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Zhu Wenjun,Zuo Xiaohua,Deng Xiangyi,Zhang Xinhao,Yao Chuang,Wang Xiaobo 한국탄소학회 2023 Carbon Letters Vol.33 No.2
Core–shell ZIFs wrapped CuO hybrid materials (CuO@ZIF-67(Co)) were designed, synthesized, characterized, and employed as peroxymonosulfate (PMS) activators to degrade methylene blue (MB). It demonstrated outstanding catalytic activity on account of the unique structure and the synergistic effect between CuO cores and ZIF-67(Co) shells, resulting in complete degradation of MB (10 mg/L) in 1 min. Reactive oxygen species (ROSs) research showed that both SO4− and OH were responsible for the removal of MB. The synergistic activation mechanisms in the CuO@ZIF-67(Co)/PMS system were investigated, which mainly involved the effective electron transfer of CuO and ZIF-67(Co) for accelerating the cycle of CuII/CuI and CoIII/CoII. This study broadens the application of MOF-derived materials for wastewater treatment.
Study on grinding mechanism and machining technology of Si3N4 ceramic spindle
Songhua Li,Chuang Li,Minghe Liu,Yonghua Wang,Chuang Zuo,Hao Zhang,Yifeng Gao 한양대학교 청정에너지연구소 2023 Journal of Ceramic Processing Research Vol.24 No.6
In order to improve the machining accuracy of the cylindrical surface of silicon nitride ceramic spindle, the machining technologyof the cylindrical surface of ceramic spindle was studied by high-speed universal cylindrical grinder in this experiment. Firstly, the primary and secondary order of the influence of various factors on the surface roughness of ceramic spindleis determined by orthogonal experiment, then the influence law of single grinding parameter on the surface roughness ofceramic spindle is explored by single factor experiment, and the prediction model of the grinding surface roughness value ofceramic spindle is calculated by numerical analysis software, and finally the optimal processing parameters of the cylindricalsurface of ceramic spindle are obtained. The experimental results show that the grinding surface roughness of silicon nitrideceramic spindle first decreases and then increases with the increase of grinding wheel linear speed and workpiece linearspeed, and then increases with the increase of transverse feed speed and axial feed speed. The relative error between the predictedvalue of the prediction model and the actual measured value is less than 5%, which shows that the prediction modelhas a good prediction effect and provides a theoretical basis for actual machining