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Tribological behavior of TiN,AlTiN,and AlTiCrN coatings in atmospheric and vacuum environments

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Friction 2024年第11期12卷 2611-2626页

作者： Youn-Hoo HWANG Kuk-Jin SEO Tae-Hyeong KIM You Jin MIN Yuzhen LIU Dae-Eun KIM department of Mechanical engineering Yonsei UniversitySeoul 03722Republic of Korea department of mechatronics and Energy engineering Ningbo Tech UniversityNingbo 315211China

In this study,the tribological characteristics of TiN,AlTiN,and AlTiCrN coatings sliding against a SUS420J1 stainless steel pin were investigated in atmospheric and vacuum *** coatings were deposited on SUS440C substrates using the arc-physical vapor deposition *** friction and wear behavior of the coatings were evaluated based on the systematic analyses of the friction coefficient data as well as the physical and chemical state of the wear *** results revealed that the friction coefficients of the SUS440C specimen and AlTiCrN coatings increased,whereas those of the TiN and AlTiN coatings decreased when the environment was changed from atmospheric to *** was confirmed that the formation of an oxide layer and adsorption of oxides on the surface were dominant factors that influenced the tribological behavior in the atmospheric *** the other hand,the compatibility,oxidation inhibition,and droplets of the surface mainly affected the frictional characteristics in the vacuum *** results of this work are expected to aid in the selection of proper coating materials for tribological systems operating in a vacuum.

关键词： friction wear coating vacuum TiN

Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED Abid HUSSAIN Hanzla SHAHID Imran ALI Hafiz Muhammad ALI department of Mechanical engineering University of Engineering and TechnologyTaxila47080Pakistan department of Mechanical engineering Institute of Space TechnologyIslamabadPakistan department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical engineering department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage *** thermal properties of PCMs can be improved by developing metal foam/PCM *** addition of metal foam in PCMs has a significant effect on the thermal characteristics of *** this paper,the heat storage properties of two different metal foam/PCM composites were experimentally *** behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was *** was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin *** temperature distribution during the phase transition process is experimentally *** comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat *** results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

Micro-nano-fabrication of green functional materials by multiphase microfluidics for environmental and energy applications

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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

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

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Energy and AI 2024年第3期17卷 406-418页

作者： Adithya Legala Matthew Kubesh Venkata Rajesh Chundru Graham Conway Xianguo Li Southwest Research Institute San AntonioTXUSA department of Mechanical and mechatronics engineering University of WaterlooWaterlooOntarioCanada

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

关键词： Artificial neural network(ANN) Proton exchange membrane fuel cell(PEMFC) Fuel cell electric vehicle(FCEV) Fuel cell-battery electric-electric hybrid power system Data based models Lithium-ion battery(LiB)

Correlation of work function and stacking fault energy through Kelvin probe force microscopy and nanohardness in diluteα-magnesium

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Journal of Magnesium and Alloys 2024年第1期12卷 237-250页

作者： Yigit Türe Ali Arslan Kaya Hüseyin Aydin Jiang Peng Servet Turan Eskisehir Technical University Porsuk Vocational SchoolElectronics and Automation DepartmentProgram of MechatronicsEskisehirTurkey Mugla Sitki Kocman University Engineering FacultyMetallurgy and Materials Engineering DepartmentMuglaTurkey Hüseying Aydın TUBITAK MRCTurkey Jiang Peng Chongqing UniversityChina Eskisehir Technical University Engineering FacultyMaterials Science and Engineering DepartmentEskisehirTurkey

Electronic interactions of the Group 2A elements with magnesium have been studied through the dilute solid solutions in binary Mg-Ca,Mg-Sr and Mg-Ba *** investigation incorporated the difference in the‘Work Function'(ΔWF)measured via Kelvin Probe Force Microscopy(KPFM),as a property directly affected by interatomic bond types,*** electronic structure,nanoindentation measurements,and Stacking Fault Energy values reported in the *** was shown that the nano-hardness of the solid-solutionα-Mg phase changed in the order of Mg-Ca>Mg-Sr>***,it was shown,by also considering the nano-hardness levels,that SFE of a solid-solution is closely correlated with its‘Work Function'***-hardness measurements on the eutectics andΔWF difference between eutectic phases enabled an assessment of the relative bond strength and the pertinent electronic structures of the eutectics in the three *** withΔWF and at least qualitative verification of those computed SFE values with some experimental measurement techniques were considered important as those computational methods are based on zero Kelvin degree,relatively simple atomic models and a number of *** asserted by this investigation,if the results of measurement techniques can be qualitatively correlated with those of the computational methods,it can be possible to evaluate the electronic structures in alloys,starting from binary systems,going to ternary and then multi-elemental *** investigation has shown that such a qualitative correlation is *** all,the SFE values are not treated as absolute values but rather become essential in comparative investigations when assessing the influences of alloying elements at a fundamental level,that is,free electron density *** study indicated that the principles of‘electronic metallurgy'in developing multi-elemental alloy systems can be followed via practical experimental methods,i.e.ΔWF measurements using KPF

关键词： Mg alloys Dilute alloys Work function Stacking fault energy Kelvin probe force microscopy Short range order Miedema Nanoindentation Eutectics

Reinforcement Learning-Based Energy Management for Hybrid Power systems:State-of-the-Art Survey,Review,and Perspectives

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Chinese Journal of Mechanical engineering 2024年第3期37卷 1-25页

作者： Xiaolin Tang Jiaxin Chen Yechen Qin Teng Liu Kai Yang Amir Khajepour Shen Li College of Mechanical and Vehicle engineering Chongqing UniversityChongqing 400044China School of Mechanical engineering Beijing Institute of TechnologyBeijing 100081China department of Mechanical and mechatronics engineering University of WaterlooWaterlooON N2L 3G1Canada School of Civil engineering Tsinghua UniversityBeijing 100084China

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient *** paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power ***,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational *** of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a ***,the comprehensive survey and review are conducted by collecting papers from mainstream academic *** most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research ***,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.

关键词： New energy vehicle Hybrid power system Reinforcement learning Energy management strategy

Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of mechatronics and Control engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

From seawater to hydrogen via direct photocatalytic vapor splitting: A review on device design and system integration

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Frontiers in Energy 2024年第3期18卷 291-307页

作者： Hongxia LI Khaja WAHAB AHMED Mohamed A.ABDELSALAM Michael FOWLER Xiao-Yu WU Technology Innovation Institute Masdar CityAbu Dhabi 9639United Arab Emirates department of Chemical engineering University of WaterlooWaterlooON N2L 3G1Canada department of Mechanical and Nuclear engineering Khalifa University of Science and TechnologyAbu Dhabi 127788United Arab Emirates department of Mechanical and mechatronics engineering University of WaterlooWaterlooON N2L 3G1Canada

Solar-driven hydrogen production from seawater attracts great interest for its emerging role in decarbonizing global energy consumption. Given the complexity of natural seawater content, photocatalytic vapor splitting offers a low-cost and safe solution, but with a very low solar-to-hydrogen conversion efficiency. With a focus on cutting-edge photothermal–photocatalytic device design and system integration, the recent research advances on vapor splitting from seawater, as well as industrial implementations in the past decades were reviewed. In addition, the design strategies of the key processes were reviewed, including vapor temperature and pressure control during solar thermal vapor generation from seawater, capillary-fed vaporization with salt repellent, and direct photocatalytic vapor splitting for hydrogen production. Moreover, the existing laboratory-scale and industrial-scale systems, and the integration principles and remaining challenges in the future seawater-to-hydrogen technology were discussed.

关键词： seawater hydrogen photocatalytic vapor splitting solar-driven