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球墨铸铁表面激光熔覆层的组织及耐腐蚀性能研究

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表面技术 2024年第17期53卷 126-134,145页

作者：党钰钦李冬杰刘艳梅赵治伟白云龙 kim kwang ho 连伟锋王子铭王铁钢天津职业技术师范大学天津市高速切削与精密加工重点实验室天津300222 天津辉锐激光科技有限公司天津300384 中国第一重型机械股份公司天津重型装备工程研究有限公司天津300457 Global Frontier R&D Center for Hybrid Interface Materials Pusan National UniversityBusan 609-735The Republic of Korea 常州光洋轴承股份有限公司江苏常州213022

目的解决用于乏燃料贮运的球墨铸铁筒体容器因内壁腐蚀导致服役寿命短的问题,提高球墨铸铁表面的硬度及耐腐蚀性能。方法利用送粉式激光熔覆技术在球墨铸铁表面制备4种不同组分的316L不锈钢、Ni625合金、410L不锈钢及NJ30合金熔覆层。... 详细信息

目的解决用于乏燃料贮运的球墨铸铁筒体容器因内壁腐蚀导致服役寿命短的问题,提高球墨铸铁表面的硬度及耐腐蚀性能。方法利用送粉式激光熔覆技术在球墨铸铁表面制备4种不同组分的316L不锈钢、Ni625合金、410L不锈钢及NJ30合金熔覆层。采用金相显微镜、X射线衍射仪、扫描电子显微镜、能谱仪表征熔覆层的微观组织、物相组成、元素分布及腐蚀形貌。借助显微硬度计、电化学工作站测试熔覆层的显微硬度及耐腐蚀性能。结果4种合金熔覆层均成形质量良好,无裂纹及明显的气孔缺陷,并与基体形成了良好的冶金结合。熔覆层底部至顶部出现相似的组织形态,但晶粒尺寸存在较大的差异。316L、Ni625、410L及NJ30显微硬度显著高于基体,分别为基体的1.74、1.92、2.35及2.4倍,熔覆层内部固溶体及硬质相的生成是提高硬度的显著因素。在3.5%的NaCl溶液中,4种熔覆层的耐腐蚀性由好到差为316L、Ni625、410L、NJ30。腐蚀形貌显示,316L及Ni625熔覆层在电化学测试环境下具有良好的抗腐蚀性能。结论316L及Ni625合金熔覆层具有良好的综合性能,适用于提高大型球墨铸铁容器的表面改性。

关键词：激光熔覆球墨铸铁 Fe基 Ni基耐腐蚀性能

Pressure-induced hydrogen-dominant high-temperature superconductors

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National Science Review 2024年第7期11卷 14-16页

作者： ho-kwang Mao Shanghai Advanced Research in Physical Sciences Center for High Pressure Science and Technology Advanced Research

Recent studies of hydrogen-dominant（superhydride） materials have led to putative discoveries of near-room temperature superconductivity at high pressures. The idea started more than half-a-century ago as a by-product of the quest for metallic hydrogen for which a natural consequence of its very high Debye temperature and phonon frequency due to the very low mass of the hydrogen atoms would lead to a high superconducting critical temperature （Tc） in weak coupling Bardeen-Cooper-Schrieffer（BCS） expression.

关键词： HYDRIDE LANTHANUM

Magnetic methods in studies of new superconducting hydrides in a diamond anvil cell

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National Science Review 2024年第7期11卷 16-18页

作者： Viktor V.Struzhkin ho-kwang Mao Center for High Pressure Science&Technology Advanced Research

In recent years, we have witnessed great success in discoveries of high-transition-temperature（Tc） hydrides using high-pressure experiments. This has been achieved by creating metallic hydrogen‘alloys’ with other ...

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A novel method for determining the resistivity of compressed superconducting materials

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Matter and Radiation at Extremes 2024年第4期9卷 1-3页

作者： Liling Sun Qi Wu Shu Cai Yang Ding ho-kwang Mao Center for High Pressure Science and Technology Advanced Research Beijing 100094China Institute of Physics Chinese Academy of SciencesBeijing 100190China

The measurement of resistivity in a compressed material within a diamond anvil cell presents significant *** high-pressure exper-imental setup makes it difficult to directly measure the size changes induced by pressure in the three crystallographic directions of the *** this study,we introduce a novel and effective method that addresses these technical *** method is anticipated to offer a valuable foundation for high-pressure investigations on quantum materials,particularly those with anisotropic layered structures.

