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Unlocking high-efficiency oxygen evolution reaction through Co-N coordination engineering in Co@N-doped porous carbon core–shell nanoparticles

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Nano Research 2024年第8期17卷 7068-7076页

作者： Shucheng Liu Yu Shuai Xiaosi Qi Zhao Ding Yi Liu College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China College of Physics Guizhou Province Key Laboratory for Photoelectrics Technology and ApplicationGuizhou UniversityGuiyang 550025China

Modulation of metal sites coordination can significantly refine the electronic architecture of catalysts,thereby improving their catalytic *** work successfully developed a core–shell Co@N-doped porous carbon(Co@NC)catalyst by pyrolyzing the COF/MOF(IISERP-COF3/ZIF-67)composite in an inert *** Co@NC catalyst exhibited impressive oxygen evolution reaction(OER)performance,with a small overpotential of 304 mV and a modest Tafel slope of 88.6 mV·dec^(−1) in a 1 M KOH,alongside remarkable stability,maintaining 98.5%of its activity over 13 *** role of IISERP-COF3 was pivotal in preventing Co atom aggregation during the ZIF-67 pyrolysis,which facilitated the creation of mesopores for enhanced mass transport and ***,it effectively modulated the Co-N coordination to fine-tune the electronic structure,thereby optimizing the catalyst's capacity for adsorption of intermediates and boosting its intrinsic *** functional theory(DFT)studies corroborate that the exceptional OER efficiency of Co@NC can be linked to the enhanced Co-N coordination,optimizing the localized electronic structure at the Co active *** study not only proposes an innovative approach for optimizing COF/MOF as effective electrocatalysts but also clears the path for the emergence of affordable,high-performance alternatives to precious metal-based catalysts,marking a significant advancement in sustainable energy technologies.

关键词： covalent organic framework(COF) metal-organic framework(MOF) core-shell structure catalysts oxygen evolution reaction

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Spatiotemporal nonlinear dynamics in multimode fiber laser based on carbon nanotubes

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Frontiers of physics 2024年第5期19卷 179-184页

作者： Jingxuan Sun Yachen Wang Congyu Zhang Lijun Xu Bo Fu Key Laboratory of Precision Opto-Mechatronics Technology School of Instrumentation and Optoelectronic EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Big Data-Based Precision Medicine Ministry of Industry and Information TechnologySchool of Engineering MedicineBeihang UniversityBeijing 100191China

We investigated 1-μm multimode fiber laser based on carbon nanotubes,where multiple typical pulse states were observed,including Q-switched,Q-switched mode-locked,and spatiotemporal mode-locked ***,stable spatiotemporal mode-locking was realized with a low threshold,where the pulse duration was 37 ps and the wavelength was centred at 1060.5 ***,both the high signal to noise and long-term operation stability proved the reliability of the mode-locked ***,the evolution of the spatiotemporal mode-locked pulses in the cavity was also simulated and *** work exhibits the flexible outputs of spatiotemporal phenomena in multimode lasers based on nanomaterials,providing more possibilities for the development of high-dimensional nonlinear dynamics.

关键词： spatiotemporal mode-locking multimode fiber saturable absorber ultrafast laser

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OSE: On-Site State of Health Estimation for Li-ion Battery using Real-Time Field data

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7452-7462页

作者： Chen, Yanwen Zhao, Cong Yang, Shusen Zhao, Peng Ren, Xuebin Han, Qing Yang, Yuqian Wu, Shuaijun Xi'an Jiaotong University National Engineering Laboratory for Big Data Analytics Shaanxi Xi'an710049 China Xi'an Jiaotong University National Engineering Laboratory for Big Data Analytics The Ministry of Education Key Lab for Intelligent Networks and Network Security Shaanxi Xi'an710049 China

On-site lithium-ion battery state of health (SoH) estimation is of crucial importance for reliable operations of electric vehicles (EVs). Yet, due to the low-quality of unlabeled real-time field data, diverse operating environments of in-service EVs, and limited computational capability of onboard devices, existing techniques established on data from well-controlled experimental environments are not practical for real world EVs' SoH estimation. Accurate and rapid SoH estimation based on field data of in-service EVs still remains quite challenging. To tackle this challenge, we present an on-site SoH estimation (OSE) method using in-service EV field data through a new knowledge embedded deep transfer learning (DTL) model. Initially, an universal data preprocessing approach integrating mechanism knowledge is designed to process low-quality data under diverse operating environments. Then, we develop a domain adaptive hybrid deep neural network (DAHDNN) model suitable for unlabeled field data, which can be deployed via edge cloud collaborative framework to meet actual computational capability. We demonstrate the superiority of our method across four real datasets, where, OSE's estimation error is decreased by up to 78.5% compared with the state-of-the-art methods. The results indicate that the proposed method has good generalizability and reliability for SoH estimation on real-time field data. © 2015 IEEE.

