A new approach to the characterization of nanomaterials: Predicting Young's modulus by correlation weighting of nanomaterials codes

Andrey A. Toropov; Jerzy Leszczynski

doi:10.1016/j.cplett.2006.11.010

A new approach to the characterization of nanomaterials: Predicting Young's modulus by correlation weighting of nanomaterials codes

Andrey A. Toropov, Jerzy Leszczynski

Istituto di Ricerche Farmacologiche "Mario Negri"

Research output: Contribution to journal › Article › peer-review

Abstract

Twenty-nine nanomaterials (atom composition and conditions of syntheses) have been studied. Their characteristics were applied to predictions of Young's modulus values (in GPa). The obtained statistical characteristics of the models are reasonably good, n = 21, r² = 0.9757, s = 18.3 GPa, F = 761 (training set) and n = 8, r² = 0.8952, r_pred ² = 0.8880, s = 34.7 GPa, F = 51 (test set).

Original language	English
Pages (from-to)	125-129
Number of pages	5
Journal	Chemical Physics Letters
Volume	433
Issue number	1-3
DOIs	https://doi.org/10.1016/j.cplett.2006.11.010
Publication status	Published - Dec 29 2006

ASJC Scopus subject areas

Physical and Theoretical Chemistry
Spectroscopy
Atomic and Molecular Physics, and Optics
Surfaces and Interfaces
Condensed Matter Physics

Access to Document

10.1016/j.cplett.2006.11.010

Fingerprint Dive into the research topics of 'A new approach to the characterization of nanomaterials: Predicting Young's modulus by correlation weighting of nanomaterials codes'. Together they form a unique fingerprint.

Cite this

@article{e00b54010e494ff0960ef94f67db1693,

title = "A new approach to the characterization of nanomaterials: Predicting Young's modulus by correlation weighting of nanomaterials codes",

abstract = "Twenty-nine nanomaterials (atom composition and conditions of syntheses) have been studied. Their characteristics were applied to predictions of Young's modulus values (in GPa). The obtained statistical characteristics of the models are reasonably good, n = 21, r2 = 0.9757, s = 18.3 GPa, F = 761 (training set) and n = 8, r2 = 0.8952, rpred 2 = 0.8880, s = 34.7 GPa, F = 51 (test set).",

author = "Toropov, {Andrey A.} and Jerzy Leszczynski",

year = "2006",

month = dec,

day = "29",

doi = "10.1016/j.cplett.2006.11.010",

language = "English",

volume = "433",

pages = "125--129",

journal = "Chemical Physics Letters",

issn = "0009-2614",

publisher = "Elsevier",

number = "1-3",

}

TY - JOUR

T1 - A new approach to the characterization of nanomaterials

T2 - Predicting Young's modulus by correlation weighting of nanomaterials codes

AU - Toropov, Andrey A.

AU - Leszczynski, Jerzy

PY - 2006/12/29

Y1 - 2006/12/29

N2 - Twenty-nine nanomaterials (atom composition and conditions of syntheses) have been studied. Their characteristics were applied to predictions of Young's modulus values (in GPa). The obtained statistical characteristics of the models are reasonably good, n = 21, r2 = 0.9757, s = 18.3 GPa, F = 761 (training set) and n = 8, r2 = 0.8952, rpred 2 = 0.8880, s = 34.7 GPa, F = 51 (test set).

AB - Twenty-nine nanomaterials (atom composition and conditions of syntheses) have been studied. Their characteristics were applied to predictions of Young's modulus values (in GPa). The obtained statistical characteristics of the models are reasonably good, n = 21, r2 = 0.9757, s = 18.3 GPa, F = 761 (training set) and n = 8, r2 = 0.8952, rpred 2 = 0.8880, s = 34.7 GPa, F = 51 (test set).

UR - http://www.scopus.com/inward/record.url?scp=33845296955&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33845296955&partnerID=8YFLogxK

U2 - 10.1016/j.cplett.2006.11.010

DO - 10.1016/j.cplett.2006.11.010

M3 - Article

AN - SCOPUS:33845296955

VL - 433

SP - 125

EP - 129

JO - Chemical Physics Letters

JF - Chemical Physics Letters

SN - 0009-2614

IS - 1-3

ER -

A new approach to the characterization of nanomaterials: Predicting Young's modulus by correlation weighting of nanomaterials codes

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this