关键词： resistivity method foundation

还原性气氛制备Zr-B-N纳米复合涂层的结构及性能分析

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表面技术 2022年第9期51卷 83-90,101页

作者：张纪福刘艳梅张涛柯培玲张翔宇丁洋 kim kwang ho 王铁钢天津职业技术师范大学天津市高速切削与精密加工重点实验室天津300222 中国科学院宁波材料技术与工程研究所中国科学院海洋新材料与应用技术重点实验室浙江宁波315201 Global Frontier R&D Center for Hybrid Interface Materials Pusan National UniversityBusan 609-735South Korea

目的制备高纯度、超硬、高耐磨的Zr-B-N纳米复合涂层。方法在反应气体中掺入还原性气体H_(2),利用氢元素强还原性去除真空室以及反应气氛中残留的O杂质,采用脉冲直流磁控溅射技术,通过调节N_(2)+H_(2)混合气体流量制备高纯度Zr-B-N涂层... 详细信息

目的制备高纯度、超硬、高耐磨的Zr-B-N纳米复合涂层。方法在反应气体中掺入还原性气体H_(2),利用氢元素强还原性去除真空室以及反应气氛中残留的O杂质,采用脉冲直流磁控溅射技术,通过调节N_(2)+H_(2)混合气体流量制备高纯度Zr-B-N涂层。利用扫描电镜、纳米压痕仪、摩擦磨损试验机等设备对涂层的微观结构、力学性能和摩擦性能进行测试,并分析其变化机理。结果随着N_(2)+H_(2)流量的增加,Zr-B-N涂层内N含量在N_(2)+H_(2)流量为10 mL/min时达到最高。从截面形貌可以看出,涂层结构由粗大的柱状晶逐步转变为玻璃状细小柱状晶结构,涂层更加致密,呈现典型的纳米复合结构。微量H元素的掺入,减少了涂层制备过程中O相关化学键的生成,制备出的Zr-B-N涂层晶粒的生长环境得到改善。在N_(2)+H_(2)流量为10 mL/min时,涂层的硬度和弹性模量达到最大值40.26 GPa和532.98 GPa,临界载荷最大约为60.1 N,摩擦系数较小,为0.72,磨损率在此时最低,为1.12×10^(–5)mm^(3)/(N·m)。结论当N_(2)+H_(2)流量为10 mL/min时,制备出了超硬Zr-B-N纳米复合涂层。适量氢元素的掺入,充分去除真空室内氧杂质,改善了涂层中晶粒的生长环境,有效地提高涂层的硬度及摩擦磨损性能。

关键词：还原性反应气氛 Zr-B-N涂层磁控溅射纳米复合涂层微观结构力学性能

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Two-stage dynamic recrystallization and texture evolution in Al-7Mg alloy during hot torsion

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International Journal of Minerals,Metallurgy and Materials 2024年第8期31卷 1900-1911页

作者： kwang Tae Son Chang Hee Cho Myoung Gyun kim Ji Woon Lee School of Mechanical Industrialand Manufacturing EngineeringOregon State UniversityCorvallis OR 97331USA Department of Materials Science Engineering Northwestern UniversityEvanston IL 60208USA Research Institute of Industrial Science and Technology(RIST) Pohang 37673Rep.of Korea Division of Advanced Materials Engineering Kongju National UniversityCheonan 31080Rep.of Korea Center for Advanced Materials and Parts of Powders Kongju National UniversityCheonan 31080Rep.of Korea

hot torsion tests were performed on the Al-7Mg alloy at the temperature ranging from 300 to 500℃ and strain rates between 0.05 and 5 s^(-1) to explore the progressive dynamic recrystallization(DRX)and texture *** DRX behavior of the alloy manifested two distinct stages:Stage 1 at strain of≤2 and Stage 2 at strains of≥*** Stage 1,there was a slight increase in the DRXed grain fraction(X_(DRX))with predominance of discontinuous DRX(DDRX),followed by a modest change in X_(DRX) until the transition to Stage *** 2 was marked by an accelerated rate of DRX,culminating in a substantial final X_(DRX) of~*** backscattered diffraction(EBSD)analysis on a sample in Stage 2 revealed that continuous DRX(CDRX)predominantly occurred within the(121)[001]grains,whereas the(111)[110]grains underwent a geometric DRX(GDRX)evolution without a noticeable sub-grain ***,a modified Avrami’s DRX kinetics model was utilized to predict the microstructural refinement in the Al-7Mg alloy during the DRX *** this kinetics model did not accurately capture the DDRX behavior in Stage 1,it effectively simulated the DRX rate in Stage *** texture index was employed to assess the evolution of the texture isotropy during hot-torsion test,demonstrating significant improvement(>75%)in texture randomness before the commencement of Stage *** initial texture evolution is attributed to the rotation of parent grains and the substructure evolution,rather than to an increase in X_(DRX).