关键词： State of charge

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Multicomponent Similarity Graphs for Cross-Network Node Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1411-1424页

作者： Zhang, Yuhong Shi, Congmei Li, Xinzheng Zhang, Zan Hu, Xuegang School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei230009 China

Cross-network node classification aims to train a classifier for an unlabeled target network using a source network with rich labels. In applications, the degree of nodes mostly conforms to the long-tail distribution, i.e., most nodes in the network are tail nodes with sparse neighborhoods. The established methods focus on either the discrepancy cross network or the long tail in a single network. As for the cross-network node classification under long tail, the coexistence of sparsity of tail nodes and the discrepancy cross-network challenges existing methods for long tail or methods for the cross-network node classification. To this end, a multicomponent similarity graphs for cross-network node classification (MS-CNC) is proposed in this article. Specifically, in order to address the sparsity of the tail nodes, multiple component similarity graphs, including attribute and structure similarity graphs, are constructed for each network to enrich the neighborhoods of the tail nodes and alleviate the long-tail phenomenon. Then, multiple representations are learned from the multiple similarity graphs separately. Based on the multicomponent representations, a two-level adversarial model is designed to address the distribution difference across networks. One level is used to learn the invariant representations cross network in view of structure and attribute components separately, and the other level is used to learn the invariant representations in view of the fused structure and attribute graphs. Extensive experimental results show that the MS-CNC outperforms the state-of-the-art methods. Impact Statement-Node classification is an important task in graph mining. With the unavailability of labels, some researchers propose cross-network node classification, using one labeled network to assist the node classification of another unlabeled network. However, the long-tail of nodes leads to unsatisfactory performance and challenges the recent cross-network node classification m

关键词： Graphic methods

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A level set model with shape prior constraint for intervertebral disc MRI image segmentation

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Multimedia Tools and Applications 2025年第9期84卷 6755-6783页

作者： Tian, Zhuangzhou Wang, Shengsheng College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

Accurate intervertebral disc image segmentation is necessary for further treatment. However, existing methods are difficult to segment due to the intensity inhomogeneity of intervertebral disc MRI images and the similarity in intensity between the intervertebral disc and the surrounding regions. This paper proposes a novel level set model by introducing a shape prior constraint for automatic and accurate segmentation. We utilize a detection model and intensity change to obtain rectangle prior information, which is used to define a shape constraint term. Then, combining data and regularizing terms construct an energy function and employ the steepest descent method minimization to get segmentation results. Finally, we apply the proposed new method to segment intervertebral disc images and get promising results. Extensive experiments and comparisons show that our model is more efficient and accurate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

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Online Streaming Features Causal Discovery Algorithm Based on Partial Rank Correlation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第1期4卷 197-208页

作者： Yang, Jing Jiang, Liufeng Shen, Anbo Wang, Aiguo Key Laboratory of Knowledge Engineering with Big Data of Ministry of Education Hefei University of Technology Hefei230009 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China School of Electronic and Information Engineering Foshan University Foshan528011 China

Aimedat the problem of dynamic causal discovery in the era of artificial intelligence, this article combines partial rank correlation coefficients and streaming features in the field of Bayesian network structure learning and proposes a new online streaming feature causal discovery algorithm based on partial rank correlation named the partial rank casual discovery streaming feature based algorithm. This algorithm is not only suitable for Bayesian causal structure learning in dynamic feature spaces generated by sequential streams of features but can also effectively process multivariate linear Gaussian and nonlinear non-Gaussian data. We present three main contributions. First, for arbitrarily distributed datasets, which can be generated by the additive noise model, we proved that the partial rank correlation coefficient can be used as the criterion for the conditional independence test and explored the distribution of corresponding statistics. Second, the PCSDSF algorithm redefined the relevance based on partial rank statistic prospects and then redefined conditional dependence or independence. This method can significantly reduce the number of conditional independence tests and achieves a good time performance. Finally, theoretical analysis and several experiments proved the reliability of the algorithm. A simulation showed that on average, the PCSDSF algorithm outperforms existing algorithms in terms of both the accuracy and time performance. © 2022 IEEE.

关键词： Additive noise

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Dissipation-Driven Superradiant Phase Transition of a Two-Dimensional Bose-Einstein Condensate in a Double Cavity

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Chinese Physics Letters 2024年第6期41卷 44-48页

作者： Bo-Hao Wu Xin-Xin Yang Yu Chen Wei Zhang Department of Physics and Beijing Key Laboratory of Opto-electronic Functional Materials and Micro-nano Devices Renmin University of ChinaBeijing 100872China Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education) Renmin University of ChinaBeijing 100872China Graduate School of China Academy of Engineering Physics Beijing 100193China Beijing Academy of Quantum Information Sciences Beijing 100193China

We study superradiant phase transitions in a hybrid system of a two-dimensional Bose–Einstein condensate of atoms and two cavities arranged with a tilt *** adjusting the loss rate of cavities,we map out the phase diagram of steady states within a mean field *** is found that when the loss rates of the two cavities are different,superradiant transitions may not occur at the same time in the two cavities.A first-order phase transition is observed between the states with only one cavity in superradiance and both in *** the case that both cavities are superradiant,a net photon current is observed flowing from the cavity with small decay rate to the one with large decay *** photon current shows a non-monotonic dependence on the loss rate difference,owing to the competition of photon number difference and cavity field phase *** findings can be realized and detected in experiments.

