Determination of the Diameter Distribution of Single-Wall Carbon Nanotubes from the Raman G-Band Using an Artificial Neural Network

Authors: Kukovecz A.; Smolik M.; Bokova S.; Kataura H.; Achiba Y.; Kuzmany H.

Source: Journal of Nanoscience and Nanotechnology, Volume 5, Number 2, February 2005 , pp. 204-208(5)

Publisher: American Scientific Publishers

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Abstract:

A novel, artificial neural network-based method is now available for obtaining the mean diameter of single wall carbon nanotube (SWCNT) samples from the diameter dispersive features of their Raman G-band. The method is demonstrated here for six different diameter SWCNT samples and 14 different excitation wavelengths. With an adequately large pool of standard nanotube samples, the suggested method is a useful complementary technique for SWCNT diameter analysis as it is capable of rapid diameter evaluation without prior knowledge of the relevant phonon dispersion relations.

Keywords: CARBON NANOTUBES; RAMAN SPECTROSCOPY; ARTIFICIAL NEURAL NETWORK; DIAMETER ANALYSIS

Document Type: Research article

DOI: http://dx.doi.org/10.1166/jnn.2005.025

Publication date: 2005-02-01

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Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
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