Rapid charging technology is increasingly needed, especially in the case of continuous energy consumption. Na superionic conductor (NASICON)-type materials are considered one of the most attractive candidates for lithium-ion batteries (LIBs) due to their multiple ionic channels and efficient kinetics. LiTi2(PO4)3 as a representative of the NASICON-type has been widely studied because of its own advantages. LiTi2(PO4)3's own poor electronic conductivity restricts its further development. Herein, Mo2C was used to decorate the external carbon layer of the LiTi2(PO4)3 to alleviate this problem. The excellent conductivity of Mo2C can enhance the concentration of electrons in the carbon layer and improve the Li+/e– conversion efficiency of electrodes. Therefore, the LiTi2(PO4)3/C@Mo2C composites displayed outstanding capacity retention of 86.8% after 4000 cycles under a high current density of 10 C, showing excellent and stable electrochemical performance. This work provides a fungible and convenient route for the hybrid of NASICON-type and carbon-layer materials as high-performance electrodes for Li-ion batteries.
Objective To explore that dynamic state of quantity of outside bod y parasitic fleas on Mormota hemanayana effect on marmot plague in Xishui area,S hunan country. Method We adopted surveillance method of marmot plague and evalua ted and analyzed effects of surveillance during 1982 to 2001. Result Annual cha nges of index marmot outside body parasitic fleas,especially cave fleas index ha ve positive correlation with the rate of checking out Y.pestis in local marmot p lague(P 0.01). Conclusion It has more important significance for marmot parasit ic fleas to have effects on marmot natural focuses of plague and keep nature of the natural focuses of plague and take care of Y.pestis for ever.
Proton transfer plays a crucial role in various chemical and biological processes. A major theoretical challenge in simulating proton transfer arises from the quantum nature of the proton. The constrained nuclear-electronic orbital (CNEO) framework was recently developed to efficiently and accurately account for nuclear quantum effects, particularly quantum nuclear delocalization effects, in quantum chemistry calculations and molecular dynamics simulations. In this paper, we systematically investigate challenging proton transfer modes in a series of shared-proton systems using CNEO density functional theory (CNEO-DFT), focusing on evaluating existing electron–proton correlation functionals. Our results show that CNEO-DFT accurately describes proton transfer vibrational modes and significantly outperforms conventional DFT. The inclusion of the epc17-2 electron–proton correlation functional in CNEO-DFT produces similar performance to that without electron–proton correlations, while the epc17-1 functional yields less accurate results, comparable with conventional DFT. These findings hold true for both asymmetrical and symmetrical shared-proton systems. Therefore, until a more accurate electron–proton correlation functional is developed, we currently recommend performing vibrational spectrum calculations using CNEO-DFT without electron–proton correlation functionals.
Vibrational spectroscopy is widely used to gain insights into structural and dynamic properties of chemical, biological and material systems. Thus, an efficient and accurate method to simulate vibrational spectra is desired. In this Letter, we propose a microcanonical molecular simulation scheme for efficient calculations of vibrational spectra. Within the new scheme, we perform constrained nuclear-electronic orbital molecular dynamics simulations and accurately predict vibrational spectra of three challenging water clusters: neutral water dimer (H4O2), protonated water trimer (H7O3+) and protonated water tetramer (H9O4+). We find that in addition to nuclear quantum effects, vibrational mode coupling effects are also crucial for the accurate description of the vibrational motions of these highly anharmonic hydrogen bonded systems, which accounts for the large discrepancy between the vibrational frequencies obtained from molecular simulations and harmonic analyses.
Traditional photonic systems are endowed with brand new properties owing to the addition of topological physics with light. A conjugated topological cavity-states (CTCS) in one-dimensional photonic systems is presented, which has not only robust light transport but also ultra-high performances, such as high quality factor (high-Q) and perfect transmission. This extraordinary CTCS can address the bottleneck of typical topological photonic systems, which can only achieve robust light transport without maintaining high performance. Furthermore, the CTCS is especially suitable for bio-photonic sensing with high resolution requirements. An ultra-sensitivity of 2000 nm/RIU and a high-Q of 109 for detecting the concentration of SARS-CoV-2 S-glycoprotein solution are obtained. Notably, the CTCS not only opens new possibilities for advanced photonics but also paves the way for high performance in topological photonic devices.
