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An integrated computational approach for determining the elastic properties of boron nitride nanotubes

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Abstract

An integrated computational approach is proposed to investigate the compressive strength of boron nitride nanotubes (BNNTs). In this approach, an artificial intelligence (AI) cluster comprising of multi-gene genetic programming and molecular dynamics (MD) simulation technique, was specifically designed to formulate the explicit relationship of compressive strength of BNNTs with respect to system aspect ratio (AR), temperature and vacancy defects. It was found that the novel MD based AI model is able to model the compressive strength of BNNTs very well, which is in good agreement with that of experimental results obtained from the literature. Additionally, we also conducted sensitivity and parametric analysis to find out specific influence and variation of each of the input system parameters on the compressive strength of BNNTs. It was found that the AR has the most dominating influence on the compressive strength of BNNTs.

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Acknowledgments

This work was partially supported by the Singapore Ministry of Education Academic Research Fund through Research Grant RG30/10, which the authors gratefully acknowledge.

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Authors and Affiliations

  1. School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    V. Vijayaraghavan, A. Garg, C. H. Wong & K. Tai

  2. Department of Mechanical Engineering, Birla Institute of Technology and Science, BITS Pilani, K.K. Birla Goa Campus, Zuarinagar, 403726, Goa, India

    Pravin M. Singru

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  1. V. Vijayaraghavan
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  2. A. Garg
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  3. C. H. Wong
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Correspondence to A. Garg.

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The first two authors contributed equally and are both considered as first authors.

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Vijayaraghavan, V., Garg, A., Wong, C.H. et al. An integrated computational approach for determining the elastic properties of boron nitride nanotubes. Int J Mech Mater Des 11, 1–14 (2015). https://doi.org/10.1007/s10999-014-9262-1

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