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SPR based biosensors register binding of analytes to the surface with immobilized receptors by measuring changes of the refractive index near this surface. An important task in the improvement of this measurement technology is a separation of signals, corresponding to the changes in the chemosensitive layer, from undesired contributions of bulk phase, for example, due to fluctuations of temperature, concentrations of solutes, pressure. The wavelength of the incident light influences strongly the penetration depth of the corresponding evanescent wave. This dependence was exploited here for compensation of the contribution of the bulk refractive index. It was performed using differential SPR measurements at two wavelengths with differing penetration depths. Theoretical analysis and numerical optimization of the suggested approach, named a Penetration Difference Self-Referencing SPR (PDSR-SPR), were performed. Experimental test was performed using 658 and 980 nm laser diodes. Over 20 times suppression of variations of bulk refractive index with magnitude up to 1000 μRIU was observed. Finally, PDSR-SPR approach was applied for monitoring of antibodies binding to the immobilized antigens.
A new approach for self-referencing in SPR biosensors is reported. The method is technologically simple and applicable for a wide range of existing SPR instrumentation with Kretschmann configuration. It is based on the micropatterning of the sensor area with sensing and referencing areas whose shape and distribution can be chosen arbitrarily and their characteristic sizes are larger than the plasmons propagation length. Provided that roughly a half of the area is used as the sensing area while its optical thickness is different from that of the referencing area, an integral measurement of the intensity of the reflected light over such a patterned surface near the summary resonance conditions exhibits self-referencing properties. An over ten-fold suppression of the effect caused by the variation of the bulk refractive index was observed.
It has recently been shown that surface plasmon microscopy (SPM) allows single nanoparticles (NPs) on sensor surfaces to be detected and analyzed. The authors have applied this technique to study the adsorption of single metallic and plastic NPs. Binding of gold NPs (40, 60 and 100 nm in size) and of 100 nm polystyrene NPs to gold surfaces modified by differently ω-functionalized alkyl thiols was studied first. Self-assembled monolayers (SAM) with varying terminal functions including amino, carboxy, oligo(ethylene glycol), methyl, or trimethylammonium groups were deposited on gold films to form surfaces possessing different charge and hydrophobicity. The affinity of NPs to these surfaces depends strongly on the type of coating. SAMs terminated with trimethylammonium groups and carboxy group display highly different affinity and therefore were preferred when creating patterned charged surfaces. Citrate-stabilized gold NPs and sulfate-terminated polystyrene NPs were used as negatively charged NPs, while branched polyethylenimine-coated silver NPs were used as positively charged NPs. It is shown that the charged patterned areas on the gold films are capable of selectively adsorbing oppositely charged NPs that can be detected and analyzed with an ~1 ng⋅mL−1 detection limit.
The increasing production and application of nanoparticles necessitates a highly sensitive analytical method for the quantification and identification of these potentially hazardous materials. We describe here an application of surface plasmon microscopy for the individual detection of each adsorbed nanoparticle and for visualization of its electrochemical conversion. Whereas the adsorption rate characterizes the number concentration of nanoparticles, the potential at which the adsorbed nanoparticles disappear during an anodic potential sweep characterizes the type of material. All the adsorbed nanoparticles are subjected to the potential sweep simultaneously; nevertheless, each of the up to a million adsorbed nanoparticles is identified individually by its electrochemical dissolution potential. The technique has been tested with silver and copper nanoparticles, but can be extended to many other electrochemically active nanomaterials.
Sensitive detection of engineered nanoparticles (NPs) in air and in liquid samples is an important task and still a major challenge in analytical chemistry. Recent work demonstrated that it can be performed using surface plasmon microscopy (SPM) where binding of single NPs to a surface leads to the formation of characteristic patterns in differential SPM images. However, these patterns have to be discriminated from a noisy background. Computer-assisted recognition of nanoparticles offers a solution but requires the development of respective tools for data analysis. Hereby a numerical method for automated detection and characterization of images of single adsorbing NPs in SPM image sequences is presented. The detection accuracy of the method was validated using computer generated images and manual counting. The method was applied for detecting and imaging of gold and silver NPs adsorbing from aqueous dispersions and for soot and NaCl NPs adsorbing from aerosols. The determined adsorption rate was in range 0.1–40 NPs per (s mm2) and linearly dependent on the concentration of nanoparticles. Depending on the type of NPs and signal to noise ratio, a probability of recognition of 90–95 % can be achieved.
