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Modeling of Quasi-One-Dimensional Carbon Nanostructures with Density Functional Theory

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Handbook of Computational Chemistry

Abstract

The purpose of this chapter is to describe and review examples of how theoretical investigations can be applied to elucidate the behavior of carbon nanostructures and to understand the physical mechanisms taking place at the molecular level. We will place a special emphasis in theoretical works utilizing density functional theory. We assume that the reader is familiar with the basics of density functional theory as well as the electronic properties of single-walled carbon nanotubes and graphene nanoribbons (GNRs). We do not intend to present an extensive review; instead, we focus on several examples to illustrate the powerful predictive capabilities of current computational approaches.

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Acknowledgments

VB acknowledges the donors of The American Chemical Society Petroleum Research Fund for support through the award ACS PRF#49427-UNI6. OH acknowledges the support of the Israel Science Foundation (Grant 1313/08), the Center for Nanoscience and Nanotechnology at Tel-Aviv University, the Lise Meitner-Minerva Center for Computational Quantum Chemistry, and the European Community’s Seventh Framework Programme FP7/2007-2013 under grant agreement no. 249225. JEP acknowledges support from NSF DMR Award #DMR-0906617.

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Authors and Affiliations

  1. Department of Physics, Central Michigan University, 48859, Mount Pleasant, Michigan, USA

    Veronica Barone

  2. Department of Chemical Physics, School of Chemistry, The Sackler Faculty of Exact Sciences, Tel Aviv University, 69978, Tel Aviv, Israel

    Oded Hod

  3. Department of Physics, Central Michigan University, 48859, Mount Pleasant, Michigan, USA

    Juan E. Peralta

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  1. Veronica Barone
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  2. Oded Hod
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  1. Department of Chemistry and Biochemistry, Jackson State University, Jackson, MS, 39217, USA

    Jerzy Leszczynski

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Barone, V., Hod, O., Peralta, J.E. (2012). Modeling of Quasi-One-Dimensional Carbon Nanostructures with Density Functional Theory. In: Leszczynski, J. (eds) Handbook of Computational Chemistry. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0711-5_24

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