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d-Like Quantum-Well States and Interface States of Paramagnetic Overlayers on Co(0001)

  • D. Hartmann
  • A. Rampe
  • W. Weber
  • M. Reese
  • G. Güntherodt
Part of the NATO ASI Series book series (NSSB, volume 345)

Abstract

Quantum-well states (QWS) are well known from semiconductor hetero structure s and have recently also been discovered in metallic overlayers on metal substrates1. Such metallic overlayers with thicknesses up to 30 atomic layers (AL) form a quantum well for the electrons inside them. One barrier of the quantum well is made up by the potential step due to the work function at the vacuum/overlayer interface and the other barrier by the potential step at the overlayer/substrate interface due to their different crystal potentials. Of special interest are overlayers on ferromagnetic substrates, because then the potential step at the overlayer/substrate interface can be spin-dependent leading to a quantum well of different depth for majority- and minority-spin electrons. The corresponding QWS therefore are spin-polarized. Furthermore, the binding energy of the QWS varies as a function of the overlayer thickness, following the dispersion of the overlayer bulk band from which they are derived2. For (100)-oriented noble metal overlayers this bulk band was identified as a sp-like band2–4. The spin-polarized QWS4–6 are considered as mediators of the oscillatory interlayer exchange coupling7,8. This description is equivalent to the RKKY-like coupling model of two ferromagnetic layers through a noble metal interlayer9. The connection between the two models is that the oscillation period is determined by extremal wave vectors of the Fermi surface, which are the corresponding wave vectors of the QWS. The present understanding is that the spin-dependent reflection coefficients of the electrons in the interlayer lead to dominantly minority-spin QWS and to a spin-density modulation.

Keywords

Atomic Layer Spin Polarization Lattice Misfit Photoemission Spectrum Interlayer Coupling 
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

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • D. Hartmann
    • 1
  • A. Rampe
    • 1
  • W. Weber
    • 1
    • 2
  • M. Reese
    • 1
  • G. Güntherodt
    • 1
  1. 1.2. Physikalisches InstitutRWTH AachenAachenGermany
  2. 2.IBM Research DivisionZürich Research LaboratoryRüschlikonSwitzerland

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