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Cited by 176

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Silicon Nanowires for Biosensing, Energy Storage, and Conversion

Wang, Yanli, Wang, Tianyu, Da, Peimei, Xu, Ming, Wu, Hao, Zheng, Gengfeng·2013·Advanced Materials

Abstract

Semiconducting silicon nanowires (SiNWs) represent one of the most interesting research directions in nanoscience and nanotechnology, with capabilities of realizing structural and functional complexity through rational design and synthesis. The exquisite control of chemical composition, structure, morphology, doping, and assembly of SiNWs, in both individual and array format, as well as incorporation with other materials, offers a nanoscale building block with unique electronic, optoelectronic, and catalytic properties, thus allowing for a variety of exciting opportunities in the fields of life sciences and renewable energy. This review provides a brief summary of SiNW research in the past decade, from the SiNW synthesis by both the top‐down approaches and the bottom‐up approaches, to several important biological and energy applications including biomolecule sensing, interfacing with cells and tissues, lithium‐ion batteries, solar cells, and photoelectrochemical conversion.

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Crossref · 10.1002/adma.201301943

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Metadata

Authors
Wang, Y., Wang, T., Da, P., Xu, M., Wu, H., & Zheng, G.
Venue
Advanced Materials
Publisher
Wiley
Published
2013-07-05
Volume
25
Issue
37
Pages
5177-5195
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W1976104630
Cited by
176
References
8
FWCI
12.40
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Silicon Nanowires for Biosensing, Energy Storage, and Conversion. https://app.cochat.ai/papers/10.1002/adma.201301943
The paper
Wang, Y., Wang, T., Da, P., Xu, M., Wu, H., & Zheng, G. (2013). Silicon Nanowires for Biosensing, Energy Storage, and Conversion. Advanced Materials. https://doi.org/10.1002/adma.201301943

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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