Self-modeling curve resolution SMCR

The SMCR method can be particularly useful for extracting chemically interpretable information from sets of spectral data without the use of reference concentration values. 

In the process analytical context, this method can be used to obtain reasonably good pure component spectra to aid in method development, as well as composition time profiles to enable assessment of reaction kinetics.4,63 

The SMCR method uses the same Beer s Law model as the CLS method, mentioned earlier  

However, unlike the CLS method, the SMLR method can be used without any knowledge of the concentrations of the different constituents in the calibration samples. Given only the spectral data (X), an estimate of the number of chemically varying and spectrally active components represented in the data (P), and some constraints regarding the nature of the expected structures of the pure component profiles (C) and pure component spectra (K), this method can be used to provide estimates of the pure component spectra (K) and the component concentrations (C). 

To address the issue of inter-correlations between pure chemical species, it is possible to impose additional application-specific constraints to improve the interpretability of SMCR results. For example, one might know the location of a pure component peak in the spectrum, or can obtain a sufficiently relevant pure component spectrum in the lab. Such additional constraints can be applied mathematically during the iterative SMCR process to improve the interpretability of the results.4 Of course, if such extra constraints 

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Jiang, J.H. and Ozaki, Y., Self-modeling curve resolution (SMCR) principles, techniques, and applications, Appl. Spectr. Rev., 37, 321-345, 2002. 

Amigo, J. M., Skov, T., Coello, J., Maspoch, S. Bro, R. (2008) Solving GC-MS problems with PARAFAC2. TrAC Trends in Analytical Chemistry, Vo. 27, No. 8, pp. 714-725 Awa, K., Okumura, T., Shinzawa, H., Otsuka, M. Ozaki, Y. (2008). Self-modeling Curve Resolution (SMCR) Analysis of Near-infrared (MR) limaging Data of Pharmaceutical Tablets. Analytica ChimicaActa, Vol. 619, No. 1, pp. 81-86 Bro, R. (2004). PARAFAC. Tutorial and applications. Chemometrics and Intelligent Laboratory Systems, Vol. 37, No. 2, pp. 149-171... 

Shinzawa, H., Jiang, J.-H., Iwