Langevin granulometry of the particle size distribution

Attila Kákay, M. W. Gutowski, L. Takacs, V. Franco, L. K. Varga

Research output: Article

16 Citations (Scopus)

Abstract

The problem of deriving the particle size distribution directly from superparamagnetic magnetization curves is studied by three mathematical methods: (1) least-squares deviation with regularization procedure, (2) simulated annealing and (3) genetic algorithm. Software has been developed for the latest versions of all these methods and its performance compared for various models of underlying particle size distributions (Dirac δ-like, lognormal- and Gaussian-shaped). For single peak distributions all three methods give reasonable and similar results, but for bimodal distributions the genetic algorithm is the only acceptable one. The genetic algorithm is able to recover with the same precision both the lognormal and Gaussian single and double (mixed) model distributions. The sensitivity of the genetic algorithm - the most promising method - to uncertainty of measurements was also tested; correct peak position and its half width were recovered for Gaussian distributions, when the analysed data were contaminated with noise of up to 5% of MS.

Original languageEnglish
Pages (from-to)6027-6041
Number of pages15
JournalJournal of Physics A: Mathematical and General
Volume37
Issue number23
DOIs
Publication statusPublished - jún. 11 2004

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)

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