3 research outputs found

    Fluorescent-Probe Characterization for Pore-Space Mapping with Single-Particle Tracking

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    Porous solids often contain complex pore networks with pores of various sizes. Tracking individual fluorescent probes as they diffuse through porous materials can be used to characterize pore networks at tens of nanometers resolution. However, understanding the motion behavior of fluorescent probes in confinement is crucial to reliably derive pore network properties. Here, we introduce well-defined lithography-made model pores developed to study probe behavior in confinement. We investigated the influence of probe-host interactions on diffusion and trapping of confined single-emitter quantum-dot probes. Using the pH-responsiveness of the probes, we were able to largely suppress trapping at the pore walls. This enabled us to define experimental conditions for mapping of the accessible pore space of a one-dimensional pore array as well as a real-life polymerization-catalyst-support particle

    Fluorescent-Probe Characterization for Pore-Space Mapping with Single-Particle Tracking

    Get PDF
    Porous solids often contain complex pore networks with pores of various sizes. Tracking individual fluorescent probes as they diffuse through porous materials can be used to characterize pore networks at tens of nanometers resolution. However, understanding the motion behavior of fluorescent probes in confinement is crucial to reliably derive pore network properties. Here, we introduce well-defined lithography-made model pores developed to study probe behavior in confinement. We investigated the influence of probe-host interactions on diffusion and trapping of confined single-emitter quantum-dot probes. Using the pH-responsiveness of the probes, we were able to largely suppress trapping at the pore walls. This enabled us to define experimental conditions for mapping of the accessible pore space of a one-dimensional pore array as well as a real-life polymerization-catalyst-support particle

    Erratum to: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

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    In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper
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