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Green Energy & Environment 2024年第8期9卷 1199-1219页

作者： Cheng Qi tao zhou Xingjiang Wu Kailang Liu Lei Li zhou Liu Zhuo Chen Jianhong Xu Tiantian Kong Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen University The State Key Laboratory of Chemical Engineering Department of Chemical EngineeringTsinghua University College of Chemistry and Environmental Engineering Shenzhen University Department of Biomedical Engineering School of MedicineShenzhen University

Multiphase microfluidic has emerged as a powerful platform to produce novel materials with tailor-designed functionalities, as microfluidic fabrication provides precise controls over the size, component, and structure of resultant materials. Recently, functional materials with welldefined micro-/nanostructures fabricated by microfluidics find important applications as environmental and energy materials. This review first illustrated in detail how different structures or shapes of droplet and jet templates are formed by typical configurations of microfluidic channel networks and multiphase flow systems. Subsequently, recent progresses on several representative energy and environmental applications, such as water purification, water collecting and energy storage, were overviewed. Finally, it is envisioned that integrating microfluidics and other novel materials will play increasing important role in contributing environmental remediation and energy storage in near future.

关键词： Microfluidics Multi-phase flow Droplet and microfiber Environmental remediation Energy Storage

Unlocking supercapacitive energy storage potential:Catalyzing electrochemically inactive manganese oxides to active MnO_(2)via heterostructure reconstruction

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Nano Research 2024年第7期17卷 5897-5906页

作者： Baohong Zhang tao Jiang Xinyan zhou Xiaoyu Fan Binbin Jia Lidong Li School of Chemistry Beihang UniversityBeijing 100191China College of Materials and Chemical Engineering Key Laboratory of Inorganic Nonmetallic Crystalline and Energy Conversion MaterialsChinaThree Gorges UniversityYichang 443002China Chinese Academy of Sciences(CAS)Key Laboratory of Nanosystem and Hierarchy Fabrication CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing 100190China Shanghai GTX Semiconductor Co. Ltd.Shanghai 201806China

Advancing supercapacitor system performance hinges on the innovation of novel electrode materials seamlessly integrated within distinct ***,we introduce a direct approach for crafting nanorod arrays featuring crystalline/amorphous CuO/MnO_(2)−*** reconfigured heterostructure results in an elevated content of electrochemically active MnO_(2).The nanorod arrays serve as efficient capacitive anodes and are easily prepared via low-potential electrochemical *** resulting structure spontaneously forms a p–n heterojunction,developing a built-in electric field that dramatically facilitates the charge transport *** intrinsic electric field,in conjunction with the crystalline/amorphous architecture,enables a large capacitance of 1.0 F·cm^(−2)at 1.0 mA·cm^(−2),an ultrahigh rate capability of approximately 85.4%at 15 mA·cm^(−2),and stable cycling performance with 92.4%retention after 10,000 *** calculations reveal that the presence of heterojunctions allows for the optimization of the electronic structure of this composite,leading to improved conductivity and optimized OH−adsorption *** work provides new insights into the rational design of heterogeneous nanostructures,which hold great potential in energy storage applications.

关键词： reconfiguration active MnO_(2) crystalline/amorphous structure p-n heterojunction supercapacitor

Vegetation changes across the Eocene-Oligocene transition:Global signals *** development

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Science China Earth Sciences 2024年第9期67卷 2937-2952页

作者： Mengxiao WU Lutz KUNZMANN Shufeng LI Vasilis TEODORIDIS Zhekun zhou tao SU CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMengla 666303China Senckenberg Natural History Collections Dresden Konigsbrücker LandstraBe 159Dresden 01109Germany Department of Biology and Environmental Studies Faculty of EducationCharles UniversityMagdalény Rettigové411639 Prague 1Czech Republic State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of TechnologyChengdu 610059China Institute of Sedimentary Geology Chengdu University of TechnologyChengdu 610059China

