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Fluorinated poly(p-triphenylene isatin) anion exchange membranes based on hydrophilic hydroxyl side chain modulation for fuel cells

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Journal of Energy Chemistry 2025年第1期100卷 702-709页

作者： Yiman Gu Yanchao Zhang Zhanyu Li Yijia Lei Baozeng sun Xiaoyu Yu Zhe Wang College of Chemistry and Life Science Changchun University of Technology College of Chemical Engineering Changchun University of Technology School of Materials Science and Engineering Changchun University of Technology Key Laboratory of Advanced Functional Polymer Membrane Materials of Jilin Province

The development of alkaline fuel cells is moving forward at an accelerated pace,and the application of ether-free bonded polymers to anion exchange membranes （AEMs） has been widely ***,the question of the“trade-off”between AEM ionic conductivity and dimensional stability remains *** strategy of inducing microphase separation to improve the performance of AEM has attracted much attention recently,but the design of optimal molecular structures is still being ***,this work introduced different ratios of 3-bromo-1,1,1-trifluoroacetone （x=40,50,and 60） into the main chain of poly（p-terphenylene isatin）.Because fluorinated groups have excellent hydrophobicity,hydrophilic hydroxyl-containing side chains are introduced to jointly adjust the formation of phase separation *** results show that PTI-PTF50-NOH AEM with the appropriate fluorinated group ratio has the best ionic conductivity and alkali stability under the combined effect of *** has an ionic conductivity of 133.83 mS cm-1at 80°*** addition,the OH-conductivity remains at 89%of the initial value at 80°C and 3 M KOH for 1056 h of *** cell polarization curve based on PTI-PTF50-NOH shows a power density of 734.76 mW cm-2at a current density of 1807.7 mA cm-2.

关键词： Potassium hydroxide

Recent advances of metal vacancies in energy and environmental catalysis:Synthesis,characterization,and roles

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Green Energy & Environment 2025年第1期10卷 84-108页

作者： Long sun Shunzheng Zhao Sirui Gao Ronghui Zhu Yiran Tan Xiaolong Tang Honghong Yi School of Energy and Environmental Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants Beijing100083China

With the ongoing depletion of fossil fuels,energy and environmental issues have become increasingly critical,necessitating the search for effective ***,being one of the hallmarks of modern industry,offers a promising avenue for ***,the question of how to significantly enhance the performance of catalysts has gradually drawn the attention of *** engineering,a commonly employed and effective approach to improve catalyst activity,has become a significant research focus in the catalysis field in recent *** vacancies have received extensive attention due to their simple ***,exploration of metal vacancies has remained stagnant for a considerable period,resulting in a scarcity of comprehensive reviews on this ***,based on the latest research findings,this paper summarizes and consolidates the construction strategies for metal vacancies,characterization techniques,and their roles in typical energy and environmental catalytic ***,it outlines potential challenges in the future,aiming to provide valuable references for researchers interested in investigating metal vacancies.

关键词： Metal vacancies Catalysis Construction strategies Characterization techniques Roles

Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

A Novel Model for Describing Rail Weld Irregularities and Predicting Wheel-Rail Forces Using a Machine Learning Approach

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 555-577页

作者： Linlin sun Zihui Wang Shukun Cui Ziquan Yan Weiping Hu Qingchun Meng State Key Laboratory of High-Speed Railway Track System China Academy of Railway Sciences Corporation LimitedBeijing100081China Railway Engineering Research Institute China Academy of Railway Sciences Corporation LimitedBeijing100081China School of Aeronautic Science and Engineering Beihang UniversityBeijing100191China

Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed *** can cause significant wheel-rail dynamic interactions,leading to wheel-rail noise,component damage,and *** researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry ***,the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric *** this study,novel theoretical models were developed for three categories of rail weld irregularities,based on measurements of the high-speed railway from Beijing to *** vertical dynamic forces in the time and frequency domains were compared under different running *** forces generated by the rail weld irregularities that were measured and modeled,respectively,were compared to validate the accuracy of the proposed ***,based on the numerical study,the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network(ANN),and the optimum combination of parameters for this model is *** results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the *** ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time.

关键词： Rail weld irregularity high-speed railway vehicle-track coupled dynamics wheel/rail dynamic vertical force artificial neural networks

A Cross Attention Transformer-Mixed Feedback Video Recommendation Algorithm Based on DIEN

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Computers, Materials & Continua 2025年第1期82卷 977-996页

作者： Jianwei Zhang Zhishang Zhao Zengyu Cai Yuan Feng Liang Zhu Yahui sun College of Software Engineering Zhengzhou University of Light IndustryZhengzhou450000China Faculty of Information Engineering Xuchang Vocational Technical CollegeXuchang461000China College of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450000China College of Electronics and Information Zhengzhou University of Light IndustryZhengzhou450000China

The rapid development of short video platforms poses new challenges for traditional recommendation *** systems typically depend on two types of user behavior feedback to construct user interest profiles:explicit feedback(interactive behavior),which significantly influences users’short-term interests,and implicit feedback(viewing time),which substantially affects their long-term ***,the previous model fails to distinguish between these two feedback methods,leading it to predict only the overall preferences of users based on extensive historical behavior ***,it cannot differentiate between users’long-term and shortterm interests,resulting in low accuracy in describing users’interest states and predicting the evolution of their *** paper introduces a video recommendationmodel calledCAT-MFRec(CrossAttention Transformer-Mixed Feedback Recommendation)designed to differentiate between explicit and implicit user feedback within the DIEN(Deep Interest Evolution Network)*** study emphasizes the separate learning of the two types of behavioral feedback,effectively integrating them through the cross-attention ***,it leverages the long sequence dependence capabilities of Transformer technology to accurately construct user interest profiles and predict the evolution of user *** results indicate that CAT-MF Rec significantly outperforms existing recommendation methods across various performance *** advancement offers new theoretical and practical insights for the development of video recommendations,particularly in addressing complex and dynamic user behavior patterns.

