Silver nanocluster films for glucose sensing by Surface Enhanced Raman Scattering (SERS)

Botta, Raju; Rajanikanth, A.; Bansal, C.

doi:10.1016/j.sbsr.2016.05.001

Cited by 38 publications

(23 citation statements)

References 24 publications

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“…The intrinsic Raman transitions of adenine were observed at 750 and 1356 cm −1 even at 1 nM (Figure 6c). SERS signals of glucose were obtained even at 0.1 mg/mL (Figure 6d), which is quite below the level in the blood of diabetic patients (2 mg/mL 48,49 ). For amyloid β, electrostatic interaction between the amyloid β (negative charge owing to pI of 5.31 50 ) and the GNRs (positive charge due to the CTAB) in neutral conditions allows for detecting noticeable Raman peaks at 1024, 1150, 1256, and 1410 cm −1 by 1 nM (Figure 6e).…”

Section: ■ Results and Discussionmentioning

confidence: 83%

Facile Amplification of Solution-State Surface-Enhanced Raman Scattering of Small Molecules Using Spontaneously Formed 3D Nanoplasmonic Wells

2018

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Surface-enhanced Raman scattering (SERS) has recently been considered as one of the most promising tools to directly analyze small molecules without labels, owing to advantages in sensitivity, specificity, and speed. However, collecting reproducible SERS signals from small molecules on substrates or in solutions is challenging because of random molecular adsorption on surfaces and laser-induced molecular convection in solutions. Herein, we report a novel and efficient way to collect SERS signals from solution samples using three-dimensional nanoplasmonic wells spontaneously formed by interfacial reactions between liquid polydimethylsiloxane (PDMS) and small droplets of metal ion solutions (e.g., HAuCl and AgNO). A SERS signal is easily maximized at the center near the bottom of the well due to spherical feature of the fabricated wells and electromagnetic field enhancement by the metallic nanoparticles (e.g., Au and Ag) integrated on their surfaces. Through the systematic control over the volume, concentration, and composition of the metal ion solution, optical functions of the nanoplasmonic wells were optimized for SERS, which was further amplified by exploiting the plasmonic couplings with colloidal nanoparticles. By using the optimized nanoplasmonic wells and the detection protocol, we successfully obtained intrinsic spectra of biomolecules (e.g., adenine, glucose, amyloid β) and toxic environmental molecules (e.g., 1,1'-diethyl-2,2'-cyanine iodide and chloromethyliothiazolinone/methylisothiazolinone) as well as Raman active molecules, such as rhodamine 6G and 1,2-bis(4-pyridyl)ethylene at a low concentrations down to the picomolar level. Our detection platform provides a powerful way to develop highly sensitive sensors and high-throughput analyzing protocols for fieldwork applications as well as diagnosing diseases.

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Section: ■ Results and Discussionmentioning

confidence: 83%

Facile Amplification of Solution-State Surface-Enhanced Raman Scattering of Small Molecules Using Spontaneously Formed 3D Nanoplasmonic Wells

2018

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“…As shown in Figure , the SERS‐based glucose detection performance developed in this study is compared with other solid platforms published recently. [ 22,25,49,50 ] It is emphasized that our platform shows better detection limit than previous solid platforms. Although some platforms show better linear ranges, those previous studies are restricted to complicated procedures and the high cost of platform fabrication without multiplex sensing capability.…”

Section: Resultsmentioning

confidence: 99%

Dual‐Modal Fluorescence‐SERS Detection of Blood Glucose Engineered by Hierarchical Laser‐Induced Micro/Nano Structures for Diabetes Screening

Guan

Hong

2022

Adv Materials Inter

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“…SERS spectra were acquired using an IR laser (λ ex = 785 nm) and addressing the sensor through an optical window ( Figure 1). This method enabled glucose detection in the range of 1-500 × 10 −6 m. [63] An important limitation of standard Raman dyes is that they provide multiple peaks in the fingerprint region (<1800 cm −1 ), and are thus likely to overlap with the complex peaks derived from endogenous biological species. [62] Although the use of self-assembled monolayers has been shown promising for glucose detection, most strategies described to date made use of boronic acids, probably due to their greater simplicity.…”

Section: Detection Of Saccharidesmentioning

confidence: 99%

Plasmonic Detection of Carbohydrate‐Mediated Biological Events

Garcı́a

Mosquera

Plou

et al. 2018

Advanced Optical Materials

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regulation of a variety of physiological and pathological processes, such as proliferation and adhesion, immune response, and cell differentiation. [8] The biological roles of carbohydrates as signaling effectors and recognition markers are associated to specific molecular recognition events in which proteins [9] or other carbohydrates [10] are involved. However, individual carbohydrate-based molecular interactions have been shown to be generally weak and, therefore, biomolecules usually present clusters of carbohydrates that interact cooperatively with their natural ligands (multivalent effect), thereby increasing the binding strength. [11] Interestingly, the multivalent carbohydrate presentation can be mimicked by man-made multivalent systems, which involve multiple synthetic oligosaccharides, [12][13][14][15][16][17] and have been used to address basic studies, but also as probe molecules and drugs. Mammalian cells are covered by a dense array of carbohydrates known as glycocalyx. The glycocalyx composition depends on the specific cellular state, and therefore it can provide information about diseases. For example, an increase of α-2,6-sialylation, fucosylation, and/or other tumor-associated carbohydrate antigens on the cellular membrane is considered as a biomarker of cancer progression, with diagnostic value. [18,19] In addition, oligosaccharides can be used as disease biomarkers for targeted therapy, and therefore the analysis and characterization of the composition of cellular glycans provide information of relevance to the diagnosis of several diseases. [20] Different strategies can be used to label glycans, including the use of covalent recognizing ligands (e.g., boronic acid), using specific carbohydrate-binding proteins, and via metabolic labeling.Plasmonics is based on the excitation of surface plasmons, that is, coherent oscillations of electrons induced by an electromagnetic radiation at metal-dielectric interfaces. [21] When the dimensions of plasmonic nanostructures are smaller than the wavelength of the incident light, the interaction between the electromagnetic field and surface charges results in nonpropagating oscillations denoted as localized surface plasmon resonances (LSPR). [22] LSPR frequencies in metal nanoparticles depend on their size, shape, organization, interparticle distance, and dielectric environment, ranging from the visible through the near-infrared (NIR). [23,24] A large volume of research has been devoted to the development of reliable methods for the preparation of plasmonic nanostructures with well-defined shape, size, and/or interparticle spacing, as basic components of various analytical applications. [25,26] Another important element, the surface chemistry of plasmonic The incorporation of nanomaterials in glycoscience research enables the design of highly selective and sensitive bioanalytical devices for the detection of disease-associated biomarkers. In particular, localized surface plasmon resonance (LSPR) and surface enhanced Raman scattering (SERS) spectroscopies ar...

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Silver nanocluster films for glucose sensing by Surface Enhanced Raman Scattering (SERS)

Cited by 38 publications

References 24 publications

Facile Amplification of Solution-State Surface-Enhanced Raman Scattering of Small Molecules Using Spontaneously Formed 3D Nanoplasmonic Wells

Facile Amplification of Solution-State Surface-Enhanced Raman Scattering of Small Molecules Using Spontaneously Formed 3D Nanoplasmonic Wells

Dual‐Modal Fluorescence‐SERS Detection of Blood Glucose Engineered by Hierarchical Laser‐Induced Micro/Nano Structures for Diabetes Screening

Plasmonic Detection of Carbohydrate‐Mediated Biological Events

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