JOURNAL ARTICLE

Tuning the electro-optical properties of germanene nanoribbons by boron atom substitution for application in information transmission.

  • Published In: International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics, 2025, v. 39, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Ngoc, Hoang Van; Ha, Chu Viet 3 of 3

Abstract

Germanene nanoribbons, a one-dimensional material, have great potential for future technological applications. This research aims to investigate the electro-optical properties of boron-doped germanene nanoribbons with a width of five atoms. The theory used in this study is density functional theory (DFT). The original system is a narrow band gap semiconductor, with a gap size of 0.06 eV. The doped configurations, which retain the honeycomb hexagonal structure, are stable and metallic in nature. The introduction of B atoms flattens the configuration, leading to a partial charge shift from Ge to B. The absorption peaks in the 3B and 5B configurations occur in the frequency range less than 500 nm, indicating good absorption of visible light, and suggesting possible applications in light-sensitive components. Notably, the real part of the dielectric function's 0z component is negative, offering immense potential for optical, microwave and communication applications. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics. 2025/01, Vol. 39, Issue 2, p1
  • Document Type:Article
  • Subject Area:Physics
  • Publication Date:2025
  • ISSN:0217-9792
  • DOI:10.1142/S021797922550016X
  • Accession Number:182123022
  • Copyright Statement:Copyright of International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics 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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