Computer assisted detection and quantification of single adsorbing nanoparticles by differential surface plasmon microscopy

Deep-Learning Driven, High-Precision Plasmonic Scattering Interferometry for Single-Particle Identification

Label-free probing of the material composition of (bio)nano-objects directly in solution at the single-particle level is crucial in various fields, including colloid analysis and medical diagnostics. However, it remains challenging to decipher the constituents of heterogeneous mixtures of nano-objects with high sensitivity and resolution. Here, we present deep-learning plasmonic scattering interferometric microscopy, which is capable of identifying the composition of nanoparticles automatically with high throughput at the single-particle level. By employing deep learning to decode the quantitative relationship between the interferometric scattering patterns of nanoparticles and their intrinsic material properties, this technique is capable of high-throughput, label-free identification of diverse nanoparticle types. We demonstrate its versatility in analyzing dynamic surface chemical reactions on single nanoparticles, revealing its potential as a universal platform for nanoparticle imaging and reaction analysis. This technique not only streamlines the process of nanoparticle characterization, but also proposes a methodology for a deeper understanding of nanoscale dynamics, holding great potential for addressing extensive fundamental questions in nanoscience and nanotechnology.

Surface plasmon coupling between wide-field SPR microscopy and gold nanoparticles

The coupling behavior of the wide field surface plasmon microscopy (WF-SPRM) with single-, two-, and multiple-gold nanoparticles (AuNPs) with different AuNPs sizes is investigated using theoretical, simulation, and experimental approaches. The signal intensity of a single AuNP increases from 208 a.u. to 583 a.u. as particle size increases from 40 to 80 nm, which evidences the signal-building mechanism of Rayleigh scattering theory. A discrete particle model of SPR is used to understand the interaction between an Au-layer and a single AuNP. The calculated intensity profile of the single AuNP from the discrete particle model is accepted with the experimental data. In addition, the superposition between 2-AuNPs surface plasmon waves is studied using the finite element method as well as experimental data from WF-SPRM. The surface plasmon waves around the two particles generate an interference pattern. Finally, it is demonstrated that plasmonic multiple particles scattering can be represented by an effective media, which is described by Maxwell-Garnet equations.

Switchable Polyacrylic Acid Polyelectrolyte Brushes for Surface Plasmon Resonance Applications

Imaging wide-field surface plasmon resonance (SPR) microscopy sensors based on polyacrylic acid polyelectrolyte brushes (PAA PEBs) were designed to enhance the sensitivity of nano-object detection. The switching behavior of the PAA PEBs against changes in the pH values was investigated by analyzing the chemical, morphological, optical, and electrical properties. At pH ~1, the brushes collapse on the surface with the dominance of carboxylic groups (COOH). Upon the increase in the pH to nine, the switching process completes, and the brushes swell from dissociating most of the COOH groups and converting them into COO- groups. The domination of the negatively charged COO- groups increases the electrostatic repulsion in the polymer chains and stretches the brushes. The sensitivity of the SPR sensing device was investigated using a theoretical approach, as well as experimental measurements. The signal-to-noise ratio for a Au layer increases from six to eighteen after coating with PAA PEBs. In addition, the linewidth of the recorded image decreases from six pixels to five pixels by using the Au-PAA layers, which results from the enhanced spatial resolution of the recorded images. Coating a Au-layer with PAA PEBs enhances the sensitivity of the SPR sensing device, and improves the spatial resolution of the recorded image.

