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End date: 2021 × Start date: 2020 × DDC: 620 × Publisher: Berlin : Springer Nature ×

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Now showing 1 - 5 of 5
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    Persistent and reversible solid iodine electrodeposition in nanoporous carbons
    (Berlin : Springer Nature, 2020) Prehal, Christian; Fitzek, Harald; Kothleitner, Gerad; Presser, Volker; Gollas, Bernhard; Freunberger, Stefan A.; Abbas, Qamar
    Aqueous iodine based electrochemical energy storage is considered a potential candidate to improve sustainability and performance of current battery and supercapacitor technology. It harnesses the redox activity of iodide, iodine, and polyiodide species in the confined geometry of nanoporous carbon electrodes. However, current descriptions of the electrochemical reaction mechanism to interconvert these species are elusive. Here we show that electrochemical oxidation of iodide in nanoporous carbons forms persistent solid iodine deposits. Confinement slows down dissolution into triiodide and pentaiodide, responsible for otherwise significant self-discharge via shuttling. The main tools for these insights are in situ Raman spectroscopy and in situ small and wide-angle X-ray scattering (in situ SAXS/WAXS). In situ Raman confirms the reversible formation of triiodide and pentaiodide. In situ SAXS/WAXS indicates remarkable amounts of solid iodine deposited in the carbon nanopores. Combined with stochastic modeling, in situ SAXS allows quantifying the solid iodine volume fraction and visualizing the iodine structure on 3D lattice models at the sub-nanometer scale. Based on the derived mechanism, we demonstrate strategies for improved iodine pore filling capacity and prevention of self-discharge, applicable to hybrid supercapacitors and batteries.
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    Light-regulated growth from dynamic swollen substrates for making rough surfaces
    (Berlin : Springer Nature, 2020) Xue, Lulu; Xiong, Xinhong; Krishnan, Baiju P.; Puza, Fatih; Wang, Sheng; Zheng, Yijun; Cui, Jiaxi
    Natural organic structures form via a growth mode in which nutrients are absorbed, transported, and integrated. In contrast, synthetic architectures are constructed through fundamentally different methods, such as assembling, molding, cutting, and printing. Here, we report a photoinduced strategy for regulating the localized growth of microstructures from the surface of a swollen dynamic substrate, by coupling photolysis, photopolymerization, and transesterification together. Photolysis is used to generate dissociable ionic groups to enhance the swelling ability that drives nutrient solutions containing polymerizable components into the irradiated region, photopolymerization converts polymerizable components into polymers, and transesterification incorporates newly formed polymers into the original network structure. Such light-regulated growth is spatially controllable and dose-dependent and allows fine modulation of the size, composition, and mechanical properties of the grown structures. We also demonstrate the application of this process in the preparation of microstructures on a surface and the restoration of large-scale surface damage.
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    Extracting local nucleation fields in permanent magnets using machine learning
    (Berlin : Springer Nature, 2020) Gusenbauer, Markus; Oezelt, Harald; Fischbacher, Johann; Kovacs, Alexander; Zhao, Panpan; Woodcock, Thomas George; Schrefl, Thomas
    Microstructural features play an important role in the quality of permanent magnets. The coercivity is greatly influenced by crystallographic defects, like twin boundaries, as is well known for MnAl-C. It would be very useful to be able to predict the macroscopic coercivity from microstructure imaging. Although this is not possible now, in the present work we examine a related question, namely the prediction of simulated nucleation fields of a quasi-three-dimensional (rescaled and extruded) system constructed from a two-dimensional image. We extract features of the image and analyze them via machine learning. A large number of extruded systems are constructed from 10 × 10 pixel sub-images of an Electron Backscatter Diffraction (EBSD) image using an automated meshing procedure. A local nucleation field is calculated by micromagnetic simulation of each quasi-three-dimensional system. Decision trees, trained with the simulation results, can predict nucleation fields of these quasi-three-dimensional systems from new images within seconds. As for now we cannot quantitatively predict the macroscopic coercivity, nevertheless we can identify weak spots in the magnet and see trends in the nucleation field distribution.
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    Wettability control of polymeric microstructures replicated from laser-patterned stamps
    (Berlin : Springer Nature, 2020) Fu, Yangxi; Soldera, Marcos; Wang, Wei; Milles, Stephan; Deng, Kangfa; Voisiat, Bogdan; Nielsch, Kornelius; Lasagni, Andrés Fabian
    In this study, two-step approaches to fabricate periodic microstructures on polyethylene terephthalate (PET) and poly(methyl methacrylate) (PMMA) substrates are presented to control the wettability of polymeric surfaces. Micropillar arrays with periods between 1.6 and 4.6 µm are patterned by plate-to-plate hot embossing using chromium stamps structured by four-beam Direct Laser Interference Patterning (DLIP). By varying the laser parameters, the shape, spatial period, and structure height of the laser-induced topography on Cr stamps are controlled. After that, the wettability properties, namely the static, advancing/receding contact angles (CAs), and contact angle hysteresis were characterized on the patterned PET and PMMA surfaces. The results indicate that the micropillar arrays induced a hydrophobic state in both polymers with CAs up to 140° in the case of PET, without modifying the surface chemistry. However, the structured surfaces show high adhesion to water, as the droplets stick to the surfaces and do not roll down even upon turning the substrates upside down. To investigate the wetting state on the structured polymers, theoretical CAs predicted by Wenzel and Cassie-Baxter models for selected structured samples with different topographical characteristics are also calculated and compared with the experimental data.
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    Tactile perception of randomly rough surfaces
    (Berlin : Springer Nature, 2020) Sahli, Riad; Prot, Aubin; Wang, Anle; Müser, Martin H.; Piovarči, Michal; Didyk, Piotr; Bennewitz, Roland
    Most everyday surfaces are randomly rough and self-similar on sufficiently small scales. We investigated the tactile perception of randomly rough surfaces using 3D-printed samples, where the topographic structure and the statistical properties of scale-dependent roughness were varied independently. We found that the tactile perception of similarity between surfaces was dominated by the statistical micro-scale roughness rather than by their topographic resemblance. Participants were able to notice differences in the Hurst roughness exponent of 0.2, or a difference in surface curvature of 0.8 mm−1 for surfaces with curvatures between 1 and 3 mm−1. In contrast, visual perception of similarity between color-coded images of the surface height was dominated by their topographic resemblance. We conclude that vibration cues from roughness at the length scale of the finger ridge distance distract the participants from including the topography into the judgement of similarity. The interaction between surface asperities and fingertip skin led to higher friction for higher micro-scale roughness. Individual friction data allowed us to construct a psychometric curve which relates similarity decisions to differences in friction. Participants noticed differences in the friction coefficient as small as 0.035 for samples with friction coefficients between 0.34 and 0.45.