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Journal of Environmental sciences 2024年第2期136卷 390-399页

作者： Aihua Cheng Yi He xiaohe Liu Chi He Department of Environmental Engineering College of Geology and EnvironmentXi’an University of Science and TechnologyXi’an 710054China State Key Laboratory of Multiphase Flow in Power Engineering School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an 710049China National Engineering Laboratory for VOCs Pollution Control Material and Technology University of Chinese Academy of SciencesBeijing 101408China

Achieving an efficient and stable heterogeneous Fenton reaction over a wide pH range is of great significance for wastewater treatment.Here,a pollen-derived biochar catalyst with a unique honeycomb-like structure,coupled with the dispersion of magnetic Fe_(3)O_(4)/FeS(Fe/S)nanoparticles,was synthesized by simple impregnation precursor,followed by pyrolysis.The prepared Fe/S-biochar catalyst demonstrated outstanding phenol degradation efficiency across a wide pH range,with 98%of which eliminated even under neutral conditions(pH 7.0).The high catalytic activity was due to the multilevel porous structure of pollenderived biochar provided enough active sites and allowed for better electron transfer,then increases oxidation ability to promote the reaction.Moreover,the acid microenvironment formed by SO_(4)^(2-)group from Fe/S composite extended the pH range for Fenton reaction,and S^(2-)facilitated the conversion of≡Fe^(3+)to≡Fe^(2+),resulting in remarkable degradation efficiency.Further,biochar can effectively promote cycling stability by limiting Fe leaching.This work may provide a general strategy for designing 3D framework biochar-based Fe/S catalysts with excellent performance for heterogeneous Fenton reactions.

关键词： Biomass Biochar Fenton reaction Fe_(3)O_(4)/FeS(Fe/S) Phenol degradation

Thin paints for durable and scalable radiative cooling

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Journal of Energy Chemistry 2024年第3期90卷 176-182,I0006页

作者： Shanquan Liu Fei Zhang xingyu Chen Hongjie Yan Wei Chen Meijie Chen School of Energy science and Engineering Central South UniversityChangsha 410083HunanChina School of Intelligent Manufacturing Ecosystem Xi'an Jiaotong-Liverpool UniversitySuzhou 215400JiangsuChina

Passive daytime radiative cooling(PDRC) is environment-friendly without energy input by enhancing the coating's solar reflectance(R_(solar)) and thermal emittance(ε_(LWIR)) in the atmosphere's long-wave infrared transmission window.However,high R_(solar) is usually achieved by increasing the coating's thickness,which not only increases materials' cost but also impairs heat transfer.Additionally,the desired high R_(solar) is vulnerable to dust pollution in the outdoors.In this work,a thin paint was designed by mixing hBN plates,PFOTS,and IPA. R_(solar)=0.963 and ε_(LWIR)=0.927 was achieved at a thickness of 150 μm due to the high backscattering ability of scatters.A high through-plane thermal conductivity(~1.82 W m^(-1) K^(-1)) also can be obtained.In addition,the porous structure coupled with the binder PFOTS resulted in a contact angle of 154°,demonstrating excellent durability under dust contamination.Outdoor experiments showed that the thin paint can obtain a 2.3℃ lower temperature for sub-ambient cooling than the reference PDRC coating in the daytime.Furtherly,the above-ambient heat dissipation performance can be enhanced by spraying the thin paint on a 3D heat sink,which was 15.7℃ lower than the reference 1D structure,demonstrating excellent performance for durable and scalable PDRC applications.

关键词： Radiative cooling Heat dissipation Solar reflectance Thermal emittance Contact angle

Data-Driven Design for Targeted Regulation of Heat Transfer in Carbon/Carbon Composite Structure

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Journal of Thermal science 2024年第2期33卷 648-657页

作者： xiAO Heye WANG Zelin WANG Hui JI Ritian Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an710072China Research&Development Institute of Northwestern Polytechnical university in Shenzhen Shenzhen518063China MOE Key Laboratory of Thermo-Fluid science and Engineering School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an710049China

Targeted regulation of heat transfer in carbon/carbon composite structure is built for cooling electronic device.A three-dimensional data-driven design model coupling genetic algorithm(GA) with self-adaption deep learning for targeted regulation of heat transfer in built structure is proposed.The self-adaption deep learning model predicts the temperature of built structure closer to optimal value in GA model.The distributions of pore and carbon fiber bundles in built structure are optimized by the proposed model.The surface temperature of electronic device in the optimized structures is 19.1%-27.5% lower than that in the initial configurations when the porosity of built structure varies from 3% to 11%.The surface temperature of electronic device increases with an increase in porosity.The built structure with carbon fiber bundles near the surface of electronic device and pore distribution in the middle of structure has a higher heat dissipation capacity compared with that in the initial configuration.Besides,the computation time of the proposed model is less than one tenth compared with that of the traditional genetic algorithm.