The Eocene-Oligocene transition(EOT)marked a rapid global cooling event,often considered as the beginning of the modern icehouse *** by various factors,including tectonic activity and paleogeographic settings,the terrestrial records indicate a diverse response of fauna and vegetation to this global *** examined nine macrofossil assemblages from seven fossil localities on the southeastern margin of the Tibetan Plateau and from the mid-latitudinal Europe ranging from the latest Bartonian and Priabonian(37.71-33.9 Ma)to the Rupelian(33.9-27.82 Ma).Our aims were to trace and compare the vegetation history of both regions in the late Eocene and early *** results show that both regions experienced changes in vegetation composition in response to climate change,characterized by a decrease in the percentages of broad-leaved evergreen elements and distinctive changes in general vegetation types.A general change in the overall vegetation type from subtropical broad-leaved evergreen forests in the late Eocene to temperate broad-leaved mixed deciduous evergreen forests,or mixed mesophytic forests,in the early Oligocene is recognized in both *** results indicate a clear change in leaf architecture,leaf margin states,and secondary venation types in the mid-latitudinal Europe,while the results from the southeastern margin of the Tibetan Plateau show a distinct reduction in leaf *** data suggest that both global and regional factors played key roles in shaping the vegetation in the two regions.

关键词： Eocene-Oligocene transition Plant fossil Paleoclimate Leaf architecture Biodiversity

Application of a neural network model with multimodal fusion for fluorescence spectroscopy

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NUCLEAR SCIENCE AND TECHNIQUES 2024年第10期35卷 1-14页

作者： Tang, Lin zhou, Shuang Shi, Kai-Bo Shen, Hong-tao You, Lei Chengdu Univ Coll Elect Informat & Elect Engn Chengdu 610106 Peoples R China Guangxi Normal Univ Guangxi Key Lab Nucl Phys & Nucl Technol Guilin 541004 Peoples R China Anhui Univ Natl Engn Res Ctr Agroecol Big Data Anal & Applica Hefei 230039 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Panzhihua Univ Vanadium & Titanium Resource Comprehens Utilizat K Panzhihua 617000 Peoples R China Chengdu Normal Univ Inst Higher Educ Sichuan Prov Key Lab Interior Layout Optimizat & Secur Chengdu 611130 Peoples R China

In energy-dispersive X-ray fluorescence spectroscopy, the estimation of the pulse amplitude determines the accuracy of the spectrum measurement. The error generated by the amplitude estimation of the pulse output distorted by the measurement system leads to false peaks in the measured spectrum. To eliminate these false peaks and achieve an accurate estimation of the distorted pulse amplitude, a composite neural network model is proposed, which embeds long and short-term memory (LSTM) into the UNet structure. The UNet network realizes the fusion of pulse sequence features and the LSTM model realizes pulse amplitude estimation. The model is trained using simulated pulse datasets with different amplitudes and distortion times. For the pulse height estimation, the average relative error of the trained model on the test set was approximately 0.64%, which is 27.37% lower than that of the traditional trapezoidal shaping algorithm. Offline processing of a standard iron source further validated the pulse height estimation performance of the UNet-LSTM model. After estimating the amplitude of the distorted pulses using the model, the false peak area was reduced by approximately 91% over the full spectrum and was corrected to the characteristic peak region of interest (ROI). The corrected peak area accounted for approximately 1.32% of the characteristic peak ROI area. The results indicate that the model can accurately estimate the height of distorted pulses and has substantial corrective effects on false peaks.

关键词： UNet Long- and short-term memory Pulse distortion Pulse height estimation Fluorescent spectroscopy

Prediction of Coefficient of Restitution for Impact Elastoplastic Spheres Considering Finite Plate Thickness

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Chinese Journal of Mechanical Engineering 2024年第4期37卷 183-193页

作者： Yunfeng Fan Hao Wang tao zhou Limin Zou Zhinong Jiang Minghui Hu State Key Laboratory of High-end Compressor and System Technology Beijing University of Chemical TechnologyBeijing 100029China China Ship Research and Development Academy Beijing 100101China Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory of High-End Mechanical Equipment Health Monitoring and Self-Recovery Beijing University of Chemical TechnologyBeijing 100029China

