Journal of Radioanalytical and Nuclear Chemistry

, Volume 210, Issue 1, pp 105–118 | Cite as

User-friendly software for Mössbauer spectrum analysis

  • Z. Klencsár
  • E. Kuzmann
  • A. Vértes
Article

Abstract

A new user-friendly software for analysis of Mössbauer-spectra has been developed. The program makes use of the advantages provided by the current generation of fast personal computers. An Evolution Algorithm1,2 is used for global search of Mössbauer parameters in order to enhance the reliability of the obtained results. Fitting of Lorentzians, Pseudo-Voigt line profiles, and deriving hyperfine-field distributions including correlations and combinations and Mössbauer Line Sharpening by Fourier transformation provide a wide range of applicability.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Z. MICHALEWICZ, Genetic Algorithms + Data Structures=Evolution Programs, Springer, Berlin, New York, London, 1992.Google Scholar
  2. 2.
    D. E. GOLDBERG, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, New York, Tokyo, Bonn, 1989.Google Scholar
  3. 3.
    S. L. RUBY, in: Mössbauer Effect Methodology, Gruverman (Ed.), Plenum Press, N.Y., 1973, p. 269.Google Scholar
  4. 4.
    A. BLAES, Nucl. Instr. Meth., B9 (1985) 201.Google Scholar
  5. 5.
    R. A. BRAND, Normos Mössbauer fit program, Laboratorium für Angewandte Physik, Duisburg, 1990.Google Scholar
  6. 6.
    E. W. MÜLLER, Mosfun, Mössbauer Spectrum Fitting Programme for Universal Theories, Inst. für Analytische Chemie, Gutenberg Universität, Mainz, 1980.Google Scholar
  7. 7.
    K. KULCSÁR, D. L. NAGY, L. PÓCS, Proc. Intern. Conf. on Mössbauer Spectroscopy, Dresden, 1971, p. 594.Google Scholar
  8. 8.
    D. G. RANCOURT, Nucl. Instr. Meth., B44 (1989) 199.Google Scholar
  9. 9.
    T. A. Kent, Wmoss Mössbauer spectral analysis software, Report WEB Research Co., Edmonton, 1993.Google Scholar
  10. 10.
    S. MARGULIES, J. R. EHRMAN, Nucl. Instr. Meth., 12 (1961) 131.Google Scholar
  11. 11.
    N. SEAGUSA, A. H. MORRISH, Phys. Rev., B26 (1992) 10.Google Scholar
  12. 12.
    R. E. VANDENBERGHE, E. De GRAVE, P. M. A. De BAKKER, Hyperfine Interactions, 83 (1994) 29.Google Scholar
  13. 13.
    W. I. F. DAVID, J. Appl. Cryst., 19 (1986) 63.Google Scholar
  14. 14.
    D. L. NAGY, U. RÖHLICH, Hyperfine Interactions, 66 (1991) 105.Google Scholar
  15. 15.
    J. HESSE, A. RÜBARTSCH, J. Phys. E: Sci. Instr., 7 (1974) 526.Google Scholar
  16. 16.
    B. WINDOW, J. Phys. E: Sci. Instr., 4 (1971) 401.Google Scholar
  17. 17.
    G. Le CÄER, J. M. DUBOIS J. Phys. E: Sci. Instr., 12 (1979) 1083.Google Scholar
  18. 18.
    I. VINCZE, Nucl. Instr. Meth., 199 (1982) 247.Google Scholar
  19. 19.
    D. W. MARQUARDT, J. Soc. Ind. Appl. Math., 11 (1963) 431.Google Scholar
  20. 20.
    W. H. PRESS, B. P. FLANNERY, S. A. TEUKOLSKY, W. T. VETTERLING, Numerical Recipes in Pascal, The Art of Scientific Computing, Cambridge University Press, New York, 1990.Google Scholar

Copyright information

© Akadémiai Kiadó 1996

Authors and Affiliations

  • Z. Klencsár
    • 1
  • E. Kuzmann
    • 1
  • A. Vértes
    • 1
  1. 1.Department of Nuclear ChemistryLoránd Eötvös UniversityBudapestHungary

Personalised recommendations