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9篇 您的检索式:作者名="Jiang Mingfei"
    题名 作者 年代 出处 被引量
1Improving the mechanical property of dissimilar Al/Mg hybrid friction stir welding joint by PIO-ANN显示文摘Ultrasonic-stationary shoulder assisted friction stir welding(U-SSFSW)is a novel hybrid welding technique,which reveals promising prospect in joining Al/Mg dissimilar alloys.A thorough understanding of U-SSFSW process is imperative for the further application of this technique.Pigeon-inspired optimization(PIO)is a swarm intelligent optimization algorithm and is proposed in mathematical modeling and process optimization by artificial intelligence.In this study,PIO optimized artificial neural network(PIOANN)was firstly established to acquire the relationships between the inputs and output of the Al/Mg welding process by U-SSFSW technique.A reliable PIO-ANN was achieved and the joint with a tensile strength of 161 MPa was acquired under the PIO optimized parameters.This tensile strength is higher than any ever-reported results with the similar welding condition.The joint formation,microstructure,microhardness and fracture behaviors were systemically investigated based on the reported studies and the confirmation experiment of this study to explore the enhancing mechanism of U-SSFSW Al/Mg joint.Wei Hu Zhongwei Ma Shude Ji Qi Song Mingfei Chen Wenhui Jiang 2020Journal of Materials Science & Technology2020,52,18:3
22020 Roadmap on two-dimensional nanomaterials for environmental catalysis显示文摘Environmental catalysis has drawn a great deal ofattention due to its clean ways to produce useful chemicals or carry out some chemical processes.Photocatalysis and electrocatalysis play important roles in these fields.They can decompose and remove organic pollutants from the aqueous environment,and prepare some fine chemicals.Moreover,they also can carry out some important reactions,such as 02 reduction reaction(ORR),O2 evolution reaction(OER),H2 evolution reaction(HER),CO2 reduction reaction(C02 RR),and N2 fixation(NRR).For catalytic reactions,it is the key to develop high-performance catalysts to meet the demand fortargeted reactions.In recentyears,two-dimensional(2 D) materials have attracted great interest in environmental catalysis due to their unique layered structures,which offer us to make use of their electronic and structural characteristics.Great progress has been made so far,including graphene,black phosphorus,oxides,layered double hydroxides(LDHs),chalcogenides,bismuth-based layered compounds,MXenes,metal organic frameworks(MOFs),covalent organic frameworks(COFs),and others.This content drives us to invite many famous groups in these fields to write the roadmap on two-dimensional nanomaterials for environmental catalysis.We hope that this roadmap can give the useful guidance to researchers in future researches,and provide the research directions.Yulu Yang Mingguang Wu Xingwang Zhu Hui Xu Si Ma Yongfeng Zhi Hong Xia Xiaoming Liu Jun Pan Jie-Yinn Tang Siang-Piao Chai Leonardo Palmisano Francesco Parrino Junli Liu Jianzhong Ma Ze-Lin Wang Ling Tan Yu-Fei Zhao Yu-Fei Song Pardeep Singh Pankaj Raizada Deli Jiang Di Li R.A.Geioushy Jizhen Ma Jintao Zhang Song Hu Rongjuan Feng Gang Liu Minghua Liu Zhenhua Li Mingfei Shao Neng Li Jiahe Peng Wee-Jun Ong Nikolay Kornienko Zhenyu Xing Xiujun Fan Jianmin Ma 2019Chinese Chemical Letters2019,30,12:2
3Electrosynthesis of hierarchical NiLa-layered double hydroxide electrode for efficient oxygen evolution reaction显示文摘Oxygen evolution reaction(OER) is a key process for electrochemical water splitting due to its intrinsic large overpotential. Recently, layered double hydroxides(LDHs), especially Ni Fe-LDH, have been regarded as highly performed electrocatalysts for OER in alkaline condition. Here we first present a new class of Ni La-LDH electrocatalyst synthesized by an electrochemical process for efficient water splitting. The as-prepared NiL a-LDH nanosheet arrays(NSAs) give remarkable electrochemical activity and durability under alkaline environments, with a low overpotential of 209 mV for OER to deliver a current density of 10 mA cm^-2, surpassing most of previous reported LDHs eletrocatalysts. The presence of NiLa-LDH in this work extends the studies about LDHs-based electrocatalysts, which will benefit the development of electrochemical energy storage and conversion systems.Shan Jiang Yunke Liu Wenfu Xie Mingfei Shao 2019Journal of Energy Chemistry2019,28,6:1