关键词： targeted regulation of heat transfer self-adaption deep learning genetic algorithm carbon/carbon composite structure

Multi-Period Resilient Model for VSC-Based AC-DC HDS Considering Public-Safety Power Shutoff to Mitigate Wildfires

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 821-833页

作者： Zekai Wang Tao Ding xiaosheng Zhang Chenggang Mu Pengwei Du Fangxing Li School of Electrical Engineering Xi'an Jiaotong UniversityXi'an 710049China Electric Reliability Council of Texas AustinTX76574 USA Department of Electrical Engineering and Computer science The University of TennesseeKnoxville(UTK)TN37996USA

This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.

关键词： AC-DC hybrid distribution system restoration network reconfiguration progressive hedging public safety power shutoffs strategy resilience

Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis With Neuromorphic Computing

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 788-790页

作者： xinrui Chen xiang Li Shupeng Yu Yaguo Lei Naipeng Li Bin Yang the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniversityXi’an 710049China

Dear Editor,This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing.The event-based camera is adopted to capture the machine vibration states in ... 详细信息

关键词： fault less diagnosis

A comparative study of data-driven battery capacity estimation based on partial charging curves

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Journal of Energy Chemistry 2024年第1期88卷 409-420,I0010页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang xianggong Zhang Enhu Li Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina Wuhan Institute of Marine Electric Propulsion China State Shipbuilding Corporation LimitedWuhan 430064HubeiChina Gresgying Digital Technology Ltd. Xi’an 710086ShaanxiChina

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

关键词： Lithium-ion battery Partial charging curves Capacity estimation Data-driven Sampling frequency

Effects of surface energy and substrate on modulus determination of biological films by conical indentation

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science China(Technological sciences) 2024年第6期67卷 1757-1764页

作者： DING Yue LI Cheng-Ya NIU xinRui WANG Gang-Feng Department of Engineering Mechanics SVLXi’an Jiaotong UniversityXi’an710049China Department of Mechanical Engineering City University of Hong KongHong Kong SAR999077China

Micro-/nano-indentation has become prevalent in evaluating the mechanical characteristics of biological samples,such as cells and tissues.However,the existing contact models describing conical indentation ignore the joint effects of surface energy and substrate,and consequently cannot accurately extract the Young's modulus of biological samples deposited on substrate.Through finite element methods,we examine the conical indentation of biological films on substrates while taking surface energy into account.Based on the dimensional analysis,the explicit relationship between load and indentation depth is achieved for films with their moduli varying from 0.001 to 100 times that of the substrate.If the classical Sneddon's model was employed to analyze the load-depth data,the measured modulus could reach 18 times the real modulus for films on harder substrates,but only 4%of the real modulus for films on softer substrates.Meanwhile,in micro-/nano-indentations,neglecting the contribution of surface energy would result in an overestimation of the Young's modulus of films depending on the contact size.The analytical expression provided here can be utilized to precisely deduce the mechanical characteristics of biological films deposited on substrate from the load and indentation depth data of a conical indentation.

关键词： biological film surface effect substrate effect indentation

A low-frequency pure metal metamaterial absorber with continuously tunable stiffness

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Applied Mathematics and Mechanics(English Edition) 2024年第7期45卷 1209-1224页

作者： xingzhong WANG Shiteng RUI Shaokun YANG Weiquan ZHANG Fuyin MA School of Mechanical Engineering Xi'an Jiaotong University xi'an Precision Machinery Research Institute

