Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/14273
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dc.contributor.authorSözmen, Alper Baran-
dc.contributor.authorElveren, Beste-
dc.contributor.authorErdoğan, Duygu-
dc.contributor.authorMezgil, Bahadır-
dc.contributor.authorBaştanlar, Yalın-
dc.contributor.authorYıldız, Ümit Hakan-
dc.contributor.authorArslan Yıldız, Ahu-
dc.date.accessioned2024-01-30T09:24:49Z-
dc.date.available2024-01-30T09:24:49Z-
dc.date.issued2024-
dc.identifier.issn2590-1370-
dc.identifier.urihttps://doi.org/10.1016/j.biosx.2024.100439-
dc.identifier.urihttps://hdl.handle.net/11147/14273-
dc.description.abstractPlasmonic 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)en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofBiosensors and Bioelectronics: Xen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectArtificial neural networken_US
dc.subjectMicroorganism monitoringen_US
dc.subjectPlasmonic biosensoren_US
dc.subjectSPR sensitivity enhancementen_US
dc.subjectBiosensorsen_US
dc.subjectEscherichia colien_US
dc.titleDevelopment of chrono-spectral gold nanoparticle growth based plasmonic biosensor platformen_US
dc.typeArticleen_US
dc.departmentİzmir Institute of Technology. Bioengineeringen_US
dc.departmentİzmir Institute of Technology. Chemistryen_US
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.volume16en_US
dc.identifier.scopus2-s2.0-85182601487en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.biosx.2024.100439-
dc.authorscopusid57201620092-
dc.authorscopusid57201152720-
dc.authorscopusid57193697547-
dc.authorscopusid57195216681-
dc.authorscopusid15833922000-
dc.authorscopusid8516383700-
dc.authorscopusid57217604248-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextembargo_20250101-
item.openairetypeArticle-
crisitem.author.dept01. Izmir Institute of Technology-
crisitem.author.dept03.04. Department of Computer Engineering-
crisitem.author.dept04.01. Department of Chemistry-
crisitem.author.dept03.01. Department of Bioengineering-
Appears in Collections:Bioengineering / Biyomühendislik
Chemistry / Kimya
Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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