An ultrasensitive analytical method for direct detection of single nanoparticles in complex environment is described. The method relies on the wide-field surface plasmon microscopy (SPM). The suppression of matrix effects is achieved by image analysis based on the template matching. First, characteristic SPM images of nanoparticles are collected in aqueous suspensions. Then the detection of nanoparticles in complex environment is performed using template matching.
Quantification and characterization of nanoparticles size was demonstrated at subppb level (∼ 100 pg/mL) in such complex media as wines, fruit juices, or cosmetic formulation. Visualization of the nanoparticles is performed in real time. The method does not require any sample pretreatment. If the minimally acceptable adsorption rate is defined as one nanoparticle to the whole sensor surface per few seconds, the working range of the method is ∼ 10 6 to 10 10
nanoparticles per mL.
An approach for visualization of patterned monomolecular layers in surface plasmon microscopy (SPM) is suggested. The development of hidden image in SPM is achieved by referencing of images obtained in the presence of electrolytes with a high molar refraction of either anions or cations. A formation of diffuse layer near the charged surface areas leads to the redistribution of ions. The ratio of SPM images allows one to visualize this redistribution and to distinguish surface areas with different properties. The approach is unobtrusive and robust; it can be used with most SPR imaging instruments.
Surface plasmon resonance, being widely used in bioanalytics and biotechnology, is influenced by the electrical potential of the resonant gold layer. To evaluate the mechanism of this effect, we have studied it in solutions of various inorganic electrolytes. The magnitude of the effect decreases according to the series: KBr>KCl>KF>NaClO4. The data were treated by using different models of the interface. A quantitative description was obtained for the model, which takes into account the local dielectric function of gold being affected by the free electron charge, diffuse ionic layer near the gold/water interface, and specific adsorption of halides to the gold surface with partial charge transfer. Taking into account that most biological experiments are performed in chloride-containing solutions, detailed analysis of the model at these conditions was performed. The results indicate that the chloride adsorption is the main mechanism for the influence of potential on the surface plasmon resonance. The dependencies of surface concentration and residual charge of chloride on the applied potential were determined.
In-situ detection and characterization of nanoparticles in biological media as well as in food or other complex samples is still a big challenge for existing analytical methods. Here we describe a label-free and cost-effective analytical method for detection of nanoparticles in the concentration range 106 -1010 NPs/ml. The proposed method is based on the surface plasmon resonance microscopy (SPRM) with a large field of view (~1.3mm2 ). It is able to detect and count adsorbing nanoparticles individually, totally up to the hundreds of thousands of NPs on the sensor surface. At constant diffusion conditions the detection rate is proportional to the number concentration of NPs, this provides an approach to determine the NPs concentration. The adsorption of nanoparticle can be manipulated by the surface functionalization, pH and electrolyte concentration of suspensions. Images of detected nanoparticles can be quantified in order to characterize them individually. The image intensity grows quasi-linearly with nanoparticle size for the given material. However, the size and material of nanoparticle cannot be resolved directly from the image. For determination of chemical composition, SPRM can be assisted by electrochemical analysis. In this case, the gold sensor surface is used both as a resonant media for plasmon microscopy and as a working electrode. Under potential sweep, the adsorbed NPs can be subjected to electrochemical dissolution, which is detected optically. The potential of this conversion characterizes the material of NPs.
Detection of nano- and micro-particles is an important task for chemical analytics, food industry, biotechnology, environmental monitoring and many other fields of science and industry. For this purpose, a method based on the detection and analysis of minute signals in surface plasmon resonance images due to adsorption of single nanopartciles was developed. This new technology allows one a real-time detection of interaction of single nano- and micro-particles with sensor surface. Adsorption of each nanoparticle leads to characteristic diffraction image whose intensity depends on the size and chemical composition of the particle. The adsorption rate characterizes volume concentration of nano- and micro-particles. Large monitored surface area of sensor enables a high dynamic range of counting and to a correspondingly high dynamic range in concentration scale. Depending on the type of particles and experimental conditions, the detection limit for aqueous samples can be below 1000 particles per microliter. For application of method in complex media, nanoparticle images are discriminated from image perturbations due to matrix components. First, the characteristic SPRM images of nanoparticles (templates) are collected in aqueous suspensions or spiked real samples. Then, the detection of nanoparticles in complex media using template matching is performed. The detection of various NPs in consumer products like cosmetics, mineral water, juices, and wines was shown at sub-ppb level. The method can be applied for ultrasensitive detection and analysis of nano- and micro-particles of biological (bacteria, viruses, endosomes), biotechnological (liposomes, protein nanoparticles for drug delivery) or technical origin.