Beyond state-of-the-art lithium-ion battery (LIB) technology with metallic lithium anodes to replace conventional ion intercalation anode materials is highly desirable because of lithium's highest specific capacity (3,860 mA/g) and lowest negative electrochemical potential (∼3.040 V vs. the standard hydrogen electrode). In this work, we report for the first time, to our knowledge, a 3D lithium-ion-conducting ceramic network based on garnet-type Li 6.4 La 3 Zr 2 Al 0.2 O 12 (LLZO) lithium-ion conductor to provide continuous Li + transfer channels in a polyethylene oxide (PEO)-based composite. This composite structure further provides structural reinforcement to enhance the mechanical properties of the polymer matrix. The flexible solid-state electrolyte composite membrane exhibited an ionic conductivity of 2.5 × 10 −4 S/cm at room temperature. The membrane can effectively block dendrites in a symmetric Li j electrolyte j Li cell during repeated lithium stripping/plating at room temperature, with a current density of 0.2 mA/cm 2 for around 500 h and a current density of 0.5 mA/cm 2 for over 300 h. These results provide an all solid ion-conducting membrane that can be applied to flexible LIBs and other electrochemical energy storage systems, such as lithium-sulfur batteries.solid-state electrolyte | 3D garnet nanofibers | polyethylene oxide | ionic conductor | flexible membrane H igh capacity, high safety, and long lifespan are three of the most important key factors to developing rechargeable lithium batteries for applications in portable electronics, transportation (e.g., electrical vehicles), and large-scale energy storage systems (1-5). Based on state-of-the-art lithium-ion battery (LIB) technology, metallic lithium anode is preferable to replace conventional ion intercalation anode materials because of the highest specific capacity (3,860 mAh/g) of lithium and the lowest negative electrochemical potential (∼3.040 V vs. the standard hydrogen electrode), which can maximize the capacity density and voltage window for increased battery energy density (1). Moreover, the success of beyond LIBs, such as lithium-sulfur and lithium-oxygen, will strongly rely on lithium metal anode designs with good stability to achieve their targeted goals of high energy density and long cycle life.Using lithium metal in organic liquid electrolyte systems faces many challenges in terms of battery performance and safety. For example, lithium-sulfur batteries suffer from the dissolution of intermediate polysulfides in the organic electrolyte that causes severe parasitic reactions on lithium metal surfaces, leading to lithium metal degradation and low lithium cycling efficiency (6). Lithium-oxygen batteries have the challenge of chemically instable liquid electrolytes on the oxygen electrode that cause limited battery cycling (7). All of these challenges are associated with the use of lithium metal in liquid electrolyte battery systems. Another major associated challenge is lithium dendrite growth on lithium metal anodes, which causes int...

Strategy to change the wettability of the solid-state electrolyte against Li and reduce interface resistance.

No abstract

The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 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 as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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 1 .