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Fiber-optic sensor for neurotransmitter with ultralow concentration: Near-infrared plasmonic electromagnetic field enhancement using raspberry-like meso-SiO2 nanospheres

Abstract

The feasibility of Localized surface Plasmon resonance (LSPR) enhanced sensor based on raspberry-like nanospheres functionalized silica microfiber has been proposed and experimentally demonstrated. The extinction of single Ag (or Au) nanoparticles usually occur in visible wavelengths. Nevertheless, a LSPR enhancement at near infrared wavelengths has been achieved by constructing raspberry-like meso-SiO2 nanosphere with noble metal nanoparticle cluster coating. The nanospheres coating captures γ-amino-butyric acid (GABA) targets through size-selectivity and enhances sensitivity by LSPR effect. The gathering of GABA on sensor surface translates the concentration signal to the information of refractive index (RI). Silica microfiber perceives the RI change to optical signal. The LSPR effect enhances the optical sensitivity by enhancing evanescent field on microfiber surface. This combination presents lowest limit of detection (LOD) of 10-15 M (magnitude of three orders than that without LSPR enhancement). It could fully afford the detection of ultra-low GABA concentration fluctuation (It is important for determining a variety of neurological and psychiatric disorders.). The inherent advantages of the proposed sensors, including their ultra-sensitivity, low cost, light weight, small size and remote operation ability, provide the potential to fully incorporate into various biomedical applications.

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Publication details

The article was received on 12 Jul 2017, accepted on 03 Sep 2017 and first published on 04 Sep 2017


Article type: Paper
DOI: 10.1039/C7NR05032A
Citation: Nanoscale, 2017, Accepted Manuscript
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    Fiber-optic sensor for neurotransmitter with ultralow concentration: Near-infrared plasmonic electromagnetic field enhancement using raspberry-like meso-SiO2 nanospheres

    Y. Huang, M. Ding, T. Guo, D. Hu, Y. Cao, L. Jin and B. Guan, Nanoscale, 2017, Accepted Manuscript , DOI: 10.1039/C7NR05032A

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