This award supports computational research and education on carbon nanotubes. Carbon nanotubes are of significant technological and scientific interest because of their unique structural, mechanical, and electronic properties. The assembly of various chemical species on the surface of nanotubes opens the way for the use of nanotubes as building blocks for nanoscale electronic devices and as reinforcing agents in polymer and epoxy composite materials. The attachment of atoms, chemical groups, and organic compounds can be accomplished by means of noncovalent sidewall functionalization or, alternatively, by covalent end-group, defect, and sidewall functionalization of carbon nanotubes. The presence of chemical contaminants that modify the surface properties of nanotubes can be detected experimentally by monitoring changes in the ultraviolet, visible, infrared, and Raman spectra. Research will focus on developing and applying computational methods for accurate prediction of structural, electronic, and optical properties of defects, termini, functionalized carbon nanotubes, and self-assembled nanotube complexes. The PI aims to extend our understanding of the mechanism of nanotube functionalization and the relation of the strength and density of chemical links in self-assembled nanotube complexes to the change observed in their vibrational and optical spectra. The developed computational algorithm will be applied to a variety of functional groups attached to single-walled nanotubes of different diameter and chirality with the purpose of identifying the most stable combinations suitable for use in nanoscale optoelectronic devices and for building nano-composite materials with superior mechanical properties. To achieve this goal, the PI will combine state-of-the-art density-functional and time-dependent density-functional theoretical methods with massively parallel computational algorithms implemented on Beowulf computer clusters. In order to take full advantage of Beowulf hardware architecture, the project will develop a parallel version of the time-dependent density-functional electronic structure code specifically optimized for parallel Beowulf computers. The research supported by this award may have broader impacts on various areas of modern technology that utilize nanostructured materials and employ complex computational algorithms, particularly on nanotechnology, microelectronics, and information technology. This award also supports outreach and education activities. Graduate and undergraduate students will be involved in interdisciplinary training and research in the fields of theoretical modeling, characterization of nanostructures, and materials design. Topics related to parallel programming, high-level computer simulations, and modern nanostructured materials will be incorporated in the graduate and undergraduate-level curriculum. The outreach and education activities will be specifically directed at increasing the participation of minorities and underrepresented groups in academic research.
NON-TECHNICAL SUMMARY: This award supports computational research and education on carbon nanotubes. Carbon nanotubes are of significant technological and scientific interest because of their unique structural, mechanical, and electronic properties. The assembly of various chemical species on the surface of nanotubes opens the way for the use of nanotubes as building blocks for nanoscale electronic devices and as reinforcing agents in polymer and epoxy composite materials. The PI will perform computational calculations of the properties of Carbon nanotubes using algorithms based on modern electronic structure theory. Part of this work will involve extensions of that theory and developing new computational algorithms to enable calculations of properties outside the scope of the original theory. The research supported by this award may have broader impacts on various areas of modern technology that utilize nanostructured materials and employ complex computational algorithms, particularly on nanotechnology, microelectronics, and information technology. This award also supports outreach and education activities. Graduate and undergraduate students will be involved in interdisciplinary training and research in the fields of theoretical modeling, characterization of nanostructured materials, and materials design. Topics related to parallel programming, high-level computer simulations, and modern nanostructured materials will be incorporated in the graduate and undergraduate-level curriculum. The outreach and education activities will be specifically directed at increasing the participation of minorities and underrepresented groups in academic research.
