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Tin-based materials with high specific capacity have been studied as high-performance anodes for energy storage devices. Herein, a SnO x (x = 0, 1, 2) quantum dots@carbon hybrid is designed and prepared by a binary oxide-induced surface-targeted coating of ZIF-8 followed by pyrolysis approach, in which SnO x quantum dots (under 5 nm) are dispersed uniformly throughout the nitrogen-containing carbon nanocage. Each nanocage is cross-linked to form a highly conductive framework. The resulting SnO x @C hybrid exhibits a large BET surface area of 598 m2 g–1, high electrical conductivity, and excellent ion diffusion rate. When applied to LIBs, the SnO x @C reveals an ultrahigh reversible capacity of 1824 mAh g–1 at a current density of 0.2 A g–1, and superior capacities of 1408 and 850 mAh g–1 even at high rates of 2 and 5 A g–1, respectively. The full cell assembled using LiFePO4 as cathode exhibits the high energy density and power density of 335 Wh kg–1 and 575 W kg–1 at 1 C based on the total active mass of cathode and anode. Combined with in situ XRD analysis, the superior electrochemical performance can be attributed to the SnO x -ZnO-C asynchronous and united lithium storage mechanism, which is formed by the well-designed multifeatured construction composed of SnO x quantum dots, interconnected carbon network, and uniformly dispersed ZnO nanoparticles. Importantly, this designed synthesis can be extended for the fabrication of other electrode materials by simply changing the binary oxide precursor to obtain the desired active component or modulating the type of MOFs coating to achieve high-performance LIBs.

Optimization of the cathode structure and exploration of a novel electrolyte system are important approaches for achieving high-performance zinc-ion batteries (ZIBs) and zinc dendrite suppression. Herein, a quasi-solid-state ZIB combining a sandwich-like MnO 2 @rGO cathode, a laponite (Lap)-modified polyacrylamide (PAM) hydrogel electrolyte, and an electrodeposited zinc anode is designed and constructed by a synergistic optimization strategy. The MnO 2 composite prepared through the intercalation of rGO shows developed mesopores, providing accessible ion transport channels and exhibiting a high electrical conductivity. Thanks to the high dispersion of Lap nanoplates in the hydrogel and good charge-averaging effect, the Zn//PAM-5% Lap//Zn symmetrical battery exhibits a consistent low-voltage polarization of less than 60 mV within 2000 h without a short-circuit phenomenon or any over-potential rise, indicating a stable zinc peeling/plating process. The optimized quasi-solid-state ZIB delivers a high reversible capacity of 291 mA h g −1 at a current density of 0.2 A g −1 due to the synergistic effect of each component of ZIB. Even at a high rate of 2 A g −1 , it still maintains a high reversible capacity of 97 mA h g −1 after 2000 cycles, indicating its excellent electrochemical performance. Furthermore, the assembled flexible battery performs excellently in terms of damage and bending resistance.

High-energy rechargeable Li-metal batteries require safer and more reliable electrolyte systems because of the dendrite growth caused by the organic liquid electrolytes. Polymer electrolytes with both high electrochemical and mechanical properties are expected, although they are challenging to prepare. Herein, a novel gel polymer electrolyte (GPE) based on poly(vinylidene fluoride) (PVDF) has been fabricated by introducing laponite nanoplates via a facile solution-casting method. The composite GPE shows a high ion conductivity and mechanical strength. When applied to LIBs with LiFePO 4 as cathode, the battery exhibits a high capacity of 157 mA h g −1 at 0.2 C with an excellent initial Coulombic efficiency of 95%. After 1000 cycles, the capacity retention is as high as 97%. Remarkably, a superior capacity of 111 mA h g −1 is still maintained at a high rate of 10 C. This result provides a way to design a high-performance electrolyte and flexible devices.

With the rapid development of remote sensing technology, satellite remote sensing images have been involved in many areas of people’s lives. Remote sensing images contain military secrets, land profiles, and other sensitive data, so it is urgent to encrypt remote sensing images. This paper proposes a dual-channel key transmission model. The plaintext related key is embedded into the ciphertext image through bit-level key hiding transmission strategy, which enhanced the ability of ciphertext image to resist known-plaintext attack and chosen plaintext attack. In addition, a multiband remote sensing image encryption algorithm based on Boolean cross-scrambling and semi-tensor product diffusion is designed. Firstly, the pixel positions of each band of the remote sensing image are disturbed. Then, the random sequence generated by the four-dimensional chaotic system is processed and deformed to obtain a Boolean matrix. Based on the generated Boolean matrix and certain rules, the cross-confusion between the bands is carried out. Finally, the semi-tensor product operation is used in the diffusion process. Simulation results and experimental analysis show that the proposed algorithm obtains a larger key space and has stronger antiattack ability than other remote sensing image encryption algorithms. It can meet the security transmission of multiband remote sensing image in open space.

In this paper, a hyperchaotic four-dimensional fractional discrete Hopfield neural network system (4D-FDHNN) with four positive Lyapunov exponents is proposed. Firstly, the chaotic dynamics’ characteristics of the system are verified by analyzing and comparing the iterative trajectory diagram, phase diagram, attractor diagram, 0-1 test, sample entropy, and Lyapunov exponent. Furthermore, a novel image encryption scheme is designed to use the chaotic system as a pseudo-random number generator. In the scenario, the confusion phase using the fractal idea proposes a fractal-like model scrambling method, effectively enhancing the complexity and security of the confusion. For the advanced diffusion phase, we proposed a kind of Hilbert dynamic random diffusion method, synchronously changing the size and location of the pixel values, which improves the efficiency of the encryption algorithm. Finally, simulation results and security analysis experiments show that the proposed encryption algorithm has good efficiency and high security, and can resist common types of attacks.

Abstract:The leaf area index (LAI) is one of the most important Earth surface parameters used in the modeling of ecosystems and their interaction with climate. Numerous vegetation indices have been developed to estimate the LAI. However, because of the effects of the bi-directional reflectance distribution function (BRDF), most of these vegetation indices are also sensitive to the effect of BRDF. In this study, we aim to present a new BRDF-resistant vegetation index (BRVI), which is sensitive to the LAI but insensitive to the effect of BRDF. Firstly, the BRDF effects of different bands were investigated using both simulated data and in-situ measurements of winter wheat made at different growth stages. We found bi-directional shape similarity in the solar principal plane between the green and the near-infrared (NIR) bands and between the blue and red bands for farmland soil conditions and with medium chlorophyll content level. Secondly, the consistency of the shape of the BRDF across different bands was employed to develop a new BRDF-resistant vegetation index for estimating the LAI. The reflectance ratios of the NIR band to the green band and the blue band to the red band were reasonably assumed to be resistant to the BRDF effects. Nevertheless, the variation amplitude of the bi-directional reflectance in the solar principal plane was different for different bands. The divisors in the two reflectance ratios were improved by combining the reflectances at the red and green bands. The new BRVI was defined as a normalized combination of the two improved reflectance ratios. Finally, the potential of the proposed BRVI for estimation of the LAI was evaluated using both simulated data and in-situ measurements and also compared to other popular vegetation indices. The results showed that the influence of the BRDF on the BRVI was the weakest and that the BRVI retrieved LAI values well, with a coefficient of determination (R 2 ) of 0.84 and an RMSE of 0.83 for the field data and with an R 2 of 0.97 and an RMSE of 0.25 for the simulated data. It was concluded, therefore, that the new BRVI is resistant to BRDF effect and is also promising for use in estimating the LAI.

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