Search

A straightforward method to achieve super-resolution consists of taking an image sequence of stochastically blinking emitters using a standard wide-field fluorescence microscope. Densely packed single molecules can be distinguished sequentially in time using high-precision localization algorithms (e.g., PALM and STORM) or by analyzing the statistics of the temporal fluctuations (SOFI). In a face-to-face comparison of the two post-processing algorithms, we show that localization-based super-resolution can deliver higher resolution enhancements but imposes significant constraints on the blinking behavior of the probes, which limits its applicability for live-cell imaging. SOFI, on the other hand, works more consistently over different photo-switching kinetics and also delivers information about the specific blinking statistics. Its suitability for low SNR acquisition reveals SOFI's potential as a high-speed super-resolution imaging technique.

SNAP‐tag: We introduce a photoswitchable O6‐benzylguanine derivative and demonstrate its use for super‐resolution microscopy of SNAP‐tagged proteins based on single fluorophore localization. Stochastic Optical Reconstruction Microscopy (STORM) reveals SNAP‐tagged microtubule structures with ∼25 nm resolution. The described probe in combination with the versatile SNAP‐tag labeling opens new possibilities for imaging biological structures at the nanoscale.

We report on the characterization of long-range surface plasmon waveguide bends at telecom wavelengths (lambda=1550 nm). The structures consist of a thin Au stripe embedded in a transparent polymer film. When the polymer thickness is larger than the lateral extension of the plasmon, the stripe sustains a conventional long-range mode; in the opposite case, the mode is hybrid because its field distribution is confined by total internal reflection in the dielectric cladding. This hybridization increases the damping by absorption but dramatically reduces the radiation loss that occurs for curved geometries, such as bends. Our results are supported quantitatively by full-wave finite-element simulations.

Using a finite-element, full-wave modeling approach, we present a flexible method of analyzing and simulating dielectric and plasmonic waveguide structures as well as their mode coupling. This method is applied to an integrated plasmonic circuit where a straight dielectric waveguide couples through a straight hybrid long-range plasmon waveguide to a uniformly bent hybrid one. The hybrid waveguide comprises a thin metal core embedded in a two-dimensional dielectric waveguide. The performance of such plasmonic circuits in terms of insertion losses is discussed.

We perform rigorous simulations of hybrid long-range modes guided by a central metal core and a two-dimensional dielectric slab. We show that these modes are subject to fewer limitations than conventional long-range plasmon modes in terms of field confinement and guiding performance. These hybrid modes may offer substantial improvements for integrated plasmonic components, as illustrated here by the consideration of 90 degrees bends.

Transport of proteins in liquid-filled nanometer-sized apertures with charged surfaces based on both diffusion and convective flow is investigated with the use of fluorescence correlation spectroscopy. The measured fluctuations of fluorescence allow the evaluation of the concentration of molecules directly inside the nanochannel. Here, we supply theoretical models describing the concentration profile of proteins inside nano-confinements, taking into account the steric exclusion, the presence of reversibly adsorbed molecules on surfaces and the exclusion-enrichment effect due to interaction with the electrical double layer. Therefore, this study presents a new step for a deeper understanding of the transport of molecules in nanofluidics.

The diffusion of charged proteins in liquid-filled nanometer-sized apertures with charged surfaces has been investigated with fluorescence correlation spectroscopy (FCS). Based on a two-dimensional (2D) multicomponent diffusion model, key parameters such as the number of molecules diffusing freely inside the nanochannel or interacting with the surfaces, together with the specific diffusion parameters, could be extracted. Different regimes of diffusion have been observed and described by a model, which takes into account the steric exclusion, the reversible surface adsorption of the biomolecules, and the exclusion-enrichment effect that is due to the charge of the proteins and the ionic strength of the solution. Conditions where the diffusion of proteins through nano-confined spaces can be of the same magnitude as in the bulk were both predicted and experimentally verified.