关键词： Einstein transitions decay

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FIR-YOLACT:Fusion of ICIoU and Res2Net for YOLACT on Real-Time Vehicle Instance Segmentation

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Computers, Materials & Continua 2023年第12期77卷 3551-3572页

作者： Wen Dong Ziyan Liu Mo Yang Ying Wu College of Big Data and Information Engineering Guizhou UniversityGuiyang550025China The State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China

Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving *** vehicle instance segmentation can perform instance-level semantic parsing of vehicle information,which is more accurate and reliable than object ***,the existing instance segmentation algorithms still have the problems of poor mask prediction accuracy and low detection ***,this paper proposes an advanced real-time instance segmentation model named FIR-YOLACT,which fuses the ICIoU(Improved Complete Intersection over Union)and Res2Net for the YOLACT ***,the ICIoU function can effectively solve the degradation problem of the original CIoU loss function,and improve the training convergence speed and detection *** Res2Net module fused with the ECA(Efficient Channel Attention)Net is added to the model’s backbone network,which improves the multi-scale detection capability and mask prediction ***,the Cluster NMS(Non-Maximum Suppression)algorithm is introduced in the model’s bounding box regression to enhance the performance of detecting similarly occluded *** experimental results demonstrate the superiority of FIR-YOLACT to the based methods and the effectiveness of all *** processing speed reaches 28 FPS,which meets the demands of real-time vehicle instance segmentation.

关键词： Instance segmentation real-time vehicle detection YOLACT Res2Net ICIoU

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Substantial grain refinement of Al-Mn-Si alloys me diate d by collaborative effect of Al-5Ti-1B refiner and sub-rapid solidification

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Journal of Materials Science & Technology 2024年第20期187卷 230-239页

作者： Yong-Si Wei Cheng Wang Jiang You Dong Qiu Yipeng Gao Hong Xu Jin Xu Hui-Yuan Wang Key Laboratory of Automobile Materials of Ministry of Education&School of Materials Science and Engineering Nanling CampusJilin UniversityNo.5988 Renmin StreetChangchun130025China Center for Additive Manufacturing School of EngineeringRMIT UniversityMelbourneVIC3001Australia State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Material Science and EngineeringHebei University of TechnologyTianjin300130China

The mechanical properties of as-cast metallic materials depend strongly on the size and shape of grains,which are critical microstructural parameters dictated by the interplay of nucleation and growth of crys-talline solids during *** our experiments,the microstructure transition from coarse colum-nar crystals into fine equiaxed crystals for dilute Al-Mn-Si alloys was achieved by using sub-rapid so-lidification with the addition of Al-5Ti-1B grain *** average grain size of Al alloy was reduced from a millimeter size to 73μ*** temperature gradient calculation,we found that the acqui-sition of fine equiaxed crystals could be attributed to the existence of a high number density of TiB2,acting as effective nucleation sites with an increase in total ***,the curvature su-percooling,constitutional undercooling,thermal undercooling,and kinetic undercooling during sub-rapid solidification were quantitatively determined for given solidification *** results showed that con-stitutional undercooling,rather than thermal undercooling,was primarily responsible for the formation of fine equiaxed grains,with the assistance of Al-5Ti-1B grain *** work provides a new insight into the grain refining mechanism under sub-rapid solidification.

关键词： Aluminum alloys Sub-rapid solidification Columnar-to-equiaxed transition Grain refinement

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Nano-scale Reinforcements and Properties of Al-Si-Cu Alloy Processed by High-Pressure Torsion

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Journal of Wuhan university of Technology(Materials Science) 2024年第5期39卷 1253-1259页

作者： DONG Ying WU Siyuan HE Ziyang LIANG Chen CHENG Feng HE Zuwei QIAN Chenhao School of Mechanical Engineering Jiangnan UniversityWuxi 214122China Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Wuxi 214122China School of International Studies Renmin University of ChinaBeijing 100872China School of Engineering University of LiverpoolLiverpool L693GHUnited Kingdom

To improve the comprehensive mechanical properties of Al-Si-Cu alloy,it was treated by a high-pressure torsion process,and the effect of the deformation degree on the microstructure and properties of the Al-Si-Cu alloy was *** results show that the reinforcements(β-Si andθ-CuAl_(2)phases)of the Al-Si-Cu alloy are dispersed in theα-Al matrix phase with finer phase size after the *** processed samples exhibit grain sizes in the submicron or even nanometer range,which effectively improves the mechanical properties of the *** hardness and strength of the deformed alloy are both significantly raised to 268 HV and 390.04 MPa by 10 turns HPT process,and the fracture morphology shows that the material gradually transits from brittle to plastic before and after *** elements interdiffusion at the interface between the phases has also been effectively *** addition,it is found that the severe plastic deformation at room temperature induces a ternary eutectic reaction,resulting in the formation of ternary Al+Si+CuAl_(2)eutectic.

关键词： Al-Si-Cu alloy high-pressure torsion nano-scale reinforcements ternary eutectic

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