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Prediction of Buckling Instability of Perfect and Defective Carbon Nanotubes

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This paper deals with axial, torsional and bending buckling instabilities of CNTs with different geometries and boundary conditions. At first, the results are obtained for some cases using structural mechanics and due to the uneven trends of the results, they are fed into an adaptive neuro-fuzzy inference system to predict the buckling loads of the unmodeled CNTs. Some special cases are used to validate the capability of the predictive tool and the accuracy of the predicted results. Moreover, the effects of various defects including single, double and triple vacancies as well as Stone-Wales defect with different numbers and positions on the buckling loads of the CNTs are analyzed in detail.
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Document Type: Research Article

Publication date: November 1, 2014

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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