Surface Plasmon Resonance Sensitivity Enhancement Based on Protonated Polyaniline Films Doped by Aluminum Nitrate

Complex composite films based on polyaniline (PANI) doped hydrochloric acid (HCl) incorporated with aluminum nitrate (Al(NO₃)₃) on Au-layer were designed and synthesized as a surface plasmon resonance (SPR) sensing device. The physicochemical properties of (PANI-HCl)/Al(NO₃)₃ complex composite films were studied for various Al(NO₃)₃ concentrations (0, 2, 4, 8, 16, and 32 wt.%). The refractive index of the (PANI-HCl)/Al(NO₃)₃ complex composite films increased continuously as Al(NO₃)₃ concentrations increased. The electrical conductivity values increased from 5.10 µS/cm to 10.00 µS/cm as Al(NO₃)₃ concentration increased to 32 wt.%. The sensitivity of the SPR sensing device was investigated using a theoretical approach and experimental measurements. The theoretical system of SPR measurement confirmed that increasing Al(NO₃)₃ in (PANI-HCl)/Al(NO₃)₃ complex composite films enhanced the sensitivity from about 114.5 [Deg/RIU] for Au-layer to 159.0 [Deg/RIU] for Au-((PANI-HCl)/Al(NO₃)₃ (32 wt.%)). In addition, the signal-to-noise ratio for Au-layer was 3.95, which increased after coating by (PANI-HCl)/Al(NO₃)₃ (32 wt.%) complex composite layer to 8.82. Finally, we conclude that coating Au-layer by (PANI-HCl)/Al(NO₃)₃ complex composite films enhances the sensitivity of the SPR sensing device.

Automated Nanoparticle Analysis in Surface Plasmon Resonance Microscopy

The unique capability of surface plasmon resonance microscopy (SPRM) in single nanoparticle analysis has found use in various chemical and biological applications. While SPRM offers exceptional sensitivity, the statistical analysis of numerous nanoparticles has been extremely laborious and time-consuming. Herein, we presented an image processing software package for nanoparticle analysis in SPRM, which is empowered by a deep learning algorithm. This package enabled fully automated nanoparticle identification, digital counting, three-dimensional tracking of particle locations, and quantification of dwell time and Brownian motion properties. With a built-in image filtering process to improve the contrast, robust identification and analysis have been achieved from SPRM images of low refractive index nanoparticles. This software tool would largely promote the translation of SPRM technology into the digital sensing platform for high throughput sample screening.

Advances in Optical Single-Molecule Detection: En Route to Supersensitive Bioaffinity Assays

The ability to detect low concentrations of analytes and in particular low-abundance biomarkers is of fundamental importance, e.g., for early-stage disease diagnosis. The prospect of reaching the ultimate limit of detection has driven the development of single-molecule bioaffinity assays. While many review articles have highlighted the potentials of single-molecule technologies for analytical and diagnostic applications, these technologies are not as widespread in real-world applications as one should expect. This Review provides a theoretical background on single-molecule-or better digital-assays to critically assess their potential compared to traditional analog assays. Selected examples from the literature include bioaffinity assays for the detection of biomolecules such as proteins, nucleic acids, and viruses. The structure of the Review highlights the versatility of optical single-molecule labeling techniques, including enzymatic amplification, molecular labels, and innovative nanomaterials.

Absolute Analysis of Nanoparticle Suspension with Surface Plasmon Microscopy

The recently developed surface plasmon microscopy of single nanoparticles offers a powerful tool for monitoring particle transfer from bulk solution to the adsorbing surface. In the present work, the possibility of absolute analysis of suspension, based on particle transfer observation, was examined. A model based on particle diffusion in a laminar flow, which allows analytical solution of mass transport equation, was considered. It was demonstrated that direct determination of particle concentration, based on counting the particles that bind to the sensor surface, is possible. The model contains only independent, easy to determine parameters: flow cell geometry, flow rate, particle size, and liquid viscosity. For applicability of the model, particles should be irreversibly bound when touching the sensor surface. It was demonstrated that the required "perfect binding" is provided in certain electrolyte concentration range because even particles oppositely charged to the surface do not bind in pure water. If the binding probability is less than 100%, "absoluteness" of the method is not violated. It will require the extension of the transport model with the sticking coefficient, which can be also measured by the surface plasmon microscopy directly. The present work shows the feasibility of the absolute analysis. It demonstrates the great potential of the method toward the comprehensive nanoparticle analytics and investigation of binding processes.

