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À propos de : Remote Fluorescence Imaging of DynamicConcentration Profiles with Micrometer ResolutionUsing a Coherent Optical Fiber Bundle        

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  • Remote Fluorescence Imaging of DynamicConcentration Profiles with Micrometer ResolutionUsing a Coherent Optical Fiber Bundle
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  • Dynamic concentration profiles within the diffusion layerof an electrode were imaged in situ using fluorescencedetection through a multichannel imaging fiber. In thiswork, a coherent optical fiber bundle is positioned orthogonal to the surface of an electrode and is used toreport spatial and temporal micrometric changes in thefluorescence intensity of an initial fluorescent species. Thefluorescence signal is directly related to the local concentration of a redox fluorescent reagent, which is electrochemically modulated by the electrode. Fluorescenceimages are collected through the optical fiber bundleduring the oxidation of tris(2,2‘-bipyridine)ruthenium(II)to ruthenium(III) at a diffusion-limited rate and allow theconcentration profiles of Ru(II) reagent to be monitoredin situ as a function of time. Tris(2,2‘-bipyridine)ruthenium(II) is excited at 485 nm and emits fluorescence at605 nm, whereas the Ru(III) oxidation state is notfluorescent. Our experiments emphasize the influence oftwo parameters on the micrometer spatial resolution: thenumerical aperture of optical fibers within the bundle andthe Ru(II) bulk concentration. The extent of the volumeprobed by each individual fiber of the bundle is discussedqualitatively in terms of a primary inner-filter effect andrefractive index gradient. Experimentally measured fluorescence intensity profiles were found to be in very goodagreement with concentration profiles predicted uponconsidering planar diffusion and thus validate the conceptof this new application of imaging fibers. The originalityof this remote approach is to provide a global view of theentire diffusion layer at a given time through one singleimage and to allow the time expansion of the diffusionlayer to be followed quantitatively in real time.
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