A molecular dynamics based artificial intelligence approach for characterizing thermal transport in nanoscale material

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@Article{Vijayaraghavan:2014:TA,
  author =       "V. Vijayaraghavan and A. Garg and C. H. Wong and 
                 K. Tai and Pravin M. Singru and Liang Gao and 
                 K. S. Sangwan",
  title =        "A molecular dynamics based artificial intelligence
                 approach for characterizing thermal transport in
                 nanoscale material",
  journal =      "Thermochimica Acta",
  volume =       "594",
  pages =        "39--49",
  year =         "2014",
  ISSN =         "0040-6031",
  DOI =          "doi:10.1016/j.tca.2014.08.029",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0040603114003992",
  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.",
  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