Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89416
Title: Sensitivity enhancement of MoS2 nanosheet based surface plasmon resonance biosensor
Authors: Ouyang, Qingling
Zeng, Shuwen
Dinh, Xuan-Quyen
Coquet, Philippe
Yong, Ken-Tye
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Surface Plasmon Resonance
Silicon Thin Film
Issue Date: 2016
Source: Ouyang, Q., Zeng, S., Dinh, X.-Q., Coquet, P., & Yong, K.-T. (2016). Sensitivity enhancement of MoS2 nanosheet based surface plasmon resonance biosensor. Procedia Engineering, 140, 134-139. doi:10.1016/j.proeng.2015.08.1114
Series/Report no.: Procedia Engineering
Abstract: A surface plasmon resonance based biosensor consisting of SF10 prism, silicon layer, gold thin film and MoS2 enhanced nanosheet is presented. We systematically investigated the SPR reflectivity and resonance angle through the transfer matrix method. Furthermore, with the optimized thickness of gold, silicon and MoS2, we calculated the change of resonance angle to a fixed refractive index change of sample solutions and the full width at half maximum of the reflectivity curves. The excitaition wavelengths of light sources that we use range from 600 nm to 1024 nm which covers both visible and near infrared light. In addition, the optimum configuration for MoS2-enhanced SPR biosensors are monolayer MoS2 and 7 nm silicon layer coated on 50 nm Au thin film with 633 nm as the excitation wavelength. With these optimized parameters we can efficiently increase the sensitivity by ∼10%. Even without the silicon layers, the pure MoS2 enhanced nanosheet can also improve the sensitivity by ∼8%. The performance of MoS2 enhanced nanosheet is almost 3-fold higher than that of graphene.
URI: https://hdl.handle.net/10356/89416
http://hdl.handle.net/10220/46227
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2015.08.1114
Schools: School of Electrical and Electronic Engineering 
Research Centres: CNRS International NTU THALES Research Alliances 
Rights: © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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