Jamming transition in a highly dense granular system under vertical vibration

The dynamics of the jamming transition in a three-dimensional granular system under vertical vibration is studied using diffusing-wave spectroscopy. When the maximum acceleration of the external vibration is large, the granular system behaves like a fluid, with the dynamic correlation function G(t) relaxing rapidly. As the acceleration of vibration approaches the gravitational acceleration g, the relaxation of G(t) slows down dramatically, and eventually stops. Thus the system undergoes a phase transition and behaves like a solid. Near the transition point, we find that the structural relaxation shows a stretched exponential behavior. This behavior is analogous to the behavior of supercooled liquids close to the glass transition.Comment: 5 pages, 5 figures, accepted by Phys. Rev.

SRZoo: An integrated repository for super-resolution using deep learning

Deep learning-based image processing algorithms, including image super-resolution methods, have been proposed with significant improvement in performance in recent years. However, their implementations and evaluations are dispersed in terms of various deep learning frameworks and various evaluation criteria. In this paper, we propose an integrated repository for the super-resolution tasks, named SRZoo, to provide state-of-the-art super-resolution models in a single place. Our repository offers not only converted versions of existing pre-trained models, but also documentation and toolkits for converting other models. In addition, SRZoo provides platform-agnostic image reconstruction tools to obtain super-resolved images and evaluate the performance in place. It also brings the opportunity of extension to advanced image-based researches and other image processing models. The software, documentation, and pre-trained models are publicly available on GitHub.Comment: Accepted in ICASSP 2020, code available at https://github.com/idearibosome/srzo

Ruthenium anchored on carbon nanotube electrocatalyst for hydrogen production with enhanced Faradaic efficiency

Developing efficient and stable electrocatalysts is crucial for the electrochemical production of pure and clean hydrogen. For practical applications, an economical and facile method of producing catalysts for the hydrogen evolution reaction (HER) is essential. Here, we report ruthenium (Ru) nanoparticles uniformly deposited on multi-walled carbon nanotubes (MWCNTs) as an efficient HER catalyst. The catalyst exhibits the small overpotentials of 13 and 17 mV at a current density of 10 mA cm(-2) in 0.5M aq. H2SO4 and 1.0M aq. KOH, respectively, surpassing the commercial Pt/C (16 mV and 33 mV). Moreover, the catalyst has excellent stability in both media, showing almost "zeroloss" during cycling. In a real device, the catalyst produces 15.4% more hydrogen per power consumed, and shows a higher Faradaic efficiency (92.28%) than the benchmark Pt/C (85.97%). Density functional theory calculations suggest that Ru-C bonding is the most plausible active site for the HER