The global market of flexible/printed and organic electronics is about 41 billion dollars in 2020, which is expected to reach over 74 billion dollars in 2030 according to the relevant reports by IDTechEx. [3] As for the development and expansion toward practical application, flexible/wearable electronics urgently request for flexible energy sources and power devices with high specific energy density and long lifetime. During the past decade, a variety of flexible energy harvesting/conversion (e.g., solar cells, nanogenerators) and energy storage devices (e.g., batteries, supercapacitors, hybrid batteries) have dedicatedly progressed and gained ongoing recognition for future wearable applications. [4][5][6] Among those promising renewable energy technologies, rechargeable lithium-ion batteries (LIBs) have received widespread adoptions for power supplies ranging from mobile/portable electronics to plug-in/ hybrid electric vehicles because of their high working voltage, appreciable energy density, easy use, and ecofriendliness. [7] Flexible LIBs became one of the potential options for powering flexible electronics. With further advance, flexible LIBs are plagued by their limited energy density, deficient safety, and relatively high cost of electrode materials (e.g., lithium, cobalt). In this case, alternative battery technologies, especially metal-air batteries gain immense attention (Table 1). [8,9] Metal-air batteries (MABs) own 2-10 times higher specific energy than current LIBs (200-250 Wh kg −1 ) due to the direct utilization of oxygen from the atmosphere within a halfopen device system. Alongside, rechargeable MABs have more freedom in metallic anodes such as lithium, sodium, potassium, zinc, aluminum and magnesium, etc., where the latter three-based MABs are compatible with aqueous alkaline electrolytes and also intrigued numerous interest. [10][11][12] Given the high theoretical specific energy (1218 Wh kg −1 , 6136 Wh L −1 ), low fabrication cost, high operational safety and environmental benignancy, aqueous zinc-air batteries (ZABs) show far more practical prospect for new-generation energy storage sources. [11] Figure 1 illustrates the brief chronology of the development of ZABs. Dating back to 1878, the first The strong propulsion stem from flexible/wearable electronics has greatly stimulated the development of miniaturized and high-performance rechargeable batteries with adaptable shape. Flexible zinc-air batteries (FZABs), which exhibit high theoretical energy density (1218 Wh kg −1 ), low cost, environmental benignancy, and admirable operational safety, have been widely recognized as one of the promising portable powers to serve future wearable electronics for ubiquitous application. During the past five years, the energy/ power density and cycling stability of FZABs have gained significant improvement largely due to the rational construction of high-efficiency bifunctional air electrodes. Herein, the recent progress of integrated binder-free bifunctional oxygen electrodes is overviewed via elaborate ...
Nonetheless, the sluggish oxygen reduction/evolution reaction (ORR/OER) involving multi-step electron transfer at the multiphase interfaces of the airbreathing cathode deleteriously impact the energy efficiency and lifespan of ZABs with limited energy/power output. [4] Until now, noble-metal-based catalysts, that is, Pt/C and IrO 2 or RuO 2 , still stand out as the benchmark catalysts for ORR and OER, respectively, though the rare reserve and chemical susceptibility severely hinder their large-scale application. [5] Indeed, tremendous efforts have been made on the exploitation of proficient earth-abundant transition-metal based bifunctional oxygen catalysts, such as oxides, hydroxides, phosphides, sulfides, nitrides, etc., so as to activate the OER/ORR electrochemistry. [6][7][8][9] Unfortunately, ideal non-precious electrocatalysts with satisfactory bifunctional activities, robust durability, and appropriate structure for unobstructive mass transport are still very scarce. [10] Among diverse non-precious electrocatalysts, nanosized and atomically dispersed metallic Co-based catalysts have intrigued numerous recognition by virtue of the rich valence states for high OER activity, electrochemical stability, and abundance of cobalt resources. [11][12][13] By further conjugation with an N-doped carbon matrix to tune the coordination configuration between Co and N heteroatoms, the electronic structure of Co sites can be effectively optimized for more balanced adsorption of oxo-intermediates and improved ORR activity. [14][15][16] However, the formation of homogeneous and sufficient Co-N x active moieties is generally difficult, as the metallic loading in these Co-N-C catalysts is always restricted due to the high tendency of self-agglomeration and irreversible fusion of cobalt nanoparticles (NPs) during common pyrolysis synthesis. [17,18] By taking advantage of high specific surface area, excellent conductivity, and mechanical strength, heteroatoms-doped 2D nanocarbon could be useful to support and well distribute Co NPs for more exposed active sites, directional electron transfer and accelerated mass diffusion across the interspaces between the carbon nanosheets (CNSs), thus boosting the reversible oxygen reactions. [19,20] Besides, feasible strategies, including morphological control, heterostructure, surface reconfiguration, and interface
To suppress the mid-high-frequency error of small optical tungsten carbide aspheric molds, it is proposed to quickly select the critical process parameters by simulating the residual error after convolution of the tool influence function (TIF). After polishing for 10.47 min by the TIF, two simulation optimizations, RMS and Ra, converge to 9.3 and 5.347 nm, respectively. Their convergence rates are improved by 40% and 7.9%, respectively, compared to ordinary TIF. Then, a faster and more high-quality multi-tool combination smoothing suppression method is proposed, and the corresponding polishing tools are designed. Finally, the global Ra of the aspheric surface converges from 5.9 to 4.5 nm after smoothing for 5.5 min with a disc-shaped polishing tool with a fine microstructure and maintains an excellent low-frequency error (PV 0.0781 µm).
This paper uses supervised machine learning (sentiment analysis) to analyze the sentiments of social media information in the P2P lending market. After segmentation, filtering, feature word extraction, and model training of the text information captured by Python, the sentiments of media and social media information were calculated to examine the effect of media and social media sentiments on default probability and cost of capital of peer-to-peer (P2P) lending platforms in China (2015–2019). We find that only positive changes in media and social media sentiment have significantly negative effects on the platform’s default probability and cost of capital, while negative changes in sentiment do not have any effects. We conclude the existence of an asymmetric effect of media and social media sentiments in the Chinese peer-to-peer lending market.
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