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Interpretable machine learning for chiral induced symmetry breaking of spin density boosting hydrogen evolution

Journal of Energy Chemistry 2025年第4期103卷 68-78页

作者： Xin Song Zhonghua Li Li Sheng Yang Liu School of Chemistry and Chemical Engineering Key Laboratory of Microsystems and Microstructures Manufacturing Ministry of Education Harbin Institute of Technology School of Computer Science and Technology Harbin Institute of Technology

The integration of machine learning and electrocatalysis presents nota ble advancements in designing and predicting the performance of chiral materials for hydrogen evolution reactions（HER）.This study utilizes theoretical calculations and machine learning techniques to assess the HER performance of both chiral and achiral M-N-SWCNTs（M=In,Bi,and Sb） single-atom catalysts（SACs）.The stability preferences of metal atoms are dependent on chirality when interacting with chiral *** HER activity of the right-handed In-N-SWCNT is 5.71 times greater than its achiral counterpart,whereas the left-handed In-N-SWCNT exhibits a 5.12-fold *** calculated hydrogen adsorption free energy for the right-handed In-N-SWCNT reaches as low as-0.02 *** enhancement is attributed to the symmetry breaking in spin density distribution,transitioning from C2Vin achiral SACs to C2in chiral SACs,which facilitates active site transfer and enhances local spin ***-handed M-N-SWCNTs exhibit superior α-electron separation and transport efficiency relative to left-handed variants,owing to the chiral induced spin selectivity（CISS） effect,with spin-up α-electron density reaching 3.43 × 10-3e/Bohr3at active *** learning provides deeper insights,revealing that the interplay of weak spatial electronic effects and appropriate curvature-chirality effects significantly enhances HER performance.A weaker spatial electronic effect correlates with higher HER activity,larger exchange current density,and higher turnover *** curvature-chirality effect undersco res the influence of intrinsic structures on HER *** findings offer critical insights into the role of chirality in electrocatalysis and propose innovative approaches for optimizing HER through chirality.

关键词： CISS DFT Hydrogen evolution reaction Machine learning Spin density Symmetry breaking

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An electron-transfer-tuning strategy at the graphene/metal interface for improving acidic water electrolysis in proton exchange membrane electrolyzers

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Journal of Energy Chemistry 2025年第4期103卷 344-352页

作者： Yue Xu Shuaidong Li Yingjian He Fumiya Shiokawa Samuel Jeong Aimi Asilah Haji Tajuddin Zeyu Xi Yoshikazu Ito Jingzi Zhang Zeyun Cai Xi Lin Kailong Hu School of Materials Science and Engineering and Institute of Materials Genome & Big Data Harbin Institute of Technology Institute of Applied Physics Graduate School of Pure and Applied Sciences University of Tsukuba Institute of Special Environments Physical Sciences Harbin Institute of Technology School of Computer Science and Technology Harbin Institute of Technology

Graphene encapsulation has been shown to be an effective technique for improving the corrosion resistance of non-noble metal catalysts for the acidic water *** key challenge lies in enhancing the electrocatalytic activity of graphene-encapsulated metals while maintaining their durability in acidic ***,an electron-transfer-tuning strategy is investigated at the graphene/NiMo interface,aiming to improve the hydrogen evolution reaction（HER） performance of graphene-encapsulated NiMo *** doping of Ti,a low electronegativity element,into NiMo substrate was confirmed to increase electron transfer from the metal core toward the *** electron-rich state on graphene facilitates the adsorption of positively charged protons on graphene,thereby enabling a Pt/C-comparable performance in 0.5 M H2SO4,with only a 3.8% degradation in performance over a 120-h continuous *** proton exchange membrane（PEM） water electrolyzer assembled by the N-doped grapheneencapsulated Ti-doped NiMo exhibits a smaller cell voltage to achieve a current density of 2.0 A cm-2,in comparison to the Pt/C based *** study proposes a novel electron-transfer-tuning strategy to improve the HER activity of graphene-encapsulated non-noble metal catalysts without sacrificing durability in acidic electrolytes.

关键词： Acidic media Graphene encapsulation Hydrogen evolution Interface Proton exchange membrane

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Research Progress in Solar Flare Prediction Methods

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Research in Astronomy and Astrophysics 2025年第3期25卷 280-309页

作者： Ke Han Zhen Liu Xian-Yi Zhao Yi-Fei Li De-Quan Zheng Jie Wan School of Computer and Information Engineering Harbin University of Commerce Faculty of Computing Harbin Institute of Technology School of Energy Science and Engineering Harbin Institute of Technology

Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.

关键词： (Sun:) sunspots magnetohydrodynamics (MHD) Sun: activity Sun: flares Sun: magnetic fields

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PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

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Chinese Journal of Electronics 2025年第1期34卷 82-97页

作者： Hongchen Guo Weilin Gan Mingyang Zhao Chuan Zhang Tong Wu Liehuang Zhu Jingfeng Xue School of Computer Science and Technology Beijing Institute of Technology School of Cyberspace Science and Technology Beijing Institute of Technology School of Computer and Communication Engineering University of Science and Technology Beijing

Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O（n） communication and storage overhead compared to prior O（n2） schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10× efficiency improvement of searching and 100× lower communication and storage overhead on average compared with existing schemes.

