Research output: Contribution to journal › Article › peer-review
On the potential and limitations of multivariate curve resolution in Mӧssbauer spectroscopic studies. / Debus, Bruno; Panchuk, Vitaly; Gusev, Boris; Savinov, Sergey; Popkov, Vadim; Legin, Andrey; Semenov, Valentin; Kirsanov, Dmitry.
In: Chemometrics and Intelligent Laboratory Systems, Vol. 198, 103941, 15.03.2020.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - On the potential and limitations of multivariate curve resolution in Mӧssbauer spectroscopic studies
AU - Debus, Bruno
AU - Panchuk, Vitaly
AU - Gusev, Boris
AU - Savinov, Sergey
AU - Popkov, Vadim
AU - Legin, Andrey
AU - Semenov, Valentin
AU - Kirsanov, Dmitry
PY - 2020/3/15
Y1 - 2020/3/15
N2 - 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.
AB - 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.
KW - Chemometrics
KW - Data processing
KW - Multivariate curve resolution
KW - Mӧssbauer spectroscopy
KW - ALTERNATING LEAST-SQUARES
KW - MIXTURE ANALYSIS
KW - Mossbauer spectroscopy
KW - EVOLVING FACTOR-ANALYSIS
KW - CONSTRAINTS
KW - AMBIGUITY
KW - RANK
KW - CHROMATOGRAPHY
UR - http://www.scopus.com/inward/record.url?scp=85078510266&partnerID=8YFLogxK
U2 - 10.1016/j.chemolab.2020.103941
DO - 10.1016/j.chemolab.2020.103941
M3 - Article
AN - SCOPUS:85078510266
VL - 198
JO - Chemometrics and Intelligent Laboratory Systems
JF - Chemometrics and Intelligent Laboratory Systems
SN - 0169-7439
M1 - 103941
ER -
ID: 51661812