNs and their nanostructures, microscopic images of CNNs were characterized with image analysis software to obtain the CNT rope length and diameter distributions. Volume fractions of CNTs in these CNNs were also determined by experimental measurements and literature reported density of CNTs. Raman spectroscopy results were used to characterize the alignment degree of magnetically aligned CNNs. The electrical properties of CNNs, including electrical conductivity and current-carrying capacity tests, were carried out. The conductivities of various types of CNNs were obtained, including single-walled nanotubes (SWNTs), multi-walled nanotubes (MWNTs), and carbon nanofibers (CNF). CNNs of pure SWNTs possess the highest conductivity among all the networks studied. Another important electrical property, the current-carrying capacity, was also studied to understand the breakdown mechanism of CNNs. The tests were conducted to characterize the breakdown temperature and current density of the CNNs. It was determined that the breakdown of CNNs under high current stimuli was due to Joule heating. The modified electrical conductivity model is an electrical circuit simulation approach that reflects multiscale electrical conduction mechanisms and statistical nature of the CNNs. The model begins with nanoscale factors such as nanotube chirality and contact type, and then incorporates microscale factors such as dispersion and nanotube orientation, and further uses circuit computation simulation to calculate the bulk conductivity of the CNNs. Case studies were conducted to first validate the model and then reveal the structure-property relationships of different types of CNNs, including the effects of CNT orientation and chirality on the conductivity of the CNNs. The experimental results and developed model can be used to design and optimize CNNs for electrical applications. / A Thesis submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the
requirements for the degree of Master of Science. / Fall Semester, 2009. / September 11, 2009. / Includes bibliographical references. / Richard Liang, Professor Directing Thesis; Petru Andrei, Committee Member; Ben Wang, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_253281
ContributorsLi, Shu (authoraut), Liang, Richard (professor directing thesis), Andrei, Petru (committee member), Wang, Ben (committee member), Department of Industrial and Manufacturing Engineering (degree granting department), Florida State University (degree granting institution)
PublisherFlorida State University, Florida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text
Format1 online resource, computer, application/pdf
RightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them.

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