Metallic nanostructures have the potential to be used in a variety of applications related to sensing and imaging biological molecules due to their ability to enhance the way molecules absorb and emit light. However, the interaction between metallic nanostructure and molecules can give rise to difficulty with determining precise molecular positions and orientations and therefore pose major challenges in the field of super-resolution imaging. In this work, we used axially defocused imaging to analyze the interaction between a single fluorescent molecule and a metallic nanostructure. In addition, a pattern matching algorithm was used to analyze the images, explore the interaction between the molecule and the nanostructure and thereby determine the lateral position. The accuracy was found to improve while the degree was dependent on the dipolar orientation and the distance between dipole and nanostructure. This approach has the potential to improve the reliability of using metallic nanostructures for imaging and sensing in the future and opens up new possibilities for various imaging and sensing methods.
We investigate the method to analyze interferometric plasmonic microscopy (IPM) images using a deep learning approach. An IPM image was generated by employing an optical model: the image intensity was formed by reflected and scattered fields. Convolutional neural network was utilized for the classification of IPM images. Conventional detection method based on fourier filtering was taken for comparison with the proposed method. It was confirmed that deep learning improves the performance significantly, in particular, robustness to noise. These results suggested applicability of deep learning beyond IPM images with higher efficiency.
We investigate a way to detect images of surface plasmon scattering using deep learning approach. Unlike fluorescence imaging, the image of surface plasmon scattering shows much worse resolution due to propagation length of surface plasmon polariton. In this work, deep learning approach is taken to address this issue and to discriminate multiple target objects under complex and noisy environment. Conventional detection method based on fourier filtering and deconvolution was employed to compare the performance of the proposed method. It was shown that deep learning improves the accuracy by about six times, and especially more useful in noisy environment.
KEYWORDS: Near field, Gold, Switching, Nanostructures, Plasmonics, Near field scanning optical microscopy, Atomic force microscopy, Quantitative analysis
We investigate switching near-field distribution on metal random nanoislands by changing the direction and the angle of light incidence in 14 channel modes. Distribution of the near-fields induced by different channel modes was calculated by finite difference time domain method. The size of near-fields under oblique channel modes ranges 48 - 77 nm in contrast to 127 - 145 nm with normal incidence. Quantitative analysis of near-field position was performed relative to nanoislands. Near-field position was largely well aligned with the direction of incident channel modes. Switching near fields was experimentally confirmed in two ways, first by measurement of fluorescence intensity and by NSOM. Fluorescence experiment was conducted by using bare glass substrate and gold nanoislands in seven channel modes. Fluorescence intensity on bare glass substrate shows symmetric intensity changes with channel modes. However, fluorescence intensity on gold nanoislands was found to be asymmetric. For quantitative analysis, mean-squared error (MSE) was calculated by defining fluorescence intensity as a 7D vector. Distribution of MSE in case of gold nanoislands was broader than on bare glass substrate. In other words, near fields induced on gold nanoislands were switched more strongly than bare glass substrate. Also, near fields induced on nanoislands were measured directly using NSOM in two channel modes. It was confirmed that spatial positions of near-fields depend on channel modes. The results of this study suggest that the near fields can be controlled by adjusting channel modes, which opens possibilities of highly sensitive and super-resolved detection and imaging.
In this report, we describe improvement of image resolution in surface plasmon resonance microscopy (SPRM) which suffers from poor quality due to severe surface plasmon (SP) propagation. Our approach takes two-channel momentum sampling by switched light incidence followed by minimum filtering to implement spatially switched SPRM (ssSPRM). The performance evaluated with periodic wires in comparison with conventional SPRM and bright-field microscopy shows that the effect of SP propagation can be circumvented and the effective decay length of SPRM is calculated to increase by only 7% compared to that of bright-field images.
KEYWORDS: Nanolithography, Plasmonics, Near field optics, Near field, Biosensors, Target detection, Lithography, Biosensing, Nanostructures, Thin films
The detection sensitivity of surface plasmon resonance (SPR) biosensors has been improved by employing colocalization of spatial distribution of electromagnetic near-fields and detection molecules. We have used plasmon nanolithography to achieve light-matter colocalization on triangular nanoaperture arrays and optimized array configurations to improve colocalization efficiency. Streptavidin-biotin interactions were measured to validate the concept. It was confirmed that colocalized distributions of target binding and localized near-fields produced larger optical detection sensitivity. The colocalized detection was also shown to come with wider dynamic range than noncolocalized detection. The effective limit-of-detection of colocalized measurements was on the order of 30 pM. The colocalized detection sensitivity was estimated to be below 1 fg/mm2 in a 100-nm deep evanescent area, an enhancement by more than three orders of magnitude over conventional SPR sensor.
KEYWORDS: Luminescence, Near field, Silver, Microscopy, Near field optics, Surface plasmons, Nanolithography, Scanning electron microscopy, Image resolution, Image restoration
We have studied fluorescence cellular imaging with randomly distributed localized near-field induced by silver nano-islands. For the fabrication of nano-islands, a 10-nm silver thin film evaporated on a BK7 glass substrate with an adhesion layer of 2-nm thick chromium. Micrometer sized silver square pattern was defined using e-beam lithography and then the film was annealed at ~ 200°C. Raw images were restored using electric field distribution produced on the surface of random nano-islands. Nano-islands were modeled from SEM images. 488-nm p-polarized light source was set to be incident at 60°. Simulation results show that localized electric fields were created among nano-islands and that their average size was found to be ~135 nm. The feasibility was tested using conventional total internal reflection fluorescence microscopy while the angle of incidence was adjusted to maximize field enhancement. Mouse microphage cells were cultured on nano-islands, and actin filaments were selectively stained with FITC-conjugated phalloidin. Acquired images were deconvolved based on linear imaging theory, in which molecular distribution was sampled by randomly distributed localized near-field and blurred by point spread function of far-field optics. The optimum fluorophore distribution was probabilistically estimated by repetitively matching a raw image. The deconvolved images are estimated to have a resolution in the range of 100-150 nm largely determined by the size of localized near-fields. We also discuss and compare the results with images acquired with periodic nano-aperture arrays in various optical configurations to excite localized plasmonic fields and to produce super-resolved molecular images.
