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Applied Physics A

, Volume 80, Issue 8, pp 1701–1706 | Cite as

Magnetic nanowire arrays in anodic alumina membranes: Rutherford backscattering characterization

  • M. Hernández-Vélez
  • K.R. Pirota
  • F. Pászti
  • D. Navas
  • A. Climent
  • M. Vázquez
Article

Abstract

Systematic study of magnetic nanowire arrays grown in anodic alumina membranes (AAM) has been done by means of Rutherford backscattering spectroscopy (RBS). The AAM used as templates were morphologically characterized by using high resolution scanning electron microscopy (HRSEM), fast Fourier transform (FFT) and atomic force microscopy (AFM). The highly ordered templates with a mean pore diameter size of 30 nanometers, a mean inter-pore spacing of 100 nm and lengths ranging from 4 to 180 microns were obtained through two-steps anodization process, and the Ni and Co nanowire arrays were grown by electrodeposition techniques. The main attention is addressed to Ni nanowire arrays. RBS results allowed us to determine the real depth profile of atomic composition of the obtained nanowire arrays. In addition, the RBS spectra fitting showed that the porosity increased from the top to the bottom of the samples. Two phenomenological models are proposed to understand the apparition of that secondary porosity and a linear relation between the total amount of electrodeposited Ni and the electrodeposition time was obtained. As an example, it is also reported the relation between RBS results and magnetic properties, such as coercive field and remanence/saturation magnetization ratio of the samples. Particularly, for Ni nanowires arrays obtained by using voltage pulses, it is demonstrated that the larger the nanowires, the higher the definition for easy axis parallel to the nanowire length is possible.

Keywords

Atomic Force Microscopy Fast Fourier Transform Nanowire Array Rutherford Backscatter Spectroscopy Secondary Porosity 
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-Verlag 2005

Authors and Affiliations

  • M. Hernández-Vélez
    • 1
    • 2
  • K.R. Pirota
    • 2
  • F. Pászti
    • 3
    • 4
  • D. Navas
    • 2
  • A. Climent
    • 3
  • M. Vázquez
    • 2
  1. 1.Applied Physics Department, C-XIIUniversidad Autónoma de MadridMadridSpain
  2. 2.Instituto de Ciencia de Materiales de Madrid (ICMM-CSIC)MadridSpain
  3. 3.Centro de Micro-Análisis de Materiales (CMAM)MadridSpain
  4. 4.KFKI-Research Institute for Particle and Nuclear PhysicsBudapestHungary

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