28
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Anisotropy of the conductivity of silicon nanowires

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Received 05 Jan 2024, Accepted 16 Apr 2024, Published online: 03 May 2024
 

ABSTRACT

This study reports the findings from an investigation into charge carrier transport within a silicon nanowire layer. The samples were prepared using the metal-assisted chemical etching method applied to crystalline silicon wafers with a resistance of 10–20 Ω·cm. The resulting silicon nanowires had a diameter of about 100 nm with a resistance of approximately 15 kΩ·cm. Electrical conductivity measurements were performed in both planar and sandwich configurations, revealing analogous conductivity mechanisms across different geometries. Frequency-dependent conductivity studies unveiled the presence of hopping conductivity. A hypothesis is proposed regarding the existence of a potential barrier at the interface between the nanowire layer and the substrate.

Acknowledgments

The authors gratefully acknowledge the Educational and Methodological Center of Lithography and Microscopy and Research Facilities Sharing Center of Lomonosov Moscow State University for providing the equipment.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The study was supported by the Russian Science Foundation, grant no. [22-72-10062].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 286.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.