Lithium-sulfur(Li-S)batteries,known for their high energy density,are attracting extensive research interest as a promising next-generation energy storage ***,their widespread use has been hampered by certain issues,i...
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Lithium-sulfur(Li-S)batteries,known for their high energy density,are attracting extensive research interest as a promising next-generation energy storage ***,their widespread use has been hampered by certain issues,including the dissolution and migration of polysulfides,along with sluggish redox *** sulfides present a promising solution to these obstacles regarding their high electrical conductivity,strong chemical adsorption with polysulfides,and remarkable electrocatalytic capabilities for polysulfide *** this review,the recent progress on the utilization of metal sulfide for suppressing polysulfide shuttling in Li-S batteries is systematically summarized,with a special focus on sulfur hosts and functional *** critical roles of metal sulfides in realizing high-performing Li-S batteries have been comprehensively discussed by correlating the materials’structure and electrochemical ***,the remaining issues/challenges and future perspectives are *** offering a detailed understanding of the crucial roles of metal sulfides,this review dedicates to contributing valuable knowledge for the pursuit of high-efficiency Li-S batteries based on metal sulfides.
The 2D sandwich model serves as a potent tool in exploring the influence of surface geometry on the combustion attributes of Ammonium perchlorate/Hydroxyl-terminated polybutadiene(AP/HTPB)propellant under rapid pressu...
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The 2D sandwich model serves as a potent tool in exploring the influence of surface geometry on the combustion attributes of Ammonium perchlorate/Hydroxyl-terminated polybutadiene(AP/HTPB)propellant under rapid pressure *** thickness of the sandwich propellant is derived from slicing the 3D random particle packing,an approach that enables a more effective examination of the micro-flame *** analysis of the predicted burning characteristics has been performed with experimental *** findings demonstrate a reasonable agreement,thereby validating the precision and soundness of the *** on the typical rapid depressurization environment of solid rocket motor(initial combustion pressure is 3 MPa and the maximum depressurization rate is 1000 MPa/s).A-type(a flatter surface),B-type(AP recesses from the combustion surface),and C-type(AP protrudes from the combustion surface)propellant combustion processes are numerically *** comparison of the evolution of gas-phase flame between 0.1 and 1 ms,it is discerned that the flame strength and form created by the three sandwich models differ significantly at the beginning stage of depressurization,with the flame structures gradually becoming harmonized over *** are drawn by comparison extinction times:the surface geometry plays a pivotal role in the combustion process,with AP protrusion favoring combustion the most.
With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engi...
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With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engineering. As one of the high-precision representative algorithms, the high-order Discontinuous Galerkin Method (DGM) has not only attracted widespread attention from scholars in the CFD research community, but also received strong development. However, when DGM is extended to high-speed aerodynamic flow field calculations, non-physical numerical Gibbs oscillations near shock waves often significantly affect the numerical accuracy and even cause calculation failure. Data driven approaches based on machine learning techniques can be used to learn the characteristics of Gibbs noise, which motivates us to use it in high-speed DG applications. To achieve this goal, labeled data need to be generated in order to train the machine learning models. This paper proposes a new method for denoising modeling of Gibbs phenomenon using a machine learning technique, the zero-shot learning strategy, to eliminate acquiring large amounts of CFD data. The model adopts a graph convolutional network combined with graph attention mechanism to learn the denoising paradigm from synthetic Gibbs noise data and generalize to DGM numerical simulation data. Numerical simulation results show that the Gibbs denoising model proposed in this paper can suppress the numerical oscillation near shock waves in the high-order DGM. Our work automates the extension of DGM to high-speed aerodynamic flow field calculations with higher generalization and lower cost.
Nowadays, voice input on earphone sides has become one of the most paramount human-computer interaction approaches. However, airborne-channel input is noise-susceptible, decreasing the quality and intelligibility of i...
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Automatic modulation recognition-oriented Deep Neural Networks (ADNNs) have achieved higher recognition accuracy than traditional methods with less labor overhead. However, their high computation complexity usually fa...
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Live video streaming demands high user Quality of Experience (QoE) and requires significant computing power and bandwidth for video encoding and transmission. The standard adaptive live streaming approach encodes the ...
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The growing use of vectors for unstructured data has made efficient hybrid queries-combining boolean filters with vector similarity searches-essential. However, publicly available datasets for evaluating DBMS performa...
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Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a...
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Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a noncooperative *** this game theoretic framework,the optimal formation is achieved by seeking the Nash equilibrium of the regularized game.A modular structure consisting of a distributed Nash equilibrium seeker and a regulator is proposed.
The indiscriminate distribution of a large number of unlicensed images through the Internet seriously harms the benefits of image owners, which prompts the study of image copyright protection solutions. Existing block...
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Point cloud completion is crucial in point cloud processing, as it can repair and refine incomplete 3D data, ensuring more accurate models. However, current point cloud completion methods commonly face a challenge: th...
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