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Sökning: WFRF:(Luo Zhihui)

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1.
  • Luo, Zhihui, et al. (författare)
  • Revealing the Charge Storage Mechanism of Nickel Oxide Electrochromic Supercapacitors
  • 2020
  • Ingår i: ACS Applied Materials and Interfaces. - : AMER CHEMICAL SOC. - 1944-8244 .- 1944-8252. ; 12:35, s. 39098-39107
  • Tidskriftsartikel (refereegranskat)abstract
    • Nickel oxide (NiO) is considered one of the most promising positive anode materials for electrochromic supercapacitors. Nevertheless, a detailed mechanism of the electrochromic and energy storage process has yet to be unraveled. In this research, the charge storage mechanism of a NiO electrochromic electrode was investigated by combining the in-depth experimental and theoretical analyses. Experimentally, a kinetic analysis of the Li-ion behavior based on the cyclic voltammetry curves reveals the major contribution of surface capacitance versus total capacity, providing fast reaction kinetics and a highly reversible electrochromic performance. Theoretically, our model uncovers that Li ions prefer to adsorb at fcc sites on the NiO(1 1 1) surface, then diffuse horizontally over the plane, and finally migrate in the bulk. More significantly, the calculated theoretical surface capacity (106 mA h g(-1)) accounts for about 77.4% of the total experimental capacity (137 mA h g(-1)), indicating that the surface storage process dominates the whole charge storage, which is in accordance with the experimental results. This work provides a fundamental understanding of transition-metal oxides for application in electrochromic supercapacitors and can also promote the exploration of novel electrode materials for high-performance electrochromic supercapacitors.
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2.
  • Kristan, Matej, et al. (författare)
  • The Sixth Visual Object Tracking VOT2018 Challenge Results
  • 2019
  • Ingår i: Computer Vision – ECCV 2018 Workshops. - Cham : Springer Publishing Company. - 9783030110086 - 9783030110093 ; , s. 3-53
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a “real-time” experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. A long-term tracking subchallenge has been introduced to the set of standard VOT sub-challenges. The new subchallenge focuses on long-term tracking properties, namely coping with target disappearance and reappearance. A new dataset has been compiled and a performance evaluation methodology that focuses on long-term tracking capabilities has been adopted. The VOT toolkit has been updated to support both standard short-term and the new long-term tracking subchallenges. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).
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