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Cited by 617

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Nanostructured Photodetectors: From Ultraviolet to Terahertz

Chen, Hongyu, Liu, Hui, Zhang, Zhiming, Hu, Kai, Fang, Xiaosheng·2016·Advanced Materials

Abstract

Inspired by nanoscience and nanoengineering, numerous nanostructured materials developed by multidisciplinary approaches exhibit excellent photoelectronic properties ranging from ultraviolet to terahertz frequencies. As a new class of building block, nanoscale elements in terms of quantum dots, nanowires, and nanolayers can be used for fabricating photodetectors with high performance. Moreover, in conjunction with traditional photodetectors, they exhibit appealing performance for practical applications including high density of integration, high sensitivity, fast response, and multifunction. Therefore, with the perspective of photodetectors constructed by diverse low‐dimensional nanostructured materials, recent advances in nanoscale photodetectors are discussed here; meanwhile, challenges and promising future directions in this research field are proposed.

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Crossref · 10.1002/adma.201503534

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Metadata

Authors
Chen, H., Liu, H., Zhang, Z., Hu, K., & Fang, X.
Venue
Advanced Materials
Publisher
Wiley
Published
2015-11-25
Volume
28
Issue
3
Pages
403-433
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2266900307
Cited by
617
References
7
FWCI
24.69
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nanostructured Photodetectors: From Ultraviolet to Terahertz. https://app.cochat.ai/papers/10.1002/adma.201503534
The paper
Chen, H., Liu, H., Zhang, Z., Hu, K., & Fang, X. (2016). Nanostructured Photodetectors: From Ultraviolet to Terahertz. Advanced Materials. https://doi.org/10.1002/adma.201503534

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.