Correlating Microstructure and Optoelectronic Performance of Carbon-Based Nanomaterials

Abstract

There is a great deal of interest in carbon nanostructures such as graphene and various forms of carbon nanotubes due to their exceptional physical, electronic, and optical properties. Many technological applications have been proposed for these nanostructures, but despite the promise many carbon nanostructure-based optoelectronic devices fail to compete with their conventional counterparts. This is often due in large part to a non-optimized material or device microstructure. Factors such as crystallinity, contact quality, defect structure, and device configuration can critically affect device performance due to the high sensitivity and extreme surface to volume ratio of carbon nanostructures. In order for the exceptional intrinsic properties of the nanostructures to be exploited, a clear understanding of the microstructure and its correlation with device-relevant optoelectronic properties is needed. This dissertation presents four projects which demonstrate this principle. First, a TiO2-coated carbon nanofiber is studied in order to optimize its structure for use in a novel dye-sensitized solar cell. Second, the electrode configuration of an individual multiwall carbon nanotube infrared sensor is investigated in order to surpass the limitations of disordered nanotube film-based infrared sensors. Third, the properties of defect structures in large area transferred graphene films grown by chemical vapor deposition are correlated with carrier diffusion in order to understand the film's low mobility compared to exfoliated graphene. Fourth, the effect of deposition conditions on graphene-metal contact was studied with the goal of achieving sufficiently transparent contacts for investigation of the superconducting proximity effect. All four projects highlight the unique properties of carbon nanostructures as well as the need to correlate their optoelectronic properties with microstructural details in order to achieve the desired device performance.