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Developing Descriptors To Predict Mechanical Properties of Nanotubes
- Source :
- Journal of Chemical Information and Modeling. 53:773-782
- Publication Year :
- 2013
- Publisher :
- American Chemical Society (ACS), 2013.
-
Abstract
- Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.
- Subjects :
- Materials science
General Chemical Engineering
Modulus
Thermodynamics
General Chemistry
Carbon nanotube
Library and Information Sciences
Poisson's ratio
Computer Science Applications
law.invention
Condensed Matter::Materials Science
symbols.namesake
Molecular dynamics
Zigzag
Computational chemistry
law
Vacancy defect
symbols
Raman spectroscopy
Elastic modulus
Subjects
Details
- ISSN :
- 1549960X and 15499596
- Volume :
- 53
- Database :
- OpenAIRE
- Journal :
- Journal of Chemical Information and Modeling
- Accession number :
- edsair.doi.dedup.....bde124389969903c6e91002783eaeda5