Lithium (Li) deposition and nucleation at solid electrolyte interphase (SEI) is the main origin for the capacity decay in Li metal batteries (LMBs).SEI conversion with enhanced electrochemical and mechanical pro...
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Lithium (Li) deposition and nucleation at solid electrolyte interphase (SEI) is the main origin for the capacity decay in Li metal batteries (LMBs).SEI conversion with enhanced electrochemical and mechanical properties is an effective approach to achieve uniform nucleation of Li+and stabilize the lithium metal ***,complex interfacial reaction mechanisms and interface compatibility issues hinder the development of SEI conversion strategies for stabilizing lithium metal ***,we presented the release of I3-in–NH2-modified metal–organic frameworks for a Li metal surface SEI phase conversion ***–NH2group in MOF pores induced the formation of I3-from I2,which was further spontaneously reacted with inactive Li2O transforming into high-performance LiI and ***,theoretical calculation provided deeply insight into the unique reconstructed interfacial formation and electrochemical mechanism of rich LiI and *** a result,the Li+deposition and nucleation were improved,facilitating the transport kinetics of Li+and inhibiting the growth of lithium *** assembled solid-state Li||LiFePO4full cells exhibited superior long-term stability of 800 cycles and high Coulombic efficiency (>99%),Li||LiNi0.8Co0.1Mn0.1O2pouch cell also displayed superior practical performance over 200 cycles at 2 C,high loading of 5 mg cm-2and safety *** innovative SEI design strategy promotes the development of high-performance solid-state Li metal batteries.
Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure ...
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Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure of KGs for *** EA models are designed for rich-resource languages,requiring sufficient resources such as a parallel corpus and pre-trained language ***,low-resource language KGs have received less attention,and current models demonstrate poor performance on those low-resource ***,researchers have fused relation information and attributes for entity representations to enhance the entity alignment performance,but the relation semantics are often *** address these issues,we propose a novel Semantic-aware Graph Neural Network(SGNN)for entity ***,we generate pseudo sentences according to the relation triples and produce representations using pre-trained ***,our approach explores semantic information from the connected relations by a graph neural *** model captures expanded feature information from *** results using three low-resource languages demonstrate that our proposed SGNN approach out performs better than state-of-the-art alignment methods on three proposed datasets and three public datasets.
Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so...
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Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.
Infrared images have been widely used in military, civilian, and industrial fields. Due to the inherent limitations of sensors, infrared images usually have some disadvantages such as low resolution and blurred textur...
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In recent years, with the rapid development of deep learning technology, researchers in the field of network security have begun to explore the use of deep learning to solve the problem of encrypted traffic classifica...
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Deep learning models are widely used in security-sensitive tasks such as facial recognition and autonomous driving. Security issues in deep models could have serious implications for people’s lives, such as life-thre...
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Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its t...
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Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.
Multi-material additive manufacturing(MMAM)takes full advantage of the ability to arbitrarily place materials of addi-tive manufacturing technology,enabling immense design free-dom and functional print *** MMAM techno...
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Multi-material additive manufacturing(MMAM)takes full advantage of the ability to arbitrarily place materials of addi-tive manufacturing technology,enabling immense design free-dom and functional print *** MMAM technologies,projection stereolithography(PSL)exhibits a great balance of high resolution and fast printing ***,fabrication accuracy of multi-material PSL is hin-dered by large overcure used to strengthen interfacial bond-ing weakened by chemical affinity and material-exchange *** present a novel multi-step exposure method for multi-material PSL process to overcome this ***,the whole layer is moderately exposed producing over-cure of single-material PSL level to generate *** weakened interfaces are strengthened individually with addi-tional steps of *** multi-step exposure is integrated into the already efficient materials printing order of multi-material PSL *** depth and overcure of photocur-able resins are modeled and *** required to achieve sufficient interfacial bonding of single-material interfaces built through material-exchange process and multi-material interfaces with altering materials printing order is determined with tensile *** channels are used to compare fabrication accuracy of traditional single-step exposure and our multi-step exposure *** method can be widely applied in multi-material PSL to improve fabri-cation accuracy in a variety of applications including micro-fluidic devices.
Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequenc...
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Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone ***,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent ***,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the *** experiment performed on a radar receiver confirms the reliability of the method proposed in this *** shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity *** on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.
In the time of Internet of Things(IoT),alternating current electroluminescence(ACEL)has unique advantages in the fields of smart display and human–computer ***,their reliance on external high-voltage AC power supplie...
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In the time of Internet of Things(IoT),alternating current electroluminescence(ACEL)has unique advantages in the fields of smart display and human–computer ***,their reliance on external high-voltage AC power supplies poses challenges in terms of wearability and limits their practical *** paper proposed an innovative scheme for preparing a feather triboelectric nanogenerator(F-TENG)using recyclable and environmentally friendly *** highest open-circuit voltage,short-circuit current,and transferred charge of SF6-treated F-TENGs can reach 449 V,63μA,and 152 nC,which enables easy lighting of BaTiO_(3)^(-)doped ACEL *** a human electrical potential,a single-electrode F-TENG is combined with ACEL device for self-powered fingerprint recognition *** works achieve self-powered flexible wearable ACEL devices,which are not only efficient and portable but also have good application prospects in the human–computer interaction,functional displays,and wearable electronic devices.
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