Identification of vacancy defects in carbon nanotubes using vibration analysis and machine learning

Identification of vacancy defects in carbon nanotubes using vibration analysis and machine learning

Point vacancies are the most common defects in a carbon nanotube (CNT) lattice. However, there is no standard technique to identify these defects. Moreover, the effect of such vacancies on the vibrational properties of CNTs is unknown. Therefore, this paper presents the first-ever technique for iden...

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Bibliographic Details
Main Authors: Sneha Singh, Zaid Bin Junaid, Vinay Vyas, Teekam Singh Kalyanwat, Subhram Subhrajyoti Rana
Format: Article
Language:English
Published: Elsevier 2021-10-01
Series:Carbon Trends
Subjects:
Carbon nanotubes
Point vacancies
Support vector machine
Regression
Vibration frequency
Defect identification
Online Access:http://www.sciencedirect.com/science/article/pii/S2667056921000687

Internet

http://www.sciencedirect.com/science/article/pii/S2667056921000687

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