关键词： Resistance Access control Data privacy Dictionaries Blockchains Encryption Complexity theory Usability Protection

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Gradient-based attitude planning for rigid spacecraft on SO(3)

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science China Technological sciences 2025年第5期68卷 167-178页

作者： Tao HUO Jin YANG Chengfei YUE Xueqin CHEN Xibin CAO School of Astronautics Harbin Institute of Technology School of Management Harbin Institute of Technology State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster Harbin Institute of Technology School of Aerospace Science Harbin Institute of Technology Shenzhen

Attitude planning of rigid bodies has many applications in robotics and aerospace. However, because the attitude configuration space is non-Euclidean and the constraints are complex and non-linear, the design of the attitude curve has always been a tricky problem. In this paper, a gradient-based attitude planning method is proposed to simultaneously handle attitude pointing, angular velocity, torque, and time constraints on Lie group SO(3). Firstly, the attitude interpolation algorithm on SO(3) gives an attitude curve connecting the initial and target attitudes. The shape of the curve is determined by the fitting coefficients and maneuvering time. Secondly, to match the curve with suitable angular velocity and control torque, a nonlinear planning model with fitting coefficients and maneuver time as decision variables is proposed. Solving the problem gives a smooth attitude curve that satisfies both kinematic and dynamic constraints and also avoids complicated time allocation. Then, to apply the gradientbased solver, analytical formulas for the derivatives of each order of the attitude curve with respect to the decision variables are given in this paper. Finally, the effectiveness of the proposed algorithm is verified by a series of numerical simulations.

关键词： attitude planning attitude constraints gradient optimization three-dimensional special orthogonal group (SO(3))

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Efect of Solution and Aging Treatment on Microstructure and Mechanical Properties of Al-14Si-5Cu-1.1Mg-2.3Ni-0.3La Alloy

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Acta Metallurgica Sinica(English Letters) 2025年第3期38卷 449-464页

作者： Jian Dong Jufu Jiang Ying Wang Minjie Huang Jingbo Cui Tao Song School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China

In this study,the efects of diferent heat treatment process parameters on the microstructure and mechanical properties of Al-12Si-5Cu-1.1Mg-2.3Ni-0.3La alloy were *** showed that eutectic Si underwent three stages during solution treatment:difusing,spheroidization and *** the solution temperature and time increased,the size of eutectic Si showed a trend of frst decreasing and then *** with the heat treatment time,the heat treatment temperature had a more signifcant efect on the mechanical *** coarsening of microstructure was the main reason for the deterioration of mechanical *** Al_(3)Ti and Al_(3)CuNiLa in the microstructure after aging can signifcantly improve the mechanical properties of the *** Al_(11)La_(3) with secondary precipitation occurred in the La-rich *** addition of La inhibited the growth of coherent/semi-coherentθandβphases,which was very benefcial for the improvement of high-temperature *** the optimal heat treatment process parameters of 500℃×4 h+190℃×4 h,the ultimate tensile strength(UTS)of the alloy reached 366.65 *** high-temperature strength and elongation of the alloy reached 101.98 MPa and 13.77%at 350℃,respectively.

关键词： Al-14Si-5Cu-1.1Mg-2.3Ni-0.3La alloy Heat treatment process Microstructure High-temperature mechanical properties

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Efficient Maximum Vertex(k,ℓ)-Biplex Computation on Bipartite Graphs

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Tsinghua science and technology 2025年第2期30卷 569-584页

作者： Hongru Zhou Shengxin Liu Ruidi Cao School of Computer Science and Technology Harbin Institute of TechnologyShenzhen 518055China Science and Technology Office Harbin Institute of TechnologyShenzhen 518055China

Cohesive subgraph search is a fundamental problem in bipartite graph *** integers k andℓ,a(k,ℓ)-biplex is a cohesive structure which requires each vertex to disconnect at most k orℓvertices in the other ***(k,ℓ)-biplexes has been a popular research topic in recent years and has various ***,most existing studies considered the problem of finding(k,ℓ)-biplex with the largest number of *** this paper,we instead consider another variant and focus on the maximum vertex(k,ℓ)-biplex problem which aims to search for a(k,ℓ)-biplex with the maximum *** first show that this problem is Non-deterministic Polynomial-time hard(NP-hard)for any positive integers k andℓwhile max{k,ℓ}is at least *** by this negative result,we design an efficient branch-and-bound algorithm with a novel *** particular,we introduce a branching strategy based on whether there is a pivot in the current set,with which our proposed algorithm has the time complexity ofγ^(n)n^(O(1)),whereγ<*** addition,we also apply multiple speed-up techniques and various pruning ***,we conduct extensive experiments on various real datasets which demonstrate the efficiency of our proposed algorithm in terms of running time.

