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Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

Nano-Micro Letters 2025年第1期17卷 361-377页

作者： Feng He Sitong Chen Ruili Zhou hanyu Diao Yangyang han Xiaodong Wu School of Mechanical Engineering Sichuan UniversityChengdu 610065People’s Republic of China School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065People’s Republic of China State Key Laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065People’s Republic of China

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced *** to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static ***,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic ***,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential *** controllable and reversible polarization process of the conjugated polymers is fully in situ ***,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference *** with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior *** demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning *** tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

关键词： Passive tactile sensors Reversible polarization of conjugated polymers Tactile perception Machine learning algorithm Object recognition

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The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao han Yi-Yang Guo He Wang Minghui Du hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

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Performance Analysis of a Coupled System based on Organic Rankine Cycle and Double Effect Absorption Refrigeration for Waste Heat Recovery in Data Center

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Journal of Thermal Science 2025年第1期34卷 188-205页

作者： LI Peng XU Jiaqi WANG Binbin LIU Jianyang ZHAO Wensheng han Zhonghe School of Energy Power and Mechanical Engineering North China Electric Power University Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation Technology North China Electric Power University

During data center operation,it generates a significant volume of low-grade waste *** recover waste heat,a coupled system including solar collector,double effect absorption refrigeration and organic Rankine cycle is *** system performance is analyzed in *** the organic Rankine cycle,five organic working fluids(R245fa,R245ca,R123,R11,and R113) are selected.R245fa,R113 and R245ca obtain the maximum net power output,thermal efficiency and exergy efficiency,*** the double effect absorption refrigeration system,the evaporation temperature,condensation temperature,and generation pressure affect the COP and exergy *** the generator pressure is unchanged,the COP increases with increasing evaporation temperature and decreasing condensation *** the COP reaches 1.3,the COP slightly decreases as the evaporation temperature or condensation temperature ***,the exergy efficiency of refrigeration systems exhibits the same trend as the COP,and the exergy efficiency maximum value appears at approximately 0.32.A new performance indicator,rPUE,was defined to evaluate the data center power utilization *** flow distribution ratio and heat source temperature were optimized with multi-objective *** the mass flow distribution rate is 0.6 and the heat source temperature is 441.5 K,rPUE and the total unit production costs of the system obtain the optimal solution.

关键词： Exergy

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Multi-Stage Voltage Control Optimization Strategy for Distribution Networks Considering Active-Reactive Co-Regulation of Electric Vehicles

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Energy Engineering 2025年第1期122卷 221-242页

作者： Shukang Lyu Fei Zeng Huachun han HuiyuMiao Yi Pan Xiaodong Yuan Electric Power Research Institute State Grid Jiangsu Electric Power Co.Ltd.Nanjing211103China

The high proportion of uncertain distributed power sources and the access to large-scale random electric vehicle(EV)charging resources further aggravate the voltage fluctuation of the distribution network,and the existing research has not deeply explored the EV active-reactive synergistic regulating characteristics,and failed to realize themulti-timescale synergistic control with other regulatingmeans,For this reason,this paper proposes amultilevel linkage coordinated optimization strategy to reduce the voltage deviation of the distribution ***,a capacitor bank reactive power compensation voltage control model and a distributed photovoltaic(PV)activereactive power regulationmodel are ***,an external characteristicmodel of EVactive-reactive power regulation is developed considering the four-quadrant operational characteristics of the *** optimization model of the distribution network is then constructed considering the time-series coupling constraints of multiple types of voltage regulators.A multi-timescale control strategy is proposed by considering the impact of voltage regulators on active-reactive EV energy consumption and PV energy ***,a four-stage voltage control optimization strategy is proposed for various types of voltage regulators with multiple time ***-objective optimization is solved with the improvedDrosophila algorithmto realize the power fluctuation control of the distribution network and themulti-stage voltage control *** results validate that the proposed voltage control optimization strategy achieves the coordinated control of decentralized voltage control resources in the distribution *** effectively reduces the voltage deviation of the distribution network while ensuring the energy demand of EV users and enhancing the stability and economic efficiency of the distribution network.

