Determination of the diameter distribution of single-wall carbon nanotubes from the raman G-band using an artificial neural network

A. Kukovecz, M. Smolik, S. Bokova, H. Kataura, Y. Achiba, H. Kuzmany

Research output: Contribution to journalArticle

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)204-208
Number of pages5
JournalJournal of Nanoscience and Nanotechnology
Issue number2
Publication statusPublished - Dec 1 2005



  • Artificial Neural Network
  • Carbon Nanotubes
  • Diameter Analysis
  • Raman Spectroscopy

ASJC Scopus subject areas

  • Bioengineering
  • Chemistry(all)
  • Biomedical Engineering
  • Materials Science(all)
  • Condensed Matter Physics

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