According to the problem of reservoired in Jiulong River basin,the judgment standard of reservoired river was determined,and the concept of integrate hydropower station was presented. Then,the parameter value of degradation coefficient K was calibrated with water quality model based on a large number of measured data of water quality. On this basis,calculation method of water environmental capacity for reservoired river was proposed. Finally,research was carried on water environmental capacity accounting of reservoired river in Jiulong River basin. The results show the effect of reservoired on water environmental capacity calculation,and the water environmental capacity of reservoired river,which provided scientific basis for the total emission control,management and decision-making of water environmental capacity in Jiulong River basin.
Abstract Near‐infrared (NIR) spectral information is important for detecting and analyzing material compositions. However, snapshot NIR spectral imaging systems still pose significant challenges owing to the lack of high‐performance NIR filters and bulky setups, preventing effective encoding and integration with mobile devices. This study introduces a snapshot spectral imaging system that employs a compact NIR metasurface featuring 25 distinct C 4 symmetry structures. Benefitting from the sufficient spectral variety and low correlation coefficient among these structures, center‐wavelength accuracy of 0.05 nm and full width at half maximum accuracy of 0.13 nm are realized. The system maintains good performance within an incident angle of 1°. A novel meta‐attention network prior iterative denoising reconstruction (MAN‐IDR) algorithm is developed to achieve high‐quality NIR spectral imaging. By leveraging the designed metasurface and MAN‐IDR, the NIR spectral images, exhibiting precise textures, minimal artifacts in the spatial dimension, and little crosstalk between spectral channels, are reconstructed from a single grayscale recording image. The proposed NIR metasurface and MAN‐IDR hold great promise for further integration with smartphones and drones, guaranteeing the adoption of NIR spectral imaging in real‐world scenarios such as aerospace, health diagnostics, and machine vision.
During the past decade, the model predictive control (MPC) of power electronics and drives has witnessed significant advancements in both dynamic performance and range of applications. However, researchers still encounter challenges with the optimal design of weighting factors, and this lowers the capabilities derivable from MPC. This study first reviews the different weighting factor design techniques proposed in the literature for power electronics and electrical drives (applied to wind/solar energy conversion, microgrids, grid-connected converters and other high performance converter-based systems). They are grouped under heuristic, offline tuning, sequential, and online optimization methods. Next, the study provides real-time hardware-in-the-loop comparative results for the implementation of four weighting factor design techniques on a grid-connected two-level back-to-back power converter-based permanent magnet synchronous generator wind turbine system. Through these laboratory results, the advantages and limitations of the different weighting factor design methods are highlighted.
Vibrational spectroscopy is widely used to gain insights into structural and dynamic properties of chemical, biological and material systems. Thus, an efficient and accurate method to simulate vibrational spectra is desired. In this paper, we justify and employ a microcanonical molecular simulation scheme to calculate the vibrational spectra of three challenging water clusters: the neutral water dimer (H4O2), the protonated water trimer (H7O3+), and the protonated water tetramer (H9O4+). We find that with the accurate description of quantum nuclear delocalization effects through the constrained nuclear-electronic orbital framework, including vibrational mode coupling effects through molecular dynamics simulations can additionally improve the vibrational spectrum calculations. In contrast, without the quantum nuclear delocalization picture, conventional ab initio molecular dynamics may even lead to less accurate results than harmonic analysis.
Power absorption resonances in microwave irradiated low-loss Al2O3 and high-loss SiC have been investigated by determining the normalized average power distribution in the sample slabs. For Al2O3, multiple resonance peaks initially occur at the position following a “half-wavelength (0.5/λm) rule”. As temperature increases, this rule becomes invalid due to the attenuation of microwaves with increased dielectric loss. For SiC, however, only one strong resonance peak is observed at the sample thickness of 0.33/λm. This indicates that only the sample having the size corresponding to resonance can obtain the maximum power absorption, considerably increasing the microwave heating efficiency.
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