关键词： bipartite graphs cohesive subgraph search maximum vertex(k,ℓ)-biplex branch-and-bound algorithm

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Multi-scale dispersion strengthening for high-temperature titanium alloys:Strength preservation and softening mechanisms

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材料科学技术（英文版） 2025年第3期206卷 1-14页

作者： Xin Chen Lujun Huang Shuo Ma Fengbo Sun Shuai Wang Lin Geng School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China

The long-lasting expectation"the hotter the engine,the better"calls for the development of high-temperature metallic *** the high specific strengths of titanium alloys are compelling for such applications,their deleterious softening beyond 600 ℃ imposes serious *** has been known for decades regarding the phase metallurgy for precipitation strengthening design in titanium al-loys,however,the other facile strength promotion mechanism,dispersion strengthening,remains compar-atively less-explored and *** present research concerns the multi-scale dispersion strength-ening in titanium alloys,with mechanistic emphases on the critical plasticity micro-events that affect strength *** to the simultaneous introduction of intragranular dispersoids and intergran-ular reinforcers,the current titanium alloys present superior engineering tensile strength of 519 MPa at 700 ℃.Throughout the examined 25-800 ℃ temperature range,noticeable softening induced by the ther-mal activation occurs above 600 ℃,accompanied by evident strength *** temperature-dependence transition of dominated softening mechanisms from dynamic recovery to dynamic recrystallization has been clarified by theoretical ***,the strengthening effect of multi-scale architec-tures is underpinned as the enhanced dislocation strengthening owing to the introduction of thermally-stable heterointerfaces,which could generically guide the design of similar heat-resistant titanium alloys.

关键词： Titanium-based alloys Multi-scale architectures Mechanical properties Temperature dependence Dislocation strengthening

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A Software Defect Prediction Method Using a Multivariate Heterogeneous Hybrid Deep Learning Algorithm

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computers, Materials & Continua 2025年第2期82卷 3251-3279页

作者： Qi Fei Haojun Hu Guisheng Yin Zhian Sun College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China Information Technology Research Department Jiangsu Automation Research InstituteLianyungang222062China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen518055China

Software defect prediction plays a critical role in software development and quality assurance processes. Effective defect prediction enables testers to accurately prioritize testing efforts and enhance defect detection efficiency. Additionally, this technology provides developers with a means to quickly identify errors, thereby improving software robustness and overall quality. However, current research in software defect prediction often faces challenges, such as relying on a single data source or failing to adequately account for the characteristics of multiple coexisting data sources. This approach may overlook the differences and potential value of various data sources, affecting the accuracy and generalization performance of prediction results. To address this issue, this study proposes a multivariate heterogeneous hybrid deep learning algorithm for defect prediction (DP-MHHDL). Initially, Abstract Syntax Tree (AST), Code Dependency Network (CDN), and code static quality metrics are extracted from source code files and used as inputs to ensure data diversity. Subsequently, for the three types of heterogeneous data, the study employs a graph convolutional network optimization model based on adjacency and spatial topologies, a Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) hybrid neural network model, and a TabNet model to extract data features. These features are then concatenated and processed through a fully connected neural network for defect prediction. Finally, the proposed framework is evaluated using ten promise defect repository projects, and performance is assessed with three metrics: F1, Area under the curve (AUC), and Matthews correlation coefficient (MCC). The experimental results demonstrate that the proposed algorithm outperforms existing methods, offering a novel solution for software defect prediction.

关键词： Software defect prediction multiple heterogeneous data graph convolutional network models based on adjacency and spatial topologies CNN-BiLSTM TabNet

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Study on enhanced heat transfer and performance improvement of a pumped hydro compressed air energy storage system

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science China(Technological sciences) 2025年第4期68卷 34-48页

作者： Biao YANG Deyou LI Huibin WANG Chuanchao WANG Xiaolong FU Hongjie WANG School of Energy Science and Engineering Harbin Institute of TechnologyHarbin150001China

In pumped hydro compressed air energy storage systems,the heat exchange performance between air and water significantly affects the thermodynamic *** study proposes an enhanced heat transfer method by adding trays and investigates the effects of parameters such as the number of trays,tray diameter,and tray mounting ***,the working principle of the heat transfer method when adding trays was clarified,and a mathematical model was ***,the effects of the number,diameter,and mounting height of the trays were ***,the thermodynamic,energy,and exergy performances of the system without trays,Tank 1 with trays,Tank 2 with trays,and Tanks 1 and 2 with trays were *** results show that the heat transfer between air and water is enhanced and the variation in air temperature is reduced when Tanks 1 and 2 have *** number and diameter of trays significantly affected the thermodynamic performance of the system,whereas the impact of the tray mounting height was not *** installing 30 trays uniformly in Tanks 1 and 2,the temperature variations in Tanks 1 and 2 were reduced by 8.2%and 15.4%,respectively;additionally,the round-trip and exergy efficiencies of the system were improved by 1.4%and 1.3%,respectively.

关键词： pumped hydro compressed air heat transfer enhancement thermodynamic analysis energy analysis exergy analysis

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