A triphenylalanine-based superhydrogel shows automatic syneresis (self-compressing properties) with time and this self-shrinking behavior has been successfully utilized to remove toxic lead ions and organic dyes from waste-water efficiently with the ability to re-use for a few times.
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A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra.
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Department of Biology, University at Albany, SUNY, 1400 Washington Ave, Albany, NY 12222, United States.
The accuracy of assigning fluorophore identity and abundance, known as spectral unmixing, in biological fluorescence microscopy images remains a significant challenge due to the substantial overlap in emission spectra among fluorophores. In traditional laser scanning confocal spectral microscopy, fluorophore information is acquired by recording emission spectra with a single combination of discrete excitation wavelengths. However, organic fluorophores possess characteristic excitation spectra in addition to their unique emission spectral signatures.
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We recently demonstrated molecular plasmons in cyanine dyes for the conversion of photon energy into mechanical energy through a whole-molecule coherent vibronic-driven-action. Here we present a model, a molecular plasmon analogue of molecular orbital theory and of plasmon hybridization in metal nanostructures. This model describes that molecular plasmons can be obtained from the combination or hybridization of elementary molecular fragments, resulting in molecules with hybridized plasmon resonances in the electromagnetic spectrum.
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Institute of Environmental Science, Shanxi University, Taiyuan 030006, China.
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