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Resonance Raman Scattering in [111]-Oriented CdTe/CdMnTe Superlattices

  • L. Vina
  • L. L. Chang
  • M. Hong
  • J. Yoshino
  • F. Calle
  • J. M. Calleja
  • C. Tejedor
Part of the NATO ASI Series book series (NSSB, volume 200)

Abstract

Cd1-xMnxTe alloys can be grown in zinc-blende structure up to a composition of х~0.7. The band gap of these crystals can be continuously tuned increasing the Mn composition.1 The difference between the band gaps of CdTe and the ternary alloy provides the potential for the electronic confinement in superlattices (SL’s) and quantum wells. High quality SL’s based on Cdi1-xMnxTе have been grown in the last years using epitaxial techniques.2–4 The optical properties of these SI’s have been studied extensively in the literature.5 Resonance Raman Scattering (RRS) provides the link between electronic and lattice-dynamical properties: the energy dependence of the Raman efficiency is determined by the electron-phonon coupling and by band-structure parameters. Recent reviews deal with vibronic6 and electronic7 properties of semiconductor SI’s studied with RRS. The phonon spectra of Cd1-xMnxTe bulk crystals8 and CdTe/Cd1-xMnxTe superlattices9–12 have been studied previously in the literature; these studies will be used here to compare new results in the SL’s. Usually, CdTe/Cd1-xMnxTe SL’s are grown on GaAs substrates. Two orientations of CdTe epitaxial films have been observed: (100)-CdTe parallel to (lOO)-GaAs13 or (111)-CdTe parallel to (100)-GaAs.14 Marked diferences between [lOO] and [ill] CdTe/Cd1-xMnxTe SL’s, attributed to the quality of the interfaces and to the presence of strain have been reported in the literature.3,9,15 Here we present a RRS study on [111] SL’s which shows a similar behaviour to that observed in [001] superlattices.9

Keywords

CdTe Layer CdTe Buffer Layer Resonance Raman Scattering Outgoing Channel Envelope Function Approximation 
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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Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • L. Vina
    • 1
  • L. L. Chang
    • 2
  • M. Hong
    • 2
  • J. Yoshino
    • 2
  • F. Calle
    • 3
  • J. M. Calleja
    • 3
  • C. Tejedor
    • 3
  1. 1.Instituto de Ciencia de MaterialesUniversidad de Zaragoza-C.S.I.C.ZaragozaSpain
  2. 2.IBM Thomas J Watson Research CenterYorktown HeightsUSA
  3. 3.Universidad Autonoma de MadridCantoblancoMadridSpain

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