Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T17:07:36.683Z Has data issue: false hasContentIssue false

Graph Spectra of Carbon Nanotube Networks: Molecular Communication

Published online by Cambridge University Press:  01 February 2011

Stephen Francis Bush
Affiliation:
bushsf@research.ge.com, GE Global Research, CDS, 1 Research Circle, Niskayuna, NY 12309, Niskayuna, NY, 12309, United States, 518-387-6827, 518-387-4042
Yun Li
Affiliation:
liyun@crd.ge.com, GE Global Research, CDS, One Research Circle, KW-B405, Niskayuna, NY, 12309, United States
Get access

Abstract

The integrated application within random carbon nanotube networks (CNT) to carry and fuse information, as well as perform simple sensing, is explored. One may imagine small CNT networks with functionalized nanotubes simultaneously sensing multiple targets in-vivo for unprecedented understanding of biological pathways. This is clearly distinct from the traditional convoluted approach of using CNT networks to construct transistors that are in turn used to construct communication networks. With random CNT network layouts, routing of information is an integral part of the physical layer.

A Mathematica analysis for evaluating random CNT networks has been developed and used to verify design characteristics. The graph spectrum of the CNT network is used to determine resistance and electron mobility characteristics. Thus, we have been able to find relationships among CNT network structure and electron mobility. The nanotube density allows for an increase in the number of bits per square meter of information transfer compared to wireless communication. Consider a wireless network; a typical bit-meters/second capacity is limited in a traditional wireless network. The maximum wireless capacity approximation in a wireless broadcast media is contrasted with a CNT network; we look at the efficiency of CNT networks to carry information and compare with theoretical limits.

Type
Research Article
Copyright
Copyright © Materials Research Society 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Bush, S. F., and Smith, N., The Limits of Motion Prediction Support for Ad hoc Wireless Network Performance, The 2005 International Conference on Wireless Networks (ICWN-05), Monte Carlo Resort, Las Vegas, Nevada, USA, June 2730, 2005.Google Scholar
2. Bush, S. F., and Goel, S., Graph Spectra of Carbon Nanotube Networks, Nano-Net 2006 1st International Conference on Nano-Networks, Lausanne, Switzerland, September 1416, 2006.Google Scholar
3. Bush, S. F. and Li, Y., “Network Characteristics of Carbon Nanotubes: A Graph Eigenspectrum Approach and Tool Using Mathematica,” GE Global Research, Technical Report 2006GRC023, January 2006.Google Scholar
4. Bush, S. F. and Li, Y., “Characteristics of Carbon Nanotube Networks: The Impact of a Metallic Nanotube on a CNT Network,” GE Global Research, Technical Report 2006GRC397, June 2006.Google Scholar
5. Bush, S. F. and Li, Y., “Nano-Communications: A New Field? An Exploration into a Carbon Nanotube Communication Network,” GE Global Research Technical Report 2006GRC066, February 2006.Google Scholar
6. Gupta, P. and Kumar, P.R., “Capacity of wireless networks,” Technical report, University of Illinois, Urbana-Champaign, 1999.Google Scholar
7. Kramer, G. and Savari, S. A., “Edge-Cut Bounds On Network Coding Rates,” Journal Of Network And Systems Management, Vol. 14, No. 1, March 2006, Special Issue On Management Of Active And Programmable Networks, ed. Stephen Bush and Shivkumar Kalyanaraman.Google Scholar
8. Wolf, E. L., Nanophysics and Nanotechnology. ISBN 3-527-40407-4, Wiley-VCH, 2004.Google Scholar
9. Wolfram, S., The Mathematica Book, Fifth Edition, Wolfram Media, ISBN 1-57955-022-3, 2003.Google Scholar