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Dislocation Microstructure in PM Astroloy and Ma 6000 After HTLCF

  • A. J. Huis in’t Veld
  • P. M. Bronsveld
  • J. Th. M. De Hosson
  • J. Bressers

Abstract

In both MA 6000 and PM Astroloy deformation induced a/3<211> stacking faults are the dominant mechanism in LCF at 760 °C with strain rate 10−5s−1. Initially stacking faults are confined to precipitates in MA 6000 whereas in PM Astroloy some faults are located just outside the precipitates. Nevertheless ultimately, extended faults transform into deformation microtwins in both alloys. At 1050 °C the important features are coalescence of γ' precipitates and the formation of dislocation networks on the interfaces between precipitates and matrix. No stacking faults are observed at this temperature.

Keywords

Mechanical Alloy Stack Fault Energy Extended Fault Dislocation Network Shockley Partial Dislocation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    European concerted action, COST 50, Materials for Gas Turbines CCR 2, April 1982, by J. Bressers, P. Tambuyser and E. Fenske.Google Scholar
  2. [2]
    X. S. Xie, G. L. Chen, P. J. McHugh and J. K. Tien, Scripta Metal. 16, 483(1982).CrossRefGoogle Scholar
  3. [3]
    A. Lasalmonie and J. C. Strudel, Phil. Mag. 32, 937 (1975).CrossRefGoogle Scholar
  4. [4]
    A. J. Huis in’t Veld, G. Boom, P. M. Bronsveld, J. Th. M. De Hosson, Scripta Metall. 19, 1123 (1985.CrossRefGoogle Scholar

Copyright information

© ECSC, EEC, EAEC, Brussels and Luxembourg 1987

Authors and Affiliations

  • A. J. Huis in’t Veld
    • 1
  • P. M. Bronsveld
    • 1
  • J. Th. M. De Hosson
    • 1
  • J. Bressers
    • 2
  1. 1.Department of Applied Physics, Materials Science CentreUniversity of GroningenGroningenThe Netherlands
  2. 2.J.R.C. Petten EstablishmentPettenThe Netherlands

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