JOURNAL ARTICLE
Electronic and half-metallic behavior of copper-doped silicon carbide armchair single-walled nanotubes using density functional theory.
Published In: International Journal of Computational Materials Science & Engineering, 2026, v. 15, n. 1. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Das, Dipan Kumar; Patnaik, Padmaja; Nayak, Santanu Kumar; Barala, Mandakini 3 of 3
Abstract
Due to their remarkable mechanical, thermal and electrical characteristics, silicon carbide (SiC) single-walled nanotubes (SWNTs) are an unusual and promising class of materials. Density functional theory (DFT) is used in this study to examine the electrical and structural characteristics of copper-doped SiC armchair SWNTs. It has been discovered that copper doping of SiC armchair SWNTs alters the materials' electrical characteristics. SiC SWNTs band gap plays a significant role in influencing the electrical conductivity and optical characteristics of the substance. The energy bands i.e., valence band and conduction band of SiC armchair SWNTs overlapped as copper doping concentration increased, altering the materials' electrical conductivity and optical characteristics. Additionally, a continuous density of states plot and a narrower band gap are frequently employed as markers of ferroelectric behaviour which indicates the existence of a polarizable and highly delocalized electronic system. The significance of copper doping in SiC SWNTs is understood by this study, along with the effects of the doping on the material's electrical properties. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Computational Materials Science & Engineering. 2026/03, Vol. 15, Issue 1, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2026
- ISSN:20476841
- DOI:10.1142/S2047684124500118
- Accession Number:189015129
- Copyright Statement:Copyright of International Journal of Computational Materials Science & Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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