Why Is the Peak Group Analysis So Effective for IR Spectra Analysis?
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2026
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| author | Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall |
| author_facet | Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall |
| collection | Wiley Open Access |
| contents | Why Is the Peak Group Analysis So Effective for IR Spectra Analysis? Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall Journal of Chemometrics ABSTRACT Peak group analysis (PGA), an MCR algorithm, has proven to be very successful in extracting pure component spectra and concentration profiles from IR and Raman spectral data when investigating carbonylation reactions with transition metal catalysts. In this field of study, mixture spectra typically exhibit high spectral selectivity, meaning certain peaks belong exclusively to a single chemical species. Under this condition, PGA can extract the associated pure component spectrum from the mixture spectra, and there is no factor ambiguity in these profiles. Here, we present a short mathematical proof of this remarkable PGA property. 10.1002/cem.70121 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/cem.70121 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_cem_70121 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2026 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Why Is the Peak Group Analysis So Effective for IR Spectra Analysis? Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall Journal of Chemometrics Why Is the Peak Group Analysis So Effective for IR Spectra Analysis? Klaus Neymeyr Christoph Kubis Lukas Prestin Robert Franke Mathias Sawall Journal of Chemometrics ABSTRACT Peak group analysis (PGA), an MCR algorithm, has proven to be very successful in extracting pure component spectra and concentration profiles from IR and Raman spectral data when investigating carbonylation reactions with transition metal catalysts. In this field of study, mixture spectra typically exhibit high spectral selectivity, meaning certain peaks belong exclusively to a single chemical species. Under this condition, PGA can extract the associated pure component spectrum from the mixture spectra, and there is no factor ambiguity in these profiles. Here, we present a short mathematical proof of this remarkable PGA property. 10.1002/cem.70121 http://creativecommons.org/licenses/by/4.0/ |
| title | Why Is the Peak Group Analysis So Effective for IR Spectra Analysis? |
| topic | Journal of Chemometrics |
| url | https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/cem.70121 |