关键词： Electric vehicle(EV) distribution network multi-stage optimization active-reactive power regulation voltage control

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Catalytic Performance of Carbon Smoke over Ag-LSCF Composite Catalysts

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 30-34页

作者： GUO Guanlun han Ming LU Shaomin YU Jing JU Hongling 无 Hubei Key Laboratory of Advanced Technology for Automotive Components&Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of TechnologyWuhan 430070China College of Mechanical and Transportation Southwest Forestry UniversityKunming 650000China

To improve the catalytic performance of La_(0.6)Sr_(0.4)Co_(0.2)Fe_(0.8)O_(3)(LSCF)towards carbon soot,we utilized the impregnation method to incorporate Ag into the prepared LSCF *** conducted a series of characterization tests and evaluated the soot catalytic activity of the composite catalyst by comparing it with the LaCoO_(3) group,LaFeO_(3) group,and catalyst-free *** results indicate that the Ag-LSCF composite catalyst exhibits the highest soot catalytic activity,with the characteristic temperature values of 376.3,431.1,and 473.9℃at 10%,50%,and 90%carbon soot conversion,*** values are 24.8,20.2,and 23.1℃lower than those of the LSCF *** also shows that LSCF can improve the catalytic activity of soot after compounding with Ag,and reflects the necessity of using catalysts in soot combustion *** characterization and BET test show that Ag-LSCF has more abundant surface-adsorbed oxygen species,larger specific surface area and pore volume than LSCF,which also proves that Ag-LSCF has higher soot catalytic activity.

关键词： metallic composites carbon smoke oxidation perovskite catalyst soot

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Deep eutectic solvents for separation and purification applications in critical metal metallurgy:Recent advances and perspectives

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 1-19页

作者： Shuo Chen Shengpeng Su Yanfang Huang Bingbing Liu Hu Sun Shuzhen Yang Guihong han School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China Zhongyuan Critical Metals Laboratory Henan ProvinceZhengzhou 450001China

Solvent extraction,a separation and purification technology,is crucial in critical metal *** solvents commonly used in solvent extraction exhibit disadvantages,such as high volatility,high toxicity,and flammability,causing a spectrum of hazards to human health and environmental *** solvents have been recognized as potential alternatives to these harmful organic *** the past two decades,several neoteric solvents have been proposed,including ionic liquids(ILs)and deep eutectic solvents(DESs).DESs have gradually become the focus of green solvents owing to several advantages,namely,low toxicity,degradability,and low *** this critical review,their classification,formation mechanisms,preparation methods,characterization technologies,and special physicochemical properties based on the most recent advancements in research have been systematically ***,the major separation and purification applications of DESs in critical metal metallurgy were comprehensively ***,future opportunities and challenges of DESs were explored in the current research *** conclusion,this review provides valuable insights for improving our overall understanding of DESs,and it holds important potential for expanding separation and purification applications in critical metal metallurgy.

关键词： deep eutectic solvents preparations properties separation and purification critical metal metallurgy

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Microstructural evolution during the progressive transformation-induced plasticity effect in a Fe-0.1C-5Mnmedium manganese steel

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 369-379页

作者： Mei Zhang Wenhao Li Yangfei Chen Yang Jiang Xiaofei Guo han Dong School of Materials Science and Engineering Shanghai UniversityShanghai 200444China State Key Laboratory of Advanced Special Steel Shanghai UniversityShanghai 200444China

