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Cited by 173

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

2D Nanomaterial-Based Surface Plasmon Resonance Sensors for Biosensing Applications

Open access
Singh, Sachin, Singh, Pravin Kumar, Umar, Ahmad, Lohia, Pooja, Albargi, Hasan, Castañeda, L., Dwivedi, D. K.·2020·Micromachines

Abstract

The absorption and binding energy of material plays an important role with a large surface area and conductivity for the development of any sensing device. The newly grown 2D nanomaterials like black phosphorus transition metal dichalcogenides (TMDCs) or graphene have excellent properties for sensing devices’ fabrication. This paper summarizes the progress in the area of the 2D nanomaterial-based surface plasmon resonance (SPR) sensor during last decade. The paper also focuses on the structure of Kretschmann configuration, the sensing principle of SPR, its characteristic parameters, application in various fields, and some important recent works related to SPR sensors have also been discussed, based on the present and future scope of this field. The present paper provides a platform for researchers to work in the field of 2D nanomaterial-based SPR sensors.

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Crossref · 10.3390/mi11080779

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Metadata

Authors
Singh, S., Singh, P. K., Umar, A., Lohia, P., Albargi, H., Castañeda, L., & Dwivedi, D. K.
Venue
Micromachines
Publisher
MDPI AG
Published
2020-08-15
Volume
11
Issue
8
Pages
779
ISSN
2072-666X (ISSN-L)
OpenAlex
W3049101263
Cited by
173
References
6
FWCI
5.16
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: 2D Nanomaterial-Based Surface Plasmon Resonance Sensors for Biosensing Applications. https://app.cochat.ai/papers/10.3390/mi11080779
The paper
Singh, S., Singh, P. K., Umar, A., Lohia, P., Albargi, H., Castañeda, L., & Dwivedi, D. K. (2020). 2D Nanomaterial-Based Surface Plasmon Resonance Sensors for Biosensing Applications. Micromachines. https://doi.org/10.3390/mi11080779

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