Characterization of the Failure Site Distribution in MIM Devices Using Zoomed Wavelet Analysis

  • J. Muñoz-Gorriz
  • S. Monaghan
  • K. Cherkaoui
  • J. Suñé
  • P. K. Hurley
  • E. Miranda
Topical Collection: 17th Conference on Defects (DRIP XVII)
  • 6 Downloads
Part of the following topical collections:
  1. 17th Conference on Defects-Recognition, Imaging and Physics in Semiconductors (DRIP XVII)

Abstract

The angular wavelet analysis is applied to the study of the spatial distribution of breakdown (BD) spots in Pt/HfO2/Pt capacitors with square and circular areas. The method is originally developed for rectangular areas, so a zoomed approach needs to be considered when the observation window does not coincide with the device area. The BD spots appear as a consequence of the application of electrical stress to the device. The stress generates defects within the dielectric film, a process that ends with the formation of a percolation path between the electrodes and the melting of the top metal layer because of the high release of energy. The BD spots have lateral sizes ranging from 1 μm to 3 μm and they appear as a point pattern that can be studied using spatial statistics methods. In this paper, we report the application of the angular wavelet method as a complementary tool for the analysis of the distribution of failure sites in large-area metal–insulator–metal (MIM) devices. The differences between considering a continuous or a discrete wavelet and the role played by the number of BD spots are also investigated.

Keywords

Oxide breakdown high-k spatial statistics wavelet analysis 

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Supplementary material

11664_2018_6298_MOESM1_ESM.pdf (513 kb)
Supplementary material 1 (PDF 513 kb)

References

  1. 1.
    A. Oates, in IEDM Tech. Dig. 923 (2003).Google Scholar
  2. 2.
    E.Y. Wu, J.H. Stathis, and L.-K. Han, Semicond. Sci. Technol. 15, 425 (2000).CrossRefGoogle Scholar
  3. 3.
    E. Miranda, M. Ricio, G. De Falco, J. Blasco, J. Suñé, and A. Irace, J. Appl. Phys. 115, 174502 (2014).CrossRefGoogle Scholar
  4. 4.
    S. Lombardo, J.H. Stathis, B.P. Linder, K.L. Pey, F. Palumbo, and C.H. Tung, J. Appl. Phys. 98, 121301 (2005).CrossRefGoogle Scholar
  5. 5.
    S. Chatterjee, S. Chatterjee, Y. Kuo, J. Lu, J.-Y. Tewg, and P. Majhi, Microelectron. Reliab. 46, 69 (2006).CrossRefGoogle Scholar
  6. 6.
    X.S. Mas, S. Monaghan, P.K. Hurley, J. Suñé, and E. Miranda, IEEE Trans. Device Mater. Reliab. 14, 1080 (2014).CrossRefGoogle Scholar
  7. 7.
    J. Illian, A. Penttinen, H. Stoyan, and D. Stoyan, Statistical Analysis and Modelling of Spatial Point Patterns (Chichester: Wiley, 2008).Google Scholar
  8. 8.
    Y.-L. Li, Zs Tökei, Ph Roussel, G. Groeseneken, and K. Maex, Microeletron. Reliab. 45, 1299 (2005).CrossRefGoogle Scholar
  9. 9.
    E. Miranda, D. Jiménez, J. Suñé, E. O’Connor, S. Monaghan, I. Povey, K. Cherkaoui, and P.K. Hurley, J. Vac. Sci. Technol. B 31, 01A107 (2013).CrossRefGoogle Scholar
  10. 10.
    M.S. Rosenberg, J. Veg. Sci. 15, 277 (2004).CrossRefGoogle Scholar
  11. 11.
    C.K. Chui, Wavelet Analysis and Its Applications, Vol. 1 (San Diego: Academic Press, 1992).Google Scholar
  12. 12.
    M.R.T. Dale and M. Mah, J. Veg. Sci. 9, 805 (1998).CrossRefGoogle Scholar
  13. 13.
    J. Muñoz-Gorrriz, S. Monaghan, K. Cherkaoui, J. Suñé, P.K. Hurley, and E. Miranda, Microelectron. Eng. 178, 10 (2017).CrossRefGoogle Scholar
  14. 14.
    A. Baddeley and R. Turner, J. Stat. Softw. 12, 1 (2005).CrossRefGoogle Scholar
  15. 15.
    M.S. Rosenberg and C.D. Anderson, Methods Ecol. Evol. 2, 229 (2011).CrossRefGoogle Scholar

Copyright information

© The Minerals, Metals & Materials Society 2018

Authors and Affiliations

  1. 1.Departament d’Enginyeria ElectrònicaUniversitat Autònoma de BarcelonaBellaterraSpain
  2. 2.Tyndall National InstituteUniversity College CorkCorkIreland

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