孔梯度陶瓷纤维复合膜管的制备及特性

陶瓷过滤管具有孔隙率高、耐腐蚀、耐高温、机械强度高、便于清洗、使用寿命长等优点,是高温烟尘处理用的高效过滤元件.本文研制了一种具有梯度孔结构堇青石陶瓷纤维复合膜过滤元件,该过滤元件是由多孔支撑体、过渡层和分离膜层组成.其中支撑体、过渡层和分离层的气孔率分别为35～40;、50～60;和60～70;.文中主要分析了孔梯度陶瓷纤维复合膜管的材料结构和抗热震性能,同时对复合膜管进行含尘气体过滤的冷态模拟试验.对于烟气中粒径大于或等于0.1μm的颗粒,复合膜管的截留率达到99.8;以上.     

CTAB与SDBS对碳酸锶粒子生长形态调控及机理研究

以表面活性剂CTAB和SDBS为化学添加剂,采用化学共沉淀法对碳酸锶晶体的生长形态进行调控,成功地制备出了实心的树枝状和花瓣为空心的花状碳酸锶粉体,并用X射线衍射(XRD)、扫描电子显微镜(SEM)和傅里叶变换红外光谱(FT-IR)等分析手段对样品进行了表征;最后重点对化学添加剂可能产生的影响机理进行了初步的探讨.结果表明,CTAB和SDBS在晶体生长的过程中能起到显著的影响作用,两者对粒子分散性能的作用效果相反,而且后者对晶体(013)和(213)晶面表面能降低的贡献明显大于前者.     

低温制备≥99.5%多晶氧化铝陶瓷

本文通过引入稀土氧化物Y2O3、Tm2O3为烧结助剂低温制备了氧化铝含量大于99.5;的多晶氧化铝陶瓷.实验表明:稀土氧化物的加入能够明显降低99.5;多晶氧化铝陶瓷的烧结温度,提高致密度.Y2O3、Tm2O3混合烧结助剂与单一稀土氧化物的烧结助剂相比能够明显抑制晶粒的生长,促进晶粒的均匀发育.当Y2O3+Tm2O3的含量为0.3;质量分数时,99.5;多晶氧化铝陶瓷的相对密度可达99.2;理论密度,抗弯强度为533MPa,显微硬度为17.2GPa.陶瓷断裂主要以穿晶断裂为主.     

Fe3+对KDP晶体光学质量的影响

金属离子Fe3+对KDP晶体的生长和光学性质有明显影响.本文在前期研究的基础上[1]系统考察了该杂质离子对KDP晶体光学质量的影响.实验结果表明,三价金属离子Fe3+会降低KDP晶体的透光率,同时对晶体均匀性和光损伤阈值也有明显影响.光损伤阈值降低的主要原因在于杂质诱发缺陷导致的电子崩电离、多光子电离(尤其是双光子电离)等过程的发生.     

缓冲层ZnPc对有机电致发光器件特性的影响

本文研究了酞菁锌(ZnPc)薄膜的表面形貌及ZnPc薄膜作为缓冲层对有机电致发光器件(OLEDs)光电特性的影响.对比两组样品的AFM图像,ZnPc薄膜相比于ITO薄膜,其表面的岛面积较大,薄膜表面更连续平整,基本上覆盖了ITO膜表面针孔,减少了表面的缺陷.另外,ZnPc薄膜的岛分布均匀有序.使用ZnPc作为缓冲层的器件性能明显好于未使用ZnPc修饰的器件,在7.42V的驱动电压下的最大发光亮度达到1.428kcd/m2,在4.3V电压驱动下时,最大光功率效率为1.411m/W;而未使用缓冲层的器件在8V的驱动电压下达到最大发光亮度达到1.212kcd/m2,在5.5V电压驱动下时,最大光功率效率为0.931m/W.     

不同晶形纳米碳酸钙的制备及其表面改性研究进展

本文综述了不同晶形纳米碳酸钙的制备方法、纳米碳酸钙表面改性技术的研究现状以及表面改性方法,分析了目前纳米碳酸钙制备及表面改性技术存在的问题,并对其发展前景作了展望.     

Synthesis and Herbicidal Activity of Novel Sulfonylureas Containing Thiadiazol Moiety

Thirteen novel sulfonylureas containing thiadiazole moiety were synthesized in a two-step reaction. Their structures were determined using IR, ^1H NMR, HRFTMS, and elemental analysis. Herbicidal activities of these compounds were determined in the green house bio-assay. The results show that four compounds among them exhibit some activity toward four tested herbs.     

Cloning, Expression and Purification of Wheat Acetyl-CoA Carboxylases CT Domain in E.coil

The entire gene of carboxyltransferase(CT) domain of acetyl-CoA carboxylase(ACCase) from Chinese Spring wheat(CSW) plastid was cloned firstly,and the 2.3 kb gene was inserted into PET28a+ vector and expressed in E.coil in a soluble state.The (His)6 fusion protein was identified by SDS-PAGE and Western blot.The recombinant protein was purified by affinity chromatography,and the calculated molecular mass(Mr) was 88000.The results of the sequence analysis indicate that the cloned gene(GeneBank accession No.EU124675) was a supplement and revision of the reported ACCase CT partial cDNA from Chinese Spring wheat plastid.The recombinant protein will be significant for us to investigate the recognizing mechanism between ACCase and herbicides,and further to screen new herbicides.     

Determination of Acetonitrile Volume Fraction in Mobile Phase by HPLC

This paper reports the development and validation of an assay for the determination of acetonitrile in the recycled mobile phase using high performance liquid chromatography（HPLC）. The method is based on that the retention in reversed-phase liquid chromatography increases with decreasing concentration of organic phase in the mobile phase. The natural logarithm of the capacity ratio for a given solute is linearly related to the volume fraction of the organic modifier in the mobile phase. For dimethylphthalate and diethylphthalate, the linearity range is 30%--60%, and for biphenyl and terphenyl, the range is 60%--95%. Precision values（RSD） were both 〈1% and the accuracy（RE） was in the range of ±1%. The assay was successfully applied to the determination of acetonitrile concentration of recycled mobile phase after the distillation of the column eluent in our laboratory.     

A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.