The microstructural evolution of a cold-rolled and intercritical annealed medium-Mn steel(Fe-0.10C-5Mn)was investigated during uniaxial tensile ***-situ observations under scanning electron microscopy,transmission electron microscopy,and X-ray diffraction analysis were conducted to characterize the progressive transformation-induced plasticity process and associated fracture initiation *** findings were discussed with the local strain measurements via digital image *** results indicated that Lüders band formation in the steel was limited to 1.5%strain,which was mainly due to the early-stage martensitic phase transformation of a very small amount of the less stable large-sized retained austenite(RA),which led to localized stress concentrations and strain hardening and further retardation of *** small-sized RA exhibited high stability and progressively transformed into martensite and contributed to a stably extended Portevin-Le Chatelier *** volume fraction of RA gradually decreased from 26.8%to 8.2%prior to *** the late deformation stage,fracture initiation primarily occurred at the austenite/martensite and ferrite/martensite interfaces and the ferrite phase.

关键词： medium-Mn steel retained austenite progressive transformation-induced plasticity effect local strain fracture initiation

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FK506 contributes to peripheral nerve regeneration by inhibiting neuroinflammatory responses and promoting neuron survival

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Neural Regeneration Research 2025年第7期20卷 2108-2115页

作者： Yuhui Kou Zongxue Jin Yusong Yuan Bo Ma Wenyong Xie Na han Department of Trauma and Orthopedics Peking University People’s HospitalBeijingChina National Center for Trauma Medicine Peking University People’s HospitalBeijingChina Key Laboratory of Trauma and Neural Regeneration(Peking University) Ministry of EducationBeijingChina Trauma Medicine Center Peking University People’s HospitalBeijingChina Department of Orthopedics China-Japan Friendship HospitalBeijingChina

FK506(Tacrolimus)is a systemic immunosuppressant approved by the *** and Drug ***506 has been shown to promote peripheral nerve regeneration,however,its precise mechanism of action and its pathways remain *** this study,we established a rat model of sciatic nerve injury and found that FK506 improved the morphology of the injured sciatic nerve,increased the numbers of motor and sensory neurons,reduced inflammatory responses,markedly improved the conduction function of the injured nerve,and promoted motor function *** findings suggest that FK506 promotes peripheral nerve structure recovery and functional regeneration by reducing the intensity of inflammation after neuronal injury and increasing the number of surviving neurons.

关键词： FK506 inflammation motor neurons nerve regeneration neuron peripheral nerve injury sensory neurons

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Experimental Study on Energy Storage Characteristics of Sintered Ore Particle Packed Beds

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Journal of Thermal Science 2025年第1期34卷 242-253页

作者： LAI Zhenya DING Liwei LYU Hongkun HOU Chenglong CHEN Jiaying GUO Xutao han Gaoyan ZhanG Kang State Grid Zhejiang Electric Power Research Institute State Key Laboratory of Clean Energy Utilization Zhejiang University

The particle packed bed energy storage system has advantages such as low costs and wide temperature ranges,which can be combined with solar thermal power generation systems to solve the inherent volatility and discontinuity of renewable *** new materials with low costs and excellent storage performances is one of the eternal research hotspots in the field of energy *** paper innovatively uses sintered ore particles as energy storage material and studies the effect of particle size on the airflow resistance characteristics,energy storage characteristics,and thermocline evolution characteristics of the packed bed through thermal energy storage *** results indicate that for the particles in the macro scale,the smaller the particle,the lower the absolute permeability of the bed and the greater the airflow *** packed bed with smaller particles has a larger specific surface area,larger bulk mass,and smaller bed ***,the packed beds with smaller particles have better thermocline characteristics,less irreversible loss,and can achieve higher thermal efficiency and higher exergy efficiency in the heat storage *** cycle thermal efficiency in packed beds with 25-40 mm,16-25 mm,and 10-16 mm particles is 53.58%,56.27%,and 57.60%,respectively,and the cycle exergy efficiency is 61.81%,69.25%,and 74.13%,***,this paper also studies the effect of discharging airflow rates on thermal storage *** experimental results indicate that suitable discharging strategies should be selected based on different heat demands.

关键词： airflow resistance particle packed bed thermal energy storage thermocline evolution

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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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