关键词： Al-7Mg alloys hot deformation hot torsion tests dynamic recrystazlliation microstructure texture

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Artificial intelligence in physiological characteristics recognition for internet of things authentication

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Digital Communications and Networks 2024年第3期10卷 740-755页

作者： Zhimin Zhang Huansheng Ning Fadi Farha Jianguo Ding kim-kwang Raymond Choo School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing100083China Faculty of Informatics Engineering Aleppo UniversityAleppoSyria Department of Computer Science Blekinge Institute of Technology37179KarlskronaSweden Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249-0631USA

Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)***,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral *** characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in ***,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate ***,we review the literature on the use of AI in physiological characteristics recognition pub-lished after *** use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their *** also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.

关键词： Physiological characteristics recognition Artificial intelligence Internet of things Biological-driven authentication

Network traffic classification:Techniques,datasets,and challenges

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Digital Communications and Networks 2024年第3期10卷 676-692页

作者： Ahmad Azab Mahmoud Khasawneh Saed Alrabaee kim-kwang Raymond Choo Maysa Sarsour College of Information Technology and Systems Victorian Institute of TechnologyAustralia College of Engineering Al Ain UniversityAbu DhabiUnited Arab Emirates Information Systems and Security College of ITUnited Arab Emirates UniversityAl Ain15551United Arab Emirates Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78260USA School of Photovoltaic and Renewable Energy Engineering University of New South WalesSydneyNSW2052Australia

In network traffic classification,it is important to understand the correlation between network traffic and its causal application,protocol,or service group,for example,in facilitating lawful interception,ensuring the quality of service,preventing application choke points,and facilitating malicious behavior *** this paper,we review existing network classification techniques,such as port-based identification and those based on deep packet inspection,statistical features in conjunction with machine learning,and deep learning *** also explain the implementations,advantages,and limitations associated with these *** review also extends to publicly available datasets used in the ***,we discuss existing and emerging challenges,as well as future research directions.

关键词： Network classification Machine learning Deep learning Deep packet inspection Traffic monitoring

Data driven computational design of stable oxygen evolution catalysts by DFT and machine learning:Promising electrocatalysts

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Journal of Energy Chemistry 2024年第4期91卷 645-655页

作者： Hwanyeol Park Yunseok kim Seulwon Choi ho Jun kim Department of Display Materials Engineering Soonchunhyang UniversityAsanChung-nam 31538Republic of Korea Department of Electronic Materials Devicesand Equipment EngineeringSoonchunhyang Uni-versityAsanChungnam 31538Republic of Korea Department of Mechanical Engineering Hanyang University ERICA Campus55 Hanyangdaehak-roSangnok-guAnsanGyeonggi-do 15588Republic of Korea

The revolutionary development of machine learning(ML),data science,and analytics,coupled with its application in material science,stands as a significant milestone of the scientific community over the last *** active,stable,and cost-efficient catalysts is crucial for oxygen evolution reaction owing to the significance in a range of electrochemical energy co nversion *** this work,we have demonstrated an efficient approach of high-throughput screening to find stable transition metal oxides under acid condition for high-performance oxygen evolution reaction(OER)catalysts through density functional theory(DFT)calculation and a machine learning algorithm.A methodology utilizing both the Materials Project database and DFT calculations was introduced to assess the acid stability under specific reaction *** upon this,OER catalytic activity of acid-stable materials was examined,highlighting potential OER catalysts that meet the required *** identified IrO_(2),Fe(SbO_(3))_(2),Co(SbO_(3))_(2),Ni(SbO_(3))_(2),FeSbO_(4),Fe(SbO_(3))4,MoWO_(6),TiSnO_(4),CoSbO_(4),and Ti(WO_(4))_(2)as promising catalysts,several of which have already been experimentally discovered for their robust OER performance,while others are novel for experimental exploration,thereby broadening the chemical scope for efficient OER *** of the bond length of TM-O and the first ionization energy were used to unveil the OER activity *** the calculated results,guidance has been derived to effectively execute advanced high-throughput screenings for the discovery of catalysts with favorable ***,the intrinsic correlation between catalytic performance and various atomic and structural factors was elucidated using the ML *** these approaches,we not only streamline the choice of the promising electrocatalysts but also offer insights for the design of varied catalyst models and the discovery of superior c

关键词： Transition metal oxides Oxygen evolution reaction High-throughput screening First-principles calculation Machine learning

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