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End date: 2015 × Start date: 2014 × DDC: 600 × Publisher: Cambridge : RSC Publ. ×

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    High-rate amorphous SnO2 nanomembrane anodes for Li-ion batteries with a long cycling life
    (Cambridge : RSC Publ., 2014) Liu, Xianghong; Zhang, Jun; Si, Wenping; Xi, Lixia; Oswald, Steffen; Yan, Chenglin; Schmidt, Oliver G.
    Amorphous SnO2 nanomembranes as anodes for lithium ion batteries demonstrate a long cycling life of 1000 cycles at 1600 mA g−1 with a high reversible capacity of 854 mA h g−1 and high rate capability up to 40 A g−1. The superior performance is because of the structural features of the amorphous SnO2 nanomembranes. The nanoscale thickness provides considerably reduced diffusion paths for Li+. The amorphous structure can accommodate the strain of lithiation/delithiation, especially during the initial lithiation. More importantly, the mechanical feature of deformation can buffer the strain of repeated lithiation/delithiation, thus putting off pulverization. In addition, the two-dimensional transport pathways in between nanomembranes make the pseudo-capacitance more prominent. The encouraging results demonstrate the significant potential of nanomembranes for high power batteries.
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    Surface- and tip-enhanced Raman spectroscopy reveals spin-waves in iron oxide nanoparticles
    (Cambridge : RSC Publ., 2015) Rodriguez, Raul D.; Sheremet, Evgeniya; Deckert-Gaudig, Tanja; Chaneac, Corinne; Hietschold, Michael; Deckert, Volker; Zahn, Dietrich R. T.
    Nanomaterials have the remarkable characteristic of displaying physical properties different from their bulk counterparts. An additional degree of complexity and functionality arises when oxide nanoparticles interact with metallic nanostructures. In this context the Raman spectra due to plasmonic enhancement of iron oxide nanocrystals are here reported showing the activation of spin-waves. Iron oxide nanoparticles on gold and silver tips are found to display a band around 1584 cm−1 attributed to a spin-wave magnon mode. This magnon mode is not observed for nanoparticles deposited on silicon (111) or on glass substrates. Metal–nanoparticle interaction and the strongly localized electromagnetic field contribute to the appearance of this mode. The localized excitation that generates this mode is confirmed by tip-enhanced Raman spectroscopy (TERS). The appearance of the spin-waves only when the TERS tip is in close proximity to a nanocrystal edge suggests that the coupling of a localized plasmon with spin-waves arises due to broken symmetry at the nanoparticle border and the additional electric field confinement. Beyond phonon confinement effects previously reported in similar systems, this work offers significant insights on the plasmon-assisted generation and detection of spin-waves optically induced.
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    A manual and an automatic TERS based virus discrimination
    (Cambridge : RSC Publ., 2015) Olschewski, Konstanze; Kämmer, Evelyn; Stöckel, Stephan; Bocklitz, Thomas; Deckert-Gaudig, Tanja; Zell, Roland; Cialla-May, Dana; Weber, Karina; Deckert, Volker; Popp, Jürgen
    Rapid techniques for virus identification are more relevant today than ever. Conventional virus detection and identification strategies generally rest upon various microbiological methods and genomic approaches, which are not suited for the analysis of single virus particles. In contrast, the highly sensitive spectroscopic technique tip-enhanced Raman spectroscopy (TERS) allows the characterisation of biological nano-structures like virions on a single-particle level. In this study, the feasibility of TERS in combination with chemometrics to discriminate two pathogenic viruses, Varicella-zoster virus (VZV) and Porcine teschovirus (PTV), was investigated. In a first step, chemometric methods transformed the spectral data in such a way that a rapid visual discrimination of the two examined viruses was enabled. In a further step, these methods were utilised to perform an automatic quality rating of the measured spectra. Spectra that passed this test were eventually used to calculate a classification model, through which a successful discrimination of the two viral species based on TERS spectra of single virus particles was also realised with a classification accuracy of 91%.