Traditional processing of Mӧssbauer spectroscopy measurements assumes a decomposition of the spectra into separate multiplets corresponding to particular non-equivalent states of the resonance atom. When the number of spectra is large (e.g. in kinetic, corrosion and phase transition studies), this procedure becomes time-consuming. Moreover, traditional processing assumes some hypotheses on the number of non-equivalent states and initial multiplet parameters. The results of the processing strongly depend on these hypotheses and may be quite subjective. In an attempt to circumvent this issue, we studied the potential of Multivariate curve resolution (MCR) to unravel mixed multiplets spectra into their individual contributions. The application of MCR to Mӧssbauer studies was found to be quite challenging due to 1) long acquisition times limiting the number of available samples, 2) presence of critical spectral overlaps and 3) occasional deviations from the ideal bilinear assumption. In this report, we show how these limitations can be circumvented under certain conditions.

Original languageEnglish
Article number103941
Number of pages8
JournalChemometrics and Intelligent Laboratory Systems
Volume198
DOIs
StatePublished - 15 Mar 2020

    Research areas

  • Chemometrics, Data processing, Multivariate curve resolution, Mӧssbauer spectroscopy, ALTERNATING LEAST-SQUARES, MIXTURE ANALYSIS, Mossbauer spectroscopy, EVOLVING FACTOR-ANALYSIS, CONSTRAINTS, AMBIGUITY, RANK, CHROMATOGRAPHY

    Scopus subject areas

  • Software
  • Analytical Chemistry
  • Process Chemistry and Technology
  • Spectroscopy
  • Computer Science Applications

ID: 51661812