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您的检索式：作者名="Bingfeng Cai"
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| 1 | Ligand-controlled synthesis of high density and ultra-small Ru nanoparticles with excellent electrocatalytic hydrogen evolution performance显示文摘Ultra-small size metal nanoparticles(u-MNPs)have broad applications in the fields of catalysis,biomedicine and energy conversion.Herein,by means of a ligand-controlled synthesis strategy,series of Ru-based NPs with high dispersity and ultra-small size(marked as u-Ru/C),or sparse and aggregated state(marked as a-Ru/C)anchored on the surface of hollow porous carbon shells are prepared.Systematical in-situ thermogravimetry-mass spectrometry-Fourier transform infrared spectra tests suggest that the different ligands in these Ru-based precursors can regulate the nucleation,growth and fixation of metal sites during the pyrolysis process,thus contributing to Ru NPs with various size and dispersity.As a result,when applied to hydrogen evolution reaction,the u-Ru-1/C catalyst displays a low Tafel slope of 26 mV dec-1,overpotential of 31 mV(at 10 mA cm^(-2))and a large exchange current density of 1.7 mA cm^(-2) in 1.0 M KOH,significantly better than that of the a-Ru-2/C,hollow carbon and even commercial 20%Pt/C.This is mainly because that the u-Ru-1/C sample owns both smaller particle size,more electrochemical active sites,higher intrinsic activity and optimized surface H adsorption ability than that of the a-Ru-2/C counterpart.Such ligand-modulated growth strategy is not only applicable to Ru,but also can be extended to other similar metals,offering a step forward in the design and synthesis of highly dispersed u-MNPs. | Zhiwen Che Xuyun Lu Bingfeng Cai Xiangxing Xu Jianchun Bao Ying Liu | 2022 | Nano Research2022，15，2： | 1 |
| 2 | High-end equipment customer requirement analysis based on opinion extraction显示文摘Acquisition and analysis of customer requirements are the essential steps in high-end equipment design.Considering that Internet and big data technologies are integrated into the manufacturing industry, we propose a method of analyzing customer requirements based on open-source data. First, online data are collected with focused crawlers and preprocessed to filter noise and duplicate. Then, user opinions are extracted based on the defined template, and users' sentiments are analyzed.Based on the relationship between user sentiments and attribute parameters, the parameter range that satisfies customers can be obtained. The proposed method is evaluated by using an example of new energy vehicle to verify its availability and feasibility. | Yuejin TAN Yuren WANG Xin LU Mengsi CAI Bingfeng GE | 2018 | Frontiers of Engineering Management2018，5，4： | 0 |
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