Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/14273
Title: Development of chrono-spectral gold nanoparticle growth based plasmonic biosensor platform
Authors: Sözmen, Alper Baran
Elveren, Beste
Erdoğan, Duygu
Mezgil, Bahadır
Baştanlar, Yalın
Yıldız, Ümit Hakan
Arslan Yıldız, Ahu
Keywords: Artificial neural network
Microorganism monitoring
Plasmonic biosensor
SPR sensitivity enhancement
Biosensors
Escherichia coli
Issue Date: 2024
Publisher: Elsevier
Abstract: Plasmonic sensor platforms are designed for rapid, label-free, and real-time detection and they excel as the next generation biosensors. However, current methods such as Surface Plasmon Resonance require expertise and well-equipped laboratory facilities. Simpler methods such as Localized Surface Plasmon Resonance (LSPR) overcome those limitations, though they lack sensitivity. Hence, sensitivity enhancement plays a crucial role in the future of plasmonic sensor platforms. Herein, a refractive index (RI) sensitivity enhancement methodology is reported utilizing growth of gold nanoparticles (GNPs) on solid support and it is backed up with artificial neural network (ANN) analysis. Sensor platform fabrication was initiated with GNP immobilization onto solid support; immobilized GNPs were then used as seeds for chrono-spectral growth, which was carried out using NH2OH at varied incubation times. The response to RI change of the platform was investigated with varied concentrations of sucrose and ethanol. The detection of bacteria E.coli BL21 was carried out for validation as a model microorganism and results showed that detection was possible at 102 CFU/ml. The data acquired by spectrophotometric measurements were analyzed by ANN and bacteria classification with percentage error rates near 0% was achieved. The proposed LSPR-based, label-free sensor application proved that the developed methodology promises utile sensitivity enhancement potential for similar sensor platforms. © 2024 The Author(s)
URI: https://doi.org/10.1016/j.biosx.2024.100439
https://hdl.handle.net/11147/14273
ISSN: 2590-1370
Appears in Collections:Bioengineering / Biyomühendislik
Chemistry / Kimya
Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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