Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes

被引：19

作者：

Toropov, Andrey A. ^{[1
]}

Leszczynska, Danuta ^{[1
]}

Leszczynski, Jerzy ^{[1
]}

机构：

[1] Jackson State Univ, Computat Ctr Mol Struct & Interact, Jackson, MS 39217 USA

来源：

MATERIALS LETTERS | 2007年 / 61卷 / 26期

关键词：

nanomaterials; thermal conductivity; predictive modeling;

D O I：

10.1016/j.matlet.2007.03.026

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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, r(2)=0.8687, s=5.14 W/m/K, F=271 (training set); n=15, r(2)=0.8598, s=4.91 W/m/K, F=80 (test set). (C) 2007 Elsevier B.V. All rights reserved.

引用

页码：4777 / 4780

页数：4

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