A molecular dynamics based artificial intelligence approach for characterizing thermal transport in nanoscale material
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{Vijayaraghavan:2014:TA,
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author = "V. Vijayaraghavan and A. Garg and C. H. Wong and
K. Tai and Pravin M. Singru and Liang Gao and
K. S. Sangwan",
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title = "A molecular dynamics based artificial intelligence
approach for characterizing thermal transport in
nanoscale material",
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journal = "Thermochimica Acta",
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volume = "594",
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pages = "39--49",
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year = "2014",
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ISSN = "0040-6031",
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DOI = "doi:10.1016/j.tca.2014.08.029",
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URL = "http://www.sciencedirect.com/science/article/pii/S0040603114003992",
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abstract = "A molecular dynamics (MD)-based-artificial
intelligence (AI) simulation approach is proposed to
investigate thermal transport of carbon nanotubes
(CNTs). In this approach, the effect of size, chirality
and vacancy defects on the thermal conductivity of CNTs
is first analysed using MD simulation. The data
obtained using the MD simulation is then fed into the
paradigm of an AI cluster comprising multi-gene genetic
programming, which was specifically designed to
formulate the explicit relationship of thermal
transport of CNT with respect to system size, chirality
and vacancy defect concentration. Performance of the
proposed model is evaluated against the actual results.
We find that our proposed MD-based-AI model is able to
model the phenomenon of thermal conductivity of CNTs
very well, which can be then used to complement the
analytical solution developed by MD simulation. Based
on sensitivity and parametric analysis, it was found
that length has most dominating influence on thermal
conductivity of CNTs.",
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keywords = "genetic algorithms, genetic programming, Thermal
conductivity, Transport properties, Nanostructures, Ab
initio calculations, Defects",
- }
Genetic Programming entries for
Venkatesh Vijayaraghavan
Akhil Garg
Chee How Wong
Kang Tai
Pravin M Singru
Liang Gao
Kuldip Singh Sangwan
Citations