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| 1 | Study of high pressure sintering behavior of CBN composites starting with CBN-Al mixtures显示文摘Cubic boron nitride(CBN) composites starting with CBN-Al mixtures were sintered on WC-16 wt%Co substrate under static high pressure of 5.0 GPa at temperatures of 800 to 1 400℃for 30 min.Vickers hardness of the sintered samples increased with increasing CBN content and the highest hardness of 32.7 GPa was achieved for the CBN-5 wt%Al specimens sintered at 1 400℃.The reactions between CBN and Al started to occur at about 900℃and the reaction products strongly depended on the Al content,sintering temperature and Co diffused from the substrates according to the x-ray diffraction(XRD) observations.The CBN composite sintered at 1 200℃from a CBN-15 wt%Al mixture showed the best cutting performance. | Li Yongjun Li Sicheng Lv Ran Qin Jiaqian Zhang Jian Wang Jianghua Wang Fulong Kou Zili He Duanwei (Institute of Atomic and Molecular Physics,Sichuan University,Chengdu 610065,China) | 2008 | 金刚石与磨料磨具工程2008，28，S1： | 3 |
| 2 | Blending LLDPE and ground rubber tires显示文摘 | Qin Jun Ding Hua Yu Zili | 2008 | Polymer-Plastics Technology and Engineering2008，47，2： | 1 |
| 3 | Large-scale preparation of black phosphorus by molten salt method for energy storage显示文摘Black phosphorus(BP)is a new layered material in concept,which has attracted great interest due to its fascinat-ing optical and electrochemical properties.Here,we report the large scale synthesis of BP(20 g)by reducing PCl 5 with metallic Al in melt AlCl 3 at 300°C.X-ray diffraction indicates the orthorhombic structure of BP and Raman spectrum shows that there is no obvious impurities.BP samples consist of micron-sized clusters of about 2μm aggregated by flake-like nanoparticles with 20-100 nm.When used as anode materials for lithium ion battery,it exhibits a high specific capacity of 1610 m Ah g−1 at a current density of 0.1C,and cycle life up to 1000 cycles at a current density of 5C.In addition,through gradient centrifugation of as-prepared BP samples,gram-scale BP quantum dots can be obtained. | Shaojie Zhang Zili Qin Zhiguo Hou Jiajia Ye Zhibin Xu Yitai Qian | 2022 | ChemPhysMater2022，1，1： | 1 |
| 4 | Decolorization of molasses fermentation wastewater by SnO:-catalyzed ozonation 显示文摘 | Zeng Yufeng Liu Zili Qin Zezeng | 2008 | Journal of Hazarddous Materials2008，162，23： | 1 |
| 5 | Preparation of InYO_3 catalyst and its application in photodegradation of molasses fermentation wastewater显示文摘An InYO 3 photocatalyst was prepared through a precipitation method and used for the degradation of molasses fermentation wastewater. The InYO 3 photocatalyst characterized by X-ray diffraction (XRD), UV-Vis diffuse reflectance spectroscopy, surface area and porosimetry. Energy band structures and density of states were achieved using the Cambridge Serial Total Energy package (CASTEP). The results indicated that the photodegradation of molasses fermentation wastewater was significantly enhanced in the presence of InYO 3 when compared with PbWO 4 . The calcination temperature was found to have a significant effect on the photocatalytic activity of InYO 3 . Specifically, InYO 3 calcined at 700°C had a considerably larger surface area and lower reflectance intensity and showed higher photocatalytic activity. The mathematical simulation results indicated that InYO 3 is a direct band gap semiconductor, and its conduction band is composed of In 5p and Y 4d orbitals, whereas its valence band is composed of O 2p and In 5s orbitals. | Zuzeng Qin Yi Liang Zili Liu Weiqing Jiang | 2011 | Journal of Environmental Sciences2011，23，7： | 1 |
| 6 | Interpolation Technique for the Underwater DEM Generated by an Unmanned Surface Vessel显示文摘High-resolution underwater digital elevation models(DEMs)are important for water and soil conservation,hydrological analysis,and river channel dredging.In this work,the underwater topography of the Panjing River in Shanghai,China,was measured by an unmanned surface vessel.Five different interpolation methods were used to generate the underwater DEM and their precision and applicability for different underwater landforms were analyzed through cross-validation.The results showed that there was a positive correlation between the interpolation error and the terrain surface roughness.The five interpolation methods were all appropriate for the survey area,but their accuracy varied with different surface roughness.Based on the analysis results,an integrated approach was proposed to automatically select the appropriate interpolation method according to the different surface roughness in the surveying area.This approach improved the overall interpolation precision.The suggested technique provides a reference for the selection of interpolationmethods for underwater DEMdata. | Shiwei Qin Zili Dai | 2023 | Computer Modeling in Engineering & Sciences2023，，9： | 0 |
| 7 | A novel pure data-selection framework for day-ahead wind power forecasting显示文摘Numerical weather prediction(NWP)data possess internal inaccuracies,such as low NWP wind speed corresponding to high actual wind power generation.This study is intended to reduce the negative effects of such inaccuracies by proposing a pure data-selection framework(PDF)to choose useful data prior to modeling,thus improving the accuracy of day-ahead wind power forecasting.Briefly,we convert an entire NWP training dataset into many small subsets and then select the best subset combination via a validation set to build a forecasting model.Although a small subset can increase selection flexibility,it can also produce billions of subset combinations,resulting in computational issues.To address this problem,we incorporated metamodeling and optimization steps into PDF.We then proposed a design and analysis of the computer experiments-based metamodeling algorithm and heuristic-exhaustive search optimization algorithm,respectively.Experimental results demonstrate that(1)it is necessary to select data before constructing a forecasting model;(2)using a smaller subset will likely increase selection flexibility,leading to a more accurate forecasting model;(3)PDF can generate a better training dataset than similarity-based data selection methods(e.g.,K-means and support vector classification);and(4)choosing data before building a forecasting model produces a more accurate forecasting model compared with using a machine learning method to construct a model directly. | Ying Chen Jingjing Zhao Jiancheng Qin Hua Li Zili Zhang | 2023 | Fundamental Research2023，3，3： | 0 |
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