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Anodic Coating

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Arthur W Brace – One of the best experts on this subject based on the ideXlab platform.

  • An expert system to identify Anodic Coating process defects. Part 2 : Compiling the hypertext database
    Transactions of The Institute of Metal Finishing, 2017
    Co-Authors: Arthur W Brace

    Abstract:

    The advantages of using a neural networks program for the identification of Anodic Coating process defects has been detailed in Part I of this paper. Having identified the defect it was considered desirable to develop a database which would provide information on the causes of defects, advise on corrective measures, include a relevant bibliography and be able to provide a graphics display of the defect where applicable. After illustrating some of the earlier databases the advantages of using a program containing a hypertext facility has been demonstrated and possible further development of the system is discussed.

  • An expert system to identify Anodic Coating process defects. Part 1 : The contribution of neural networks
    Transactions of The Institute of Metal Finishing, 2017
    Co-Authors: Arthur W Brace

    Abstract:

    The origin of process defects that may occur in the production of anodized finishes is categorized and the literature on process defects is reviewed. The author suggests from personal experience that in many plants steps taken to overcome problems due to the occurrence of defects is largely empirical and based on prior experience It is considered that this is a situation in which a systematic approach using computer-based information technology has practical advantages. After briefly discussing expert systems that have been used in metal finishing it is argued that these have limitations when applied to the identification of process defects since there is a degree of uncertainty existing as to the conditions that prevailed when the defect was produced. A neural networks program, considered to be particularly suited to evaluating problems in condition of uncertainty, has been adapted for the identification of defects. The primary classification is based on whether the defect is below or within the Anodic Coating, or associated with sealing. Having made this primary identification the user is directed to a file which relates to a specific process stage at which the defect was produced. After entering those features that describe the defect the program will identify the defect and indicate the probability of the classification being correct. Examples are given of the application of the program to defect identification.

P. Mishra – One of the best experts on this subject based on the ideXlab platform.

  • Effect of Surface Roughness of an Electropolished Aluminum Substrate on the Thickness, Morphology, and Hardness of Aluminum Oxide Coatings Formed During Anodization in Oxalic Acid
    Journal of Materials Engineering and Performance, 2017
    Co-Authors: R. K. Choudhary, K. P. Sreeshma, P. Mishra

    Abstract:

    Aluminum specimens were electropolished to five different roughness profiles and anodized in 10% oxalic acid under identical conditions in order to study the effect of surface topography on the thickness, morphology, chemical composition and hardness of the Anodic aluminum oxide Coatings formed. Field emission scanning electron microscopy showed that the Anodic Coating grown on a substrate having an average roughness of 250 nm was dense, whereas the microstructure became more porous with increasing the substrate roughness. The thickness of the Coating was found to be a parabolic function of substrate roughness. Energy-dispersive x-ray analysis of Coatings revealed a continuous increase in O/Al ratio with increasing substrate roughness suggesting increased incorporation of anions during oxide growth and also a tendency toward the formation of stoichiometric Al_2O_3. Coatings with higher O/Al ratio displayed improved hardness values.

Mu-rong Yang – One of the best experts on this subject based on the ideXlab platform.

  • The improvement of high-temperature oxidation of α2-Ti3Al by Anodic Coating in the phosphoric acid with sodium silicate
    Intermetallics, 2007
    Co-Authors: Mu-rong Yang, J.r. You

    Abstract:

    Abstract The 800 °C cyclic oxidation resistance of α2-Ti3Al can be improved by Anodic Coating in 4 wt% phosphoric acid with 2.9 wt% Na2SiO3 at 18 °C. Cyclic oxidation test indicates that, at 350 V anodizing voltage, the parabolic oxidation rate constant can be reduced to about 1/160 of that for as-homogenized α2-Ti3Al.

  • The improvement of high-temperature oxidation of Ti-50Al by Anodic Coating in the phosphoric acid
    Acta Materialia, 2002
    Co-Authors: Mu-rong Yang

    Abstract:

    Abstract The high temperature cyclic oxidation resistance of Ti–50Al can be improved by Anodic Coating in phosphoric acid aqueous solution (4 wt% H 3 PO 4 ) at 18°C. Sparking occurs sporadically on the surface as the voltage is over 300 V and the instantaneous current density after 45 min of anodization increases with increasing voltage. The Anodic films are amorphous and contain substantial amount of phosphorus. Cyclic oxidation test indicates that the anodization can remarkably reduce the oxidation in air at 800°C and the improvement increases with increasing anodizing voltage up to 400 V, at which the parabolic oxidation rate constant can be reduced to about 1/600 of that for as-homogenized Ti–50Al. Raman spectra show that the Anodic film can slow down the formation of rutile and α-Al 2 O 3 during oxidation. The doping effect of phosphorus ions in titanium oxide accounts for the improvement of high temperature oxidation of Ti–50Al.