To address the incompatibility between high environmental adaptability and deep subwavelength characteristics in conventional local resonance metamaterials,and overcome the deficiencies in the stability of existing active control techniques for band gaps, this paper proposes a design method of pure metal vibration damping metamaterial with continuously tunable stiffness for wideband elastic wave absorption. We design a dual-helix narrow-slit pure metal metamaterial unit, which possesses the triple advantage of high spatial compactness, low stiffness characteristics, and high structural stability, enabling the opening of elastic flexural band gaps in the low-frequency range.Similar to the principle of a sliding rheostat, the introduction of continuously sliding plug-ins into the helical slits enables the continuous variation of the stiffness of the metamaterial unit, achieving a continuously tunable band gap effect. This successfully extends the effective band gap by more than ten times. The experimental results indicate that this metamaterial unit can be used as an additional vibration absorber to absorb the low-frequency vibration energy effectively. Furthermore, it advances the metamaterial absorbers from a purely passive narrowband design to a wideband tunable one. The pure metal double-helix metamaterials retain the subwavelength properties of metamaterials and are suitable for deployment in harsh environments. Simultaneously, by adjusting its stiffness, it substantially broadens the effective band gap range, presenting promising potential applications in various mechanical equipment operating under adverse conditions.

关键词： elastic metamaterial absorber continuously tunable stiffness low-frequency vibration damping variable stiffness design pure metal structure O343 74G60

Fabrication and integration of photonic devices for phase-change memory and neuromorphic computing

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International Journal of Extreme Manufacturing 2024年第2期6卷 2-27页

作者： Wen Zhou Xueyang Shen xiaolong Yang Jiangjing Wang Wei Zhang Center for Alloy Innovation and Design(CAID) State Key Laboratory for Mechanical Behavior of MaterialsXi’an Jiaotong UniversityXi’an 710049People’s Republic of China

In the past decade,there has been tremendous progress in integrating chalcogenide phase-change materials(PCMs)on the silicon photonic platform for non-volatile memory to neuromorphic in-memory computing applications.In particular,these non von Neumann computational elements and systems benefit from mass manufacturing of silicon photonic integrated circuits(PICs)on 8-inch wafers using a 130 nm complementary metal-oxide semiconductor line.Chip manufacturing based on deep-ultraviolet lithography and electron-beam lithography enables rapid prototyping of PICs,which can be integrated with high-quality PCMs based on the wafer-scale sputtering technique as a back-end-of-line process.In this article,we present an overview of recent advances in waveguide integrated PCM memory cells,functional devices,and neuromorphic systems,with an emphasis on fabrication and integration processes to attain state-of-the-art device performance.After a short overview of PCM based photonic devices,we discuss the materials properties of the functional layer as well as the progress on the light guiding layer,namely,the silicon and germanium waveguide platforms.Next,we discuss the cleanroom fabrication flow of waveguide devices integrated with thin films and nanowires,silicon waveguides and plasmonic microheaters for the electrothermal switching of PCMs and mixed-mode operation.Finally,the fabrication of photonic and photonic–electronic neuromorphic computing systems is reviewed.These systems consist of arrays of PCM memory elements for associative learning,matrix-vector multiplication,and pattern recognition.With large-scale integration,the neuromorphic photonic computing paradigm holds the promise to outperform digital electronic accelerators by taking the advantages of ultra-high bandwidth,high speed,and energy-efficient operation in running machine learning algorithms.

关键词： nanofabrication silicon photonics phase-change materials non-volatile photonic memory neuromorphic photonic computing

Heat Transfer Characteristics of a Microchannel Heat Sink with Highly-Dense Micro-Jet Arrays

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Journal of Thermal science 2024年第3期33卷 1148-1160页

作者： ZHANG Yu CHEN xiaoyan MIAO Lin CHEN Liang HOU Yu State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong UniversityXi’an710049China Beijing Aerospace Technology Institute Beijing100083China

This paper proposed a new structure of highly-dense micro-jet arrays for hybrid jet-impingement/microchannel heat sinks(~120 jet per cm^(2) with jet width of 0.35 mm).Parametric study is performed to investigate the influence of structure and flow parameters on the convective heat transfer of water jet cooling in confined space.The simulation results show that the optimal jet width,jet spacing and impingement distance are around 0.2 mm,0.2 mm and 0.3 mm,respectively,which can achieve a low thermal resistance as well as a relatively low pressure drop.The analysis of the heat transfer pathways shows that the micro-fin jet structures can extend the impinging heat transfer area and conduct a considerable proportion of heat,which can reach up to 38.9%with the Reynolds number ranging from 797.1 to 5602.2.The heat transfer characteristics in the heat sink will shift from impingement dominated heat transfer to the channel-convection dominated heat transfer as the jet impingement distance increases.A correlation is proposed to predict the average Nusselt number on the stagnation area for the heat sink with different structure parameters,and the deviations of predictions from the numerical results are less than 10%.

关键词： hybrid heat sink impingement microchannel thermal management high heat flux