Collisions between objects are a relatively common phenomenon in *** of collision processes can greatly contribute to solving problems such as impact-rub faults and particle *** coefficient of restitution is a critical parameter in the analysis of collision *** experiments have shown that the coefficient of restitution is closely related to the plate thickness,and the smaller the plate thickness,the more inaccurate the coefficient of restitution predicted by the existing model,which seriously affects the process of collision *** remedy this shortcoming,this paper proposes a plate thickness influence factor with the ratio of sphere diameter to plate thickness as the *** plate thickness influence factor can optimize the coefficient of restitution model to effectively predict the coefficient of restitution of impacting elastoplastic spheres with finite plate ***,the validity of the new model is verified using a large amount of experimental data.

关键词： Collision Coefficient of restitution Energy loss Sphere

Clustering for Bivariate Functional Data

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 613-629页

作者： Shi-yun CAO Yan-qiu zhou Yan-ling WAN tao ZHANG School of Science Guangxi University of Science and TechnologyLiuzhou 545006China School of Marxism Guangxi University of Science and TechnologyLiuzhou 545006China Key Laboratory of Intelligent Information Processing and Graph Processing Guangxi University of Science and TechnologyLiuzhou 545006China

In this paper,we consider the clustering of bivariate functional data where each random surface consists of a set of curves recorded repeatedly for each *** k-centres surface clustering method based on marginal functional principal component analysis is proposed for the bivariate functional data,and a novel clustering criterion is presented where both the random surface and its partial derivative function in two directions are *** addition,we also consider two other clustering methods,k-centres surface clustering methods based on product functional principal component analysis or double functional principal component *** results indicate that the proposed methods have a nice performance in terms of both the correct classification rate and the adjusted rand *** approaches are further illustrated through empirical analysis of human mortality data.

关键词： bivariate functional data -centres surface clustering functional principal component analysis partial derivative function

Spatial differences of Sustainable Development Goals(SDGs)among counties(cities)on the northern slope of the Kunlun Mountains

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Regional Sustainability 2024年第1期5卷 1-10页

作者： WANG tao zhou Daojing FAN Jie School of Economics and Management University of Chinese Academy of SciencesBeijing100190China Xinjiang Arts University Urumqi830049China Institutes of Science and Development Chinese Academy of SciencesBeijing100190China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing100101China

The county(city)located on the northern slope of the Kunlun Mountains is the primary area to solidify and extend the success of Xinjiang Uygur Autonomous Region,China in poverty *** Sustainable Development Goals(SDGs)are intertwined with the concerted economic and social development of Xinjiang and the objective of achieving shared prosperity within the *** study established a sustainable development evaluation framework by selecting 15 SDGs and 20 secondary indicators from the United Nations’*** aim of this study is to quantitatively assess the progress of SDGs at the county(city)level on the northern slope of the Kunlun *** results indicate that there are substantial variations in the scores of SDGs among the nine counties and one city located on the northern slope of the Kunlun *** high scores of SDGs are observed in the central and eastern regions,whereas lower scores are prevalent in the western *** scores of SDGs,in descending order,are as follows:62.22 for Minfeng County,54.22 for Hotan City,50.21 for Qiemo County,42.54 for Moyu County,41.56 for Ruoqiang County,41.39 for Qira County,39.86 for Lop County,38.25 for Yutian County,38.10 for Pishan County,and 36.87 for Hotan *** performances of SDGs reveal that Hotan City,Lop County,Minfeng County,and Ruoqiang County have significant sustainable development capacity because they have three or more SDGs ranked as green ***,Hotan County,Moyu County,Qira County,and Yutian County show the poorest performance,as they lack SDGs with green *** is important to establish and enhance mechanisms that can ensure sustained income growth among poverty alleviation beneficiaries,sustained improvement in the capacity of rural governance,and the gradual improvement of social security *** measures will facilitate the effective implementation of ***,this study offers a valuable support for governmental authorities and relevant departments i

