4.7 Article

Gold Nanobipyramids as LPSR Sensing Materials for Glyphosate Detection: Surface Density and Aspect Ratio Effect

Journal

IEEE SENSORS JOURNAL
Volume 22, Issue 19, Pages 18479-18485

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2022.3199466

Keywords

Sensors; Surface morphology; Nanoparticles; Gold; Sensitivity; Metals; Ocean temperature; Gold nanobipyramids (GNBPs); gold nanoparticles; localized surface plasmon resonance (LSPR); LSPR sensor

Funding

  1. Institut Teknologi Sumatera through Hibah Penelitian ITERA 2022 [B/763a/IT9.C1/PT.01.03/2022]

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This study investigates the effects of surface density and aspect ratio of gold nanobipyramids (GNBPs) on the performance of localized surface plasmon resonance (LSPR)-based sensors. The experimental results show a linear relationship between the mean surface density and aspect ratio of GNBPs and the sensitivity of the LSPR-based sensor. The highest sensitivity is achieved with a surface density of 80.02% +/- 0.86% and an aspect ratio of 2.58 +/- 0.04. Additionally, this sample exhibits clear response recovery behavior and stable repeatability.
The governing of localized surface plasmon resonance (LSPR)-based sensor performance is derived with consideration of shape, surface density, and aspect ratio of sensing material, as well as the refractive index of the medium. Dependencies of the surface density and aspect ratio of gold nanobipyramids (GNBPs) used as sensing materials in self-customized LSPR-based sensor setup for the detection of herbicides namely glyphosate are studied in this work. In this work, the GNBPs with a surface density from 5.21% +/- 0.44% to 91.46% +/- 3.32% and an aspect ratio from 2.00 +/- 0.02 to 2.76 +/- 0.05 were fabricated. Experimentally, the result shows a linear relationship between the mean surface density and aspect ratio of GNBPs toward the sensitivity of the LSPR-based sensor for both transverse surface plasmon resonance (t-SPR) and longitudinal surface plasmon resonance (l-SPR) resonance peaks. The optimum result for sensitivity was carried out by a sample with a surface density of 80.02% +/- 0.86% and an aspect ratio of 2.58 +/- 0.04. Furthermore, this sample also exhibits very clear response recovery behavior and stable repeatability up to five cycles with variances of 0.011% and 0.022%, respectively. The findings are useful to enhance the performance of LSPR-based sensor through process conditions that are able to control the morphology (surface density and aspect ratio) of GNBPs to improve the sensitivity of LSPR-based sensor.

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