4Experimental studies on the properties of constructional steel at elevated temperatures 显示文摘Li Guoqiang Jiang Shouchao Yin Yingzhi Chen Kai Li Mingfei 2003Journal of Structural Engineering2003,129,12:1
5Experimental studies on the properties of constructional steel at elevated temperatures 显示文摘LI Guoqiang JIANG Shouchao YIN Yingzhi CHEN Kai LI Mingfei 2003Journal of Structural Engineering2003,129,12:1
6Transa-ction management of database in mobile computing environment显示文摘Xu Lizhen Jiang Mingfei Dong Yisheng 2002Journal of Southeast University2002,32,6:1
7Experimental Structural on the Properties of Constructional Steel at Elevated Temperatures显示文摘Li Guoqiang Jiang Shouchao Yin Yingzhi Chen Kai Li Mingfei 2003Journal of Structural Engineering2003,129,12:1
8Elevational patterns and ecological determinants of mean family age of angiosperm assemblages in temperate forests within Mount Taibai, China显示文摘Aims Species assembly is shaped by the interactions among ecological and evolutionary processes.By integrating the niche conservatism and evolutionary history,the tropical niche conservatism hypoth-esis(TCH)has clarified species latitudinal diversity gradient at large scales.One of the TCH’s central predictions,though lack-ing empirical evidence,implies that positive relationship between clade age and temperature along the altitudinal gradient should also be observed.Thus,we aim to test this prediction using a data set derived from forest communities of Mt.Taibai,central China.Methods We systematically established 49 plots(20 m×30 m)along the north slope on Mt.Taibai,China.We calculated the mean family age(MFA)and its corresponding standardized values through rarefi-cation and standardization,for woody and herbaceous angiosperm assemblages in each community respectively.Generalized linear models with Akaike weight and correlation analysis was used to evaluate the relationships between MFA with seven environmental predictors.Important Findings For both woody and herbaceous assemblages,the standardized MFA showed significant decreasing tendencies along the eleva-tional gradient and positive associations with minimum temperature(measured as mean temperature of the coldest month).Additionally,minimum temperature is the dominant predictor compared with the others in the regression models.These findings are generally con-sistent with the age-related predictions of the TCH,but are contrary to the results of related studies conducted in tropical regions.Mingfei Zhao Yuhang Wang Feng Xue Wanyi Zuo Kaixiong Xing Guoyi Wang Muyi Kang Yuan Jiang 2018Journal of Plant Ecology2018,11,6:0
9Metal vacancy-enriched layered double hydroxide for biomass molecule electrooxidation coupled with hydrogen production显示文摘The electrochemical oxidation of biomass molecules coupling with hydrogen production is a promising strategy to obtain both green energy and value-added chemicals;however,this strategy is limited by the competing oxygen evolution reactions and high energy consumption.Herein,we report a hierarchical CoNi layered double hydroxides(LDHs)electrocatalyst with abundant Ni vacancies for the efficient anodic oxidation of 5-hydroxymethylfurfural(HMF)and cathodic hydrogen evolution.The unique hierarchical nanosheet structure and Ni vacancies provide outstanding activity and selectivity toward several biomass molecules because of the finely regulated electronic structure and highly-exposed active sites.In particular,a high faradaic efficiency(FE)at a high current density(99%at 100 mA cm^(-2))is achieved for HMF oxidation,and a two-electrode electrolyzer is assembled based on the Ni vacancies-enriched LDH,which realized a continuous synthesis of highly-pure 2,5-furandicarboxylic acid products with high yields(95%)and FE(90%).Yingjie Song Shan Jiang Yeheng He Yu Wu Xin Wan Wenfu Xie Jingjing Wang Zhenhua Li Haohong Duan Mingfei Shao 2024Fundamental Research2024,4,1:0
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