Point Spread Function of Objective-Based Surface Plasmon Resonance Microscopy

Objective-based surface plasmon resonance microscopy (SPRM) is a novel optical imaging technique that can map the spatial distribution of a local refractive index based on propagating surface plasmon polaritons (SPPs). Different from some other optical microscopy that shows a dot-like point spread function (PSF), a nanosized object appears as a wave-like pattern containing parabolic tails in SPRM. The geometrical complexity of the wave-like pattern hampered the quantitative interpretation of the PSF of SPRM. Previous studies have shown that two adjacent rings were obtained in the frequency domain by applying a two-dimensional Fourier transform to such patterns. In the present work, a ring-fitting method was developed to extract geometrical features out of the dual rings and to connect these features with several experimental parameters. It was found that the radius of ring equaled to the wavevector of SPPs. Its orientation revealed the propagation direction of SPPs. The coordinate distance of the center of ring gave the parallel component of the wavevector of the incident light, which was regulated by the incident angle. The ring-broadening factor reflected the propagation length of SPPs in a reciprocal relationship. Systematical and quantitative interpretations in the frequency domain not only advanced the basic understanding on the PSF of SPRM but also opened up the possibility to utilize these frequency-domain features for detection and sensing purposes in future.

Imaging the chemical activity of single nanoparticles with optical microscopy

Chemical activity of single nanoparticles can be imaged and determined by monitoring the optical signal of each individual during chemical reactions with advanced optical microscopes. It allows for clarifying the functional heterogeneity among individuals, and for uncovering the microscopic reaction mechanisms and kinetics that could otherwise be averaged out in ensemble measurements.

Application of the PAMONO-Sensor for Quantification of Microvesicles and Determination of Nano-Particle Size Distribution

The PAMONO-sensor (plasmon assisted microscopy of nano-objects) demonstrated an ability to detect and quantify individual viruses and virus-like particles. However, another group of biological vesicles-microvesicles (100-1000 nm)-also attracts growing interest as biomarkers of different pathologies and needs development of novel techniques for characterization. This work shows the applicability of a PAMONO-sensor for selective detection of microvesicles in aquatic samples. The sensor permits comparison of relative concentrations of microvesicles between samples. We also study a possibility of repeated use of a sensor chip after elution of the microvesicle capturing layer. Moreover, we improve the detection features of the PAMONO-sensor. The detection process utilizes novel machine learning techniques on the sensor image data to estimate particle size distributions of nano-particles in polydisperse samples. Altogether, our findings expand analytical features and the application field of the PAMONO-sensor. They can also serve for a maturation of diagnostic tools based on the PAMONO-sensor platform.

Plasmonic detection and visualization of directed adsorption of charged single nanoparticles to patterned surfaces

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.

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Detection and Quantification of Single Engineered Nanoparticles in Complex Samples Using Template Matching in Wide-Field Surface Plasmon Microscopy

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 ∼10⁶ to 10¹⁰ nanoparticles per mL.

Individual Detection and Electrochemically Assisted Identification of Adsorbed Nanoparticles by Using Surface Plasmon Microscopy

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.

How reliably can a material be classified as a nanomaterial? Available particle-sizing techniques at work

ABSTRACT

Currently established and projected regulatory frameworks require the classification of materials (whether nano or non-nano) as specified by respective definitions, most of which are based on the size of the constituent particles. This brings up the question if currently available techniques for particle size determination are capable of reliably classifying materials that potentially fall under these definitions. In this study, a wide variety of characterisation techniques, including counting, fractionating, and spectroscopic techniques, has been applied to the same set of materials under harmonised conditions. The selected materials comprised well-defined quality control materials (spherical, monodisperse) as well as industrial materials of complex shapes and considerable polydispersity. As a result, each technique could be evaluated with respect to the determination of the number-weighted median size. Recommendations on the most appropriate and efficient use of techniques for different types of material are given.