关键词： Video recommendation user interest cross-attention transformer

Fractal autoencoder with redundancy regularization for unsupervised feature selection

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Science China(Information Sciences) 2025年

作者： Meiting sun Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Institute of Artificial Intelligence(Beijing)

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder (RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

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Molecular dynamics simulation of quartz deformation under slow earthquake background

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Science China Earth Sciences 2025年

作者： Jingxian sun Qianqian GUO Quanlin HOU College of Earth and Planetary Sciences University of Chinese Academy of Sciences Key Laboratory of Computational Geodynamics CAS

Slow earthquakes are the primary mechanism of slow energy release, and research on the focal mechanism has been inconclusive. Studies have primarily focused on the friction law based on physical mechanisms and have suggested that slow earthquakes are caused by brittle faults. However, the focal strength and structural characteristics of slow earthquakes in subduction zones provide evidence of plastic deformation. What is the role of plastic deformation in the focal mechanisms of slow earthquakes? Mechanochemical study have shown that mechanical forces can directly affect chemical bonds. In this study,we examine the storage and release of chemical energy during plastic deformation and consider a mechanochemical process in the focal mechanism of slow earthquakes. Combined with the Tersoff potential, molecular dynamics simulation on the shear deformation process of two α-quartz crystals show that the shear modulus of α-quartz is 18 GPa, and that the crystal model primarily exhibits atoms flowing and changing in the direction of chemical bonds during the steady-state flow stage. The molecular potential energy and stress vary in an oscillating up-and-down curve during shear, indicating that chemical energy can be stored and released during plastic deformation. This is consistent with the energy variation during slow earthquakes. Under the initial simple-shear loading condition, α-quartz crystals undergo general shear deformation instead of plane strain and the angle between the longest instantaneous stretching axis （ISA1） and the shearing direction is approximately 30°, not 45°. Both the deformation type and direction of ISA1are contrary to basic deformation theory, which may provide clues for future *** study reveals the process of quartz elastic-plastic shear deformation on an atomic scale. This information is useful for understanding focal mechanisms of slow earthquakes. This study is part of a series of investigations on tectonic stress chemistry.

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Investigations of liquid-liquid transitions in metallic melts by fast differential scanning calorimetry

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Science China(Physics,Mechanics & Astronomy) 2025年

作者： Qi Cheng Yonghao sun Weihua Wang Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular Engineering Peking University School of Physics and Electronic Information Anhui Normal University Institute of Physics Chinese Academy of Sciences Songshan Lake Materials Lab

Liquid-liquid transition in metallic melts is an intriguing phenomenon often confused with liquid-liquid separation, oxidation or precipitation. Here, we employ a state-of-the-art ultrafast chip-based differential scanning calorimeter to investigate the thermal behavior of six metallic melts, ranging from unary to quinary systems, at temperatures above their liquidus. Calorimetric signals of liquid-liquid transition vary across systems: Sn melts showed no direct endothermic or exothermic events, though liquid-liquid transition influenced solidification and melting temperatures, while Yb-Zn melts exhibited an exothermic peak during cooling,indicating liquid-liquid transition. Thermal signals in other systems including Li, Pd-Ni-P, Yb-Mg-Zn-Cu and Au-Ag-Pd-Cu-Si,are primarily driven by compositional changes. Our in-situ analysis provides new insights into the structural and compositional evolution of metallic melts, offering significant implications for the design and processing of novel materials.

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创新公立医院多学科联合会诊服务供给模式

中国医院 2017年第8期21卷 42-44页

作者：李琴孙爱娟龚力谭明英杨利龙婷四川大学华西医院成都市武侯区国学巷37号610041

目的:为推进分级医疗,更好地履行国家对公立医院的功能定位,提高医院多学科联合会诊服务工作。方法:对医院2013-2015年多学科联合会诊服务中心2331例患者信息,采用卡方检验及趋势卡方检验进行资料分析,总结医院创新多学科联合会诊服务... 详细信息

目的:为推进分级医疗,更好地履行国家对公立医院的功能定位,提高医院多学科联合会诊服务工作。方法:对医院2013-2015年多学科联合会诊服务中心2331例患者信息,采用卡方检验及趋势卡方检验进行资料分析,总结医院创新多学科联合会诊服务供给模式,会诊后通过随访疗效及满意度评价。结果:3年中医院多学科联合门诊患者数呈逐年增加势态,不同年度多学科会诊患者的年龄分布差异有统计学意义(χ~2=22.57,P=0.001)。申请多学科联合门诊目的:要求明确诊断664例(28.5%);诊断已明确寻求治疗方案1667例(71.5%)。会诊后随访治疗效果:痊愈418例(17.9%);好转1473例(63.2%);无明显改善123例(5.3%);死亡37例(1.6%);失去随访280例(12.0%)。医院多学科联合会诊中心病种数量逐年增加,且不同年度间多学科联合门诊病种数量差异有统计学意义(χ~2=746.44,P<0.001)。不同年度患者对多学科联合会诊的满意度差异有统计学意义,并呈逐年上升趋势,从2013年的90.1%增加到2015年的97.1%(χ~2=30.51,P_(fortrend)<0.001)。结论:优化多学科联合会诊服务供给模式,有效推动了双向转诊、分级诊疗和区域医疗协作;拓展了医院疑难重症医疗、教学和科学研究工作。

关键词：公立医院多学科联合会诊供给模式分级诊疗

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