We present surface plasmon enhanced fluorescence microscopy with random spatial sampling using patterned block of silver nanoislands. Rigorous coupled wave analysis was performed to confirm near-field localization on nanoislands. Random nanoislands were fabricated in silver by temperature annealing. By analyzing random near-field distribution, average size of localized fields was found to be on the order of 135 nm. Randomly localized near-fields were used to spatially sample F-actin of J774 cells (mouse macrophage cell-line). Image deconvolution algorithm based on linear imaging theory was established for stochastic estimation of fluorescent molecular distribution. The alignment between near-field distribution and raw image was performed by the patterned block. The achieved resolution is dependent upon factors including the size of localized fields and estimated to be 100-150 nm.
We analyze and evaluate super-resolved image acquisition with full-field localization microscopy in which an individual signal sampled by localization may or may not be switched. For the analysis, Nyquist-Shannon sampling theorem based on ideal delta function was extended to sampling with unit pulse comb and surface-enhanced localized near-field that was numerically calculated with finite difference time domain. Sampling with unit pulse was investigated in Fourier domain where magnitude of baseband becomes larger than that of adjacent subband, i.e. aliasing effect is reduced owing to pulse width. Standard Lena image was employed as imaging target and a diffraction-limited optical system is assumed. A peak signal-to-noise ratio (PSNR) was introduced to evaluate the efficiency of image reconstruction quantitatively. When the target was sampled without switching by unit pulse as the sampling width and period are varied, PSNR increased eventually to 18.1 dB, which is the PSNR of a conventional diffraction-limited image. PSNR was found to increase with a longer pulse width due to reduced aliasing effect. When switching of individual sampling pulses was applied, blurry artifact outside the excited field is removed for each pulse and PSNR soars to 25.6 dB with a shortened pulse period, i.e. effective resolution of 72 nm is obtained, which can further be decreased.
We have considered linear nanoaperture arrays for super-resolved live cell imaging. The nanoaperture arrays consist of nanoholes of varying diameter. Each nanohole localizes near-field distribution and produces extraordinary optical transmission (EOT) by surface plasmon localization. Much deeper light penetration was achieved in EOT than under total internal reflection. The results can be used to implement subdiffraction-limited axial resolution when applied to microscopy.
KEYWORDS: Nanostructures, Near field, Nanoplasmonics, Surface plasmons, Super resolution, Near field optics, Biosensors, Optical engineering, Image resolution, Imaging systems
We have numerically analyzed the effect of geometrical parameters of circular, rhombic, and square nanostructure arrays when light fields are localized based on surface-enhanced nanoplasmonics. It was found that subdiffraction-limited field localization can be achieved using the nanostructures. We have also discussed various approaches to implement superresolution imaging systems using the obtained localized fields. The localized field can be used to implement colocalized light matter distribution with much enhanced sensitivity in surface plasmon resonance biosensor and more interestingly for super-resolution full-field microscopy.
We present a theoretical approach to single nanoparticle detection using surface plasmon scattering microscopy. Through rigorous coupled wave analysis assuming light incidence on a gold coated BK7 glass substrate under total internal reflection condition for a 200-nm polystyrene as targets attached to the gold film, it was found that surface plasmon polariton induced by incident light on the gold thin film is perturbed. As a result, parabolic waves were observed in the reflection plane. By varying angles of incidence and wavelengths, optimum incident conditions for surface plasmon scattering microscopy were obtained.
KEYWORDS: Microscopy, Surface plasmons, Near field, Luminescence, Silver, Live cell imaging, Nanostructures, Scanning electron microscopy, Molecular interactions, Thin films
Localized surface plasmon enhanced microscopy based on nanoislands of random spatial distribution was demonstrated for imaging live cells and molecular interactions. Nanoislands were produced without lithography by high temperature annealing under various processing conditions. The localization of near-field distribution that is associated with localized surface plasmon on metallic random nanoislands was analyzed theoretically and experimentally in comparison with periodic nanostructures. For experimental validation in live cell imaging, mouse macrophage-like cell line stained with Alexa Fluor 488 was prepared on nanoislands. The results suggest the possibility of attaining the imaging resolution on the order of 80 nm.
We have investigated near field distribution and absorption cross-section of CdSe quantum dot (QD) conjugated gold nanoparticles using three-dimensional finite-difference time-domain method. A gold nanoparticle core was modeled with a different SiO2 shell thickness and surface density of QDs. Absorption cross-section was found to be proportionate to the shell thickness and the QD surface density. In regard to the absorption by a single QD, either nanoparticle-QD coupling or QD-QD coupling was dominant depending on the surface density. Moreover, shell thickness weakens the coupling and the absorption of a single QD. Finally, enhanced absorption by a QD-conjugated nanoparticle dimer structure is also reported as a result of field enhancement between NPs assisted by QDs.
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