Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes

Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

A number of characteristics that include atom compositions, conditions of synthesis and the features of nanomaterials related to their commercial manufacturing have been examined as possible descriptors of a given nanostructure. Using an optimization procedure linked to the Monte Carlo method the special correlation weights have been calculated for each descriptor. A new application of the correlation weights predictive model for the thermal conductivity of nanomaterials has been developed. Statistical characteristics of the model are as follows: n = 43, r2 = 0.8687, s = 5.14 W/m/K, F = 271 (training set); n = 15, r2 = 0.8598, s = 4.91 W/m/K, F = 80 (test set).

Original languageEnglish
Pages (from-to)4777-4780
Number of pages4
JournalMaterials Letters
Volume61
Issue number26
DOIs
Publication statusPublished - Oct 2007

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Nanostructured materials
Thermal conductivity
thermal conductivity
Monte Carlo method
Nanostructures
Monte Carlo methods
education
manufacturing
Atoms
optimization
synthesis
Chemical analysis
atoms

Keywords

  • Nanomaterials
  • Predictive modeling
  • Thermal conductivity

ASJC Scopus subject areas

  • Materials Science(all)

Cite this

Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes. / Toropov, Andrey A.; Leszczynska, Danuta; Leszczynski, Jerzy.

In: Materials Letters, Vol. 61, No. 26, 10.2007, p. 4777-4780.

Research output: Contribution to journalArticle

Toropov, Andrey A. ; Leszczynska, Danuta ; Leszczynski, Jerzy. / Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes. In: Materials Letters. 2007 ; Vol. 61, No. 26. pp. 4777-4780.
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