Advertisement

Journal of the Korean Physical Society

, Volume 74, Issue 11, pp 1046–1051 | Cite as

Degradation Test for an Anodic Aluminum Oxide Film in Plasma Etching

  • Seung-Su Lee
  • Min-Joong Kim
  • Chin-Wook Chung
  • Je-Boem Song
  • Seong-Geun Oh
  • Jin-Tae Kim
  • Nak-Kwan Chung
  • Ju-Young YunEmail author
Article

Abstract

A reliability assessment was performed to predict the lifetime of an anodic aluminum oxide film coated on equipment used in plasma etching processes. An anodic aluminum-oxide-coated part was exposed to an argon plasma, and its weight loss was monitored. This plasma test was conducted at four different pressure levels (125, 150, 200, and 250 mTorr). The failure distribution data obtained for each pressure level were found to indicate the same failure mechanism. Subsequently, an inverse power model was the best fit model for describing the relationship between the applied pressure and the lifetime of a part. The failure of the anodic aluminum oxide film caused by long-term exposure to plasma is, thus, shown to be closely linked to a decrease in the weight of the film.

Keywords

Plasma etching Anodic aluminum oxide film Degradation test Reliability 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

This research was funded by the R&D Convergence Program of National Research Council of Science and Technology (NST) of the Republic of Korea (NST, CAP- 16-04-KRISS).

References

  1. [1]
    T. Kawasaki, J. Electrostat. 66, 395 (2008).CrossRefGoogle Scholar
  2. [2]
    C. E. Barchiche et al., Electrochim. Acta 53, 417 (2007).CrossRefGoogle Scholar
  3. [3]
    V. M. Donnelly and A. Kornblit, J. Vac. Sci. Technol. A 31, 050825 (2013).CrossRefGoogle Scholar
  4. [4]
    N. Ito et al., Jpn. J. Appl. Phys. 47, 3630 (2008).CrossRefGoogle Scholar
  5. [5]
    W. B. Nelson, Accelerated Testing Statistical Models, Test Plans and Data Analysis (John Wiley & Sons, Inc., New York, 1990).zbMATHGoogle Scholar
  6. [6]
    W. Q. Meeker and L. A. Escobar, Statistical Methods for Reliability Data (John Wiley & Sons, Inc., New York, 1998).zbMATHGoogle Scholar
  7. [7]
    S. H. Mohammadian, D. Aït-Kadi and F. Routhier, Reliab. Eng. Syst. Safe. 95, 149 (2010).CrossRefGoogle Scholar
  8. [8]
    F. Pascual, IEEE T. Reliab. 57, 435 (2008).CrossRefGoogle Scholar
  9. [9]
    M. B. Carey and R. H. Koenig, IEEE T. Reliab. 40, 499 (1991).CrossRefGoogle Scholar
  10. [10]
    V. Bagdonavičius, A. Bikelis and V. Kazakevičius, Lifetime Data Anal. 10, 65 (2004).MathSciNetCrossRefGoogle Scholar
  11. [11]
    W. Li and H. Pham, IEEE T. Reliab. 54, 297 (2005).CrossRefGoogle Scholar
  12. [12]
    C. Park and W. J. Padgett, IEEE T. Reliab. 55, 379 (2006).CrossRefGoogle Scholar
  13. [13]
    L. A. Escobar W. Q. Meeker, Stat. Sci. 21, 552 (2006).CrossRefGoogle Scholar
  14. [14]
    F. Dia et al., Open J. Appl. Sci. 6, 49 (2016).CrossRefGoogle Scholar

Copyright information

© The Korean Physical Society 2019

Authors and Affiliations

  • Seung-Su Lee
    • 1
  • Min-Joong Kim
    • 1
  • Chin-Wook Chung
    • 1
  • Je-Boem Song
    • 2
  • Seong-Geun Oh
    • 2
  • Jin-Tae Kim
    • 3
  • Nak-Kwan Chung
    • 3
  • Ju-Young Yun
    • 3
    Email author
  1. 1.Department of Electrical EngineeringHanyang UniversitySeoulKorea
  2. 2.Department of Chemical EngineeringHanyang UniversitySeoulKorea
  3. 3.Center for Materials and Energy MeasurementKorea Research Institute of Standards and ScienceDaejeonKorea

Personalised recommendations