Fluorescent nano-particle labeling methods produce high contrast signals for rare-cell detection. Unfortunately, many imaging methods cannot yet reach adequate space-bandwidth products for these samples. We propose a lens-free time-gated fluorescence system using pulsed excitation and long-lifetime fluorescent nanoparticles. We minimize the required sample to sensor distance by applying a temporal filter instead of spectral filters and achieve a resolution of 8.77 μm. This approach simplifies the architecture, requires minimal image reconstruction, and reduces system size and cost. Our method surpasses the performance of other non-computational fluorescent lens-free imaging approaches and provides a foundation for future resolution enhancement.
Bead-based assays are traditionally difficult to adapt for high-sensitivity quantitative point-of-care diagnostics. Here we use lensfree optical microscopes with automated image processing to quantitatively sense specific proteins in solution via the agglutination of functionalized beads within a microfluidic chip. Simple protocols and compact and inexpensive readout devices make our approach well-suited for point-of-care diagnostics. We sense interferon gamma, a biomarker of infectious and inflammatory disease, as well as NeutrAvidin. Furthermore, we discuss computational methods for improving the identification of small particles in the lensfree images, including sparsity-promoting regularized reconstruction and vectorial Green’s function modeling based on dipole electromagnetic scattering theory.
Scattering from nanoparticles has previously been utilized to achieve sub-wavelength resolution in microscopy, sub-diffraction beam widths in focused laser beams, and improved sensitivity in biological sensing. However, these applications often require time-consuming detailed vectorial simulation of the interaction of incident fields with the nanoparticles to achieve the desired performance. On the other hand, the scalar angular spectrum method is widely used for rapid holographic reconstruction, but can be inaccurate for sub-wavelength features, depending on the light-matter interaction model. Here we establish the domains of accuracy of three scalar light-matter interaction models for arrays of randomly distributed dielectric and metallic nanoparticles.
The angular spectrum method (ASM) is commonly used for reconstructing images in digital holography for applications such as lens-free holography and metasurface design. The lack of Fraunhofer or Fresnel approximations and computational speed due to the fast Fourier transform makes ASM a competitive field propagation method. Using a thin-object approximation, ASM can also efficiently compute fields over large areas, enabling faster calculations than those using other methods such as finite difference time domain or Mie theory. However, thin-object approximations are not accurate for nanoscale objects and so ASM is currently unable to accurately recover nanoscale object information. Here we test three ASM transmission models that use a scalar description to model the interaction of a plane wave with a plane of randomly assembled nanoparticles and evaluate the accuracy of each against the discrete dipole method (DDA). Random distributions of nanoparticles are often used in super-resolution, sub-diffraction limit, or specialized sensing applications as they are easy to place. We study the performance of the three transmission models for gold and polystyrene nanospheres of 30 nm, 60 nm, and 100 nm in diameter for different particle densities. The performance of the models is evaluated against simulations using DDA, which is validated against Mie theory calculations, for the same configurations. We show transmission models in ASM that perform within 20% accuracy of the fields calculated using DDA.
The coupling of optical near fields and far-field scattering by arrays of nanoparticles can be harnessed to improve superresolution imaging, sub-diffraction limit beam focusing, or specialized sensing applications. Numerical simulation and optimization of all these processes commonly entails calculating far-field electric field distributions. However, widelyused simulation techniques such as finite difference time domain (FDTD), Mie theory, and the discrete dipole approximation (DDA) are computationally intensive for large numbers of particles and consequently restrict the size of the domain. Alternatively, the angular spectrum method (ASM) combined with a thin-object approximation, which are commonly used in lens-free holography and other applications to reconstruct images, are well-suited for computationallyefficient large-area calculations. But this approach is not necessarily accurate for nanostructured surfaces. Here we investigate the accuracy of the ASM in modeling the scattered field from a plane wave incident on a plane of randomly assembled nanoparticles. Many super-resolution, sub-diffraction limit, or specialized sensing applications utilize randomly distributed nanoparticles for the ease of placement. We investigate the dipole matched transmission model (DMT) using ASM for polystyrene and gold nanoparticles 30 nm, 60 nm, and 100 nm in diameter for various fill fractions of the nanoparticle plane. We compare the results from the ASM with DDA, which is validated against Mie theory calculations.
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