关键词： Sustainable Development Goals(SDGs) Northern slope of the Kunlun Mountains Poverty alleviation Arid lands Sustainable development capacity

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming zhou Kaiwen Li tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

An intermittent lithium deposition model based on CuMnbimetallic MOF derivatives for composite lithium anode with ultrahigh areal capacity and current densities

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Nano Research 2024年第4期17卷 2763-2769页

作者： tao Wei Yanyan zhou Cheng Sun Xingtong Guo Shoudong Xu Daifen Chen Yongfu Tang School of Energy and Power Jiangsu University of Science and TechnologyZhenjiang 212003China State Key Laboratory of Metastable Materials Science and Technology(MMST) Hebei Key Laboratory of Applied ChemistryYanshan UniversityQinhuangdao 066004China College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan 030024China

Recently,three-dimensional(3D)conductive frameworks have been chosen as the host for composite lithium(Li)metal anode because of their exceptional electrical conductivity and remarkable thermal and electrochemical ***,Li tends to accumulate on the top of the 3D frameworks with homogenous lithiophilicity and Li dendrite still *** work firstly designed a bimetallic metal-organic framework(MOF)(CuMn-MOF)derived Cu_(2)O and Mn_(3)O_(4) nanoparticles decorated carbon cloth(CC)substrates(CC@Cu_(2)O/Mn_(3)O_(4))to fabricate a composite Li *** to the synergistic effects of lithiophilic Cu_(2)O and Mn_(3)O_(4),the CC@Cu_(2)O/Mn_(3)O_(4)@Li symmetrical cell can afford a prolonged cycling lifespan(1400 h)under an ultrahigh current density and areal capacity(6 mA·cm^(-2)/6 mAh·cm^(-2)).When coupled with the LiFePO_(4)(LFP)cathode,the LFP||CC@Cu_(2)O/Mn_(3)O_(4)@Li full cell demonstrated a superior performance of 89.7 mAh·g^(-1) even at an extremely high current density(10 C).Furthermore,it can also be matched well with LiNi_(0.5)Co^(0).2Mn_(0.3)O_(2)(NCM523)***,to explain the excellent performances of the CC@Cu_(2)O/Mn_(3)O_(4)@Li composite anode,an intermittent model was also *** study offers a novel model that can enhance our comprehension of the Li deposition behavior and pave the way to attain stable and safe Li metal anodes by employing bimetallic MOF-derived materials to construct 3D frameworks.

关键词： lithium metal anode(LMA) three-dimensional(3D)frameworks intermittent lithiophilic model high areal capacity bimetallic metal-organic frameworks(MOFs)

Overcoming the Limits of Cross-Sensitivity:Pattern Recognition Methods for Chemiresistive Gas Sensor Array

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Nano-Micro Letters 2024年第12期16卷 285-341页

作者： Haixia Mei Jingyi Peng tao Wang Tingting zhou Hongran Zhao Tong Zhang Zhi Yang Key Lab Intelligent Rehabil&Barrier Free Disable(Ministry of Education) Changchun UniversityChangchun 130022People’s Republic of China Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237People’s Republic of China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Department of Micro/Nano ElectronicsSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin UniversityChangchun 130012People’s Republic of China

As information acquisition terminals for artificial olfaction,chemiresistive gas sensors are often troubled by their cross-sensitivity,and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing *** recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas *** is crucial to choose an appropriate pattern recognition method for enhancing data analysis,reducing errors and improving system reliability,obtaining better classification or gas concentration prediction *** this review,we analyze the sensing mechanism of crosssensitivity for chemiresistive gas *** further examine the types,working principles,characteristics,and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing ***,we report,summarize,and evaluate the outstanding and novel advancements in pattern recognition methods for gas *** the same time,this work showcases the recent advancements in utilizing these methods for gas identification,particularly within three crucial domains:ensuring food safety,monitoring the environment,and aiding in medical *** conclusion,this study anticipates future research prospects by considering the existing landscape and *** is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

关键词： Pattern recognition Sensor array Chemiresistive gas sensor Cross-sensitivity Artificial olfactory