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Volume 33 Issue 05
May  2007
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Journal of Beijing University of Aeronautics and Astronautics  > 2007  >  33(05): 608-612.
Zhang Jun, Li Zhongxiao. Delay analysis of self-organized TDMA VHF datalink[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(03): 222-226. (in Chinese)
Citation: Yu Qinghe, Zhou Chungen. Plasma spraying of the nano-structured TiO2 coatings and its photocatalytic properties[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(05): 608-612. (in Chinese)
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Plasma spraying of the nano-structured TiO2 coatings and its photocatalytic properties

  • School of Materials Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • Received Date: 12 Jun 2006
  • Publish Date: 31 May 2007
    Abstract
  • The starting nano-TiO2 feedstock was agglomerated by spray-drying process. Nano-TiO2 coatings on transparent glasses were prepared by plasma spraying. The coating proceeded heat treatment at 300℃,400℃ and 500℃ respectively. The phase structure and the morphology of the TiO2 coatings were characterized by X-ray diffraction(XRD), scanning electron microscope(SEM) and transmission electron microscope(TEM). The porosity of the TiO2 coatings was tested by mercury porosimetry method. The result shows that the content of anatase TiO2 in the sprayed coatings is approximate to 30%~50%, and its grain size is about 10~30nm.The porosity of the TiO2 coatings is less than 6%,but has a great influence to the photocatalytic properties. After heat treatment at 300℃,400℃ and 500℃, the coating becomes denser and has a lower porosity, which leads to a decrease in photocatalytic properties. Sprayed nano-TiO2 coating obtained without heat treatment at the spraying current of 400A has the best photocatalytic property.

     

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  • [1] Lee Changhoon, Choi Hanshin, Lee Changhee, et al. Photocatalytic properties of nano-structured TiO2 plasma sprayed coating[J]. Surface and Coatings Technology, 2003,173(2/3):192-200 [2] Yu Jiaguo, Zhao Xiujian, Zhao Qingnan. Photocatalytic activity of nanometer TiO2 thin films prepared by the sol-gel method[J]. Materials Chemistry and Physics, 2001,69(1/2/3):25-29 [3] Boyd I W,Fang Q,Zhang J Y,et al. Investigation of TiO2-doped HfO2 thin films deposited by photo-CVD[J]. Thin Solid Films, 2003,428(1/2):263-268 [4] 王豫,水恒勇. 化学气相沉积制膜技术的应用与发展[J].热处理,2001,16(4):1-4 Wang Yu,Shui Hengyong. The application and development of techniques of film making with chemical vapor deposition[J]. Heat Treatment, 2001,16(4):1-4(in Chinese) [5] Zeman P, Takabayashi S. Nano-scaled photocatalytic TiO2 thin films prepared by magnetron sputtering[J]. Thin Solid Films, 2003,433(1/2):57-62 [6] Berger-keller N, Bertrand G, Filiatre C, et al. Microstructure of plasma-sprayed titania coatings deposited from spray-dried powder[J]. Surface and Coatings Technology, 2003,168(2/3):281-290  [7] Karthikeyan J, Berndt C C, Tikkanen J, et al. Plasma spray synthesis of nanomaterial powders and deposits[J]. Mater Sci Eng A Struct Mater Prop Microstruct Process, 1997,A238(2):275-286 [8] Shaw L L, Goberman D, Ren R, et al. Dependency of microstructure and properties of nanostructured coatings on plasma spray conditions[J]. Surface and Coatings Technology, 2000,130(1):1-8 [9] Beauvais S, Guipont V, Borit F, et al. Process-microstructure-property relationships in controlled atmosphere plasma spraying of ceramics[J]. Surface and Coatings Technology, 2004,183(2/3):204-211 [10] 冯拉俊,刘兵.等离子喷涂制备TiO2纳米颗粒[J].中国表面工程,2004,65(2):11-14 Feng Lajun, Liu Bing. Plasma spray synthesis of TiO2 nanopartical[J]. Surface Engineering of China, 2004, 65(2) :11-14(in Chinese) [11] Ye Fuxing, Ohomio A. A new application field of plasma spraying technique to environment depollution[J]. Trans Nonferrous Met Soc China, 2004, l14(2):55-61 [12] Yang R, Zhang Y P, Zhao R Y. An improved model for analyzing the performance of photocatalytic oxidation reactor in removing volatile organic compounds and its application[J]. The Air and Waste Management, 2004, 54(12):1516-1524 [13] 杨瑞,张寅平. 光催化反应器性能参数及其简便测试方法[J].工程热物理学报,2003,24 (2):310-312 Yang Rui, Zhang Yinping. Performance parameters for photocatalytic reactor and a convenient method for measuring them[J]. Journal of Engineering Thermophysics, 2003, 24 (2):310-312(in Chinese) [14] 杨瑞,莫金汉,张寅平. TiO2/丝光沸石光催化降解甲醛特性研究[J]. 工程热物理学报, 2005, 26 (3):474-476 Yang Rui, Mo Jinhan, Zhang Yinping. Photodestruction of dilute formaldehyde by titania/mordenite hybrid photo catylyst[J]. Journal of Engineering Thermophysics, 2005, 26(3):474-476(in Chinese)
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