Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes

Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski

Research output: Contribution to journalArticle

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

Keywords

  • Nanomaterials
  • Predictive modeling
  • Thermal conductivity

ASJC Scopus subject areas

  • Materials Science(all)

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