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Probabilistic investigation of temperature-dependent vibrational behavior of hetero-nanotubes

Publication Type : Journal Article

Publisher : Springer

Source : Applied Nanoscience, 12, pages 2077–2089, SCI, IF: 3.869, 2022.

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Campus : Coimbatore

School : School of Artificial Intelligence - Coimbatore

Center : Computational Engineering and Networking

Year : 2022

Abstract : The present report outlines a probabilistic investigation of the temperature-dependent resonant frequency of various BNNT and CNT-based hetero-junctions and Van der Waals (VdW) heterostructures. Prior to performing the extensive atomistic simulations, the vibrational response of pristine SWCNT is validated by the values reported in the past literature. The responses determined in the present study are found in agreement (error within ≈ ± 8%) with the published literature. With the sufficient confidence in the results obtained by MD simulations, the further detailed analysis is carried out. In the preliminary analysis, the vibrational behaviour of the considered heterostructures is evaluated by taking into account the degree of heterogeneity, boundary conditions, and the inherent strain percentage in the system. To address the limitations of the heterostructures’ fracture and elastic behaviour, the structures are subjected to uniaxial tensile deformation, with the mechanical behaviour of the structures assessed based on the degree of heterogeneity. It is noticed that, the VdW heterostructures with the outer wall BNNT (10, 10) and inner wall CNT (5, 5) results in a slightly better (3%) resonant frequency than the DWCNT. The VdW heterogeneity has a positive impact on the failure strain of the structures; however, the fracture strength and Young’s modulus reduce drastically under the influence of the VdW heterogeneity. Following the preliminary analysis, the influence of stochastic variations in the temperature on the vibrational behavior of different hetero-nanotubes is assessed. In this regard, the artificial neural network (ANN) model is integrated with the random sampling-based MD simulations to characterize the temperature-dependent resonant frequencies of hetero-junctions and VdW heterostructures. The proposed machine learning-based framework performs the complete characterization of temperature-dependent resonant frequency of the considered heterostructures, which would otherwise remain unexplored due to the exorbitant nature of performing large-scale molecular dynamics simulations.

Cite this Research Publication : Roy, A., Gupta, K.K. and Dey, S., "Probabilistic investigation of temperature-dependent vibrational behaviour of hetero-nanotubes," Applied Nanoscience, 12, pages 2077–2089, SCI, IF: 3.869, 2022.

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