Carbon nanotubes (CNTs) are known to exhibit outstanding mechanical, electrical, thermal, and coupled electromechanical properties. CNTs can be employed towards the design of an
innovative strain sensor with enhanced multifunctionality due to their load carrying capability, sensing properties, high thermal stability, and outstanding electrical conductivity. All
these features indicate the prospect to use CNTs in a very wide range of applications, for instance, highly sensitive resistance-type strain/force sensors, wearable electronics, flexible
microelectronic devices, robotic skins, and in-situ structural health monitoring. CNT-based strain sensors can be divided into two different types, the individual CNT- based strain sensors
and the ensemble CNT-based strain sensors e.g. CNT/polymer nanocomposites and CNT thin films. In contrast, to individual CNT-based strain sensors with very high gauge factor (GF) e.g.
~3000, the ensemble CNT-based strain sensors exhibit very low GFs e.g. for a SWCNT thin film strain sensor, GF is ~1. This research discusses the mechanisms and the optimizing principles
of a SWCNT thin film piezoresistive sensor, and provide an experimental validation of the numerical/analytical investigations. The dependence of the piezoresistivity on key parameters like
alignment, network density, bundle diameter (effective tunneling area), and SWCNT length is studied. The tunneling effect is significant in SWCNT thin films showing higher degrees of
alignment, due to greater inter-tube distances between the SWCNTs as compared to random oriented SWCNT thin films. It can be concluded that SWCNT thin films featuring higher alignment
would have a higher GF. On the other hand, the use of sparse network density which comprises of aligned SWCNTs can as well intensify the tunneling effect which can result to a further
increase in the GF. In addition, it is well-known that percolation is greatly influenced by the geometry of the nanotubes e.g. bundle diameter and length. A study on the influence of
bundle diameter of SWCNTs on the piezoresistivity behavior of mechanically drawn SWCNT thin films showed the best performance with an improved GF of ~10 when compared to the randomly
oriented SWCNT thin films with GF of ~1. The non-linear piezoresistivity of the mechanically drawn SWCNT thin films is considered to be the main mechanism behind the high strain
sensitivity. Furthermore, information about the average length and length distribution is very essential when examining the influence of individual nanotube length on the strain
sensitivity. With that in mind, we use our previously developed preparative ultracentrifuge method (PUM), and our newly developed gel electrophoresis and simultaneous Raman and
photolumiscence spectroscopy (GEP-SRSPL) to characterize the average length and length distribution of SWCNTs respectively. / A Dissertation submitted to the Department of Industrial and Manufacturing Engineering in partial fulfillment of the requirements for the degree of Doctor
of Philosophy. / Fall Semester 2015. / September 28, 2015. / Alignment, Gauge Fcator, Network density, Piezoresistivity, Single Walled Carbon nanotubes, Strain sensor / Includes bibliographical references. / Tao Liu, Professor Directing Dissertation; Sachin Shanbhag, University Representative; Mei Zhang, Committee Member; Okenwa Okoli, Committee Member;
William Oates, Committee Member.
Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_291321 |
Contributors | Obitayo, Waris (authoraut), Liu, Tao, 1969- (professor directing dissertation), Shanbhag, Sachin (university representative), Zhang, Mei (committee member), Okoli, Okenwa (committee member), Oates, William S. (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Industrial and Manufacturing Engineering (degree granting department) |
Publisher | Florida State University |
Source Sets | Florida State University |
Language | English, English |
Detected Language | English |
Type | Text, text |
Format | 1 online resource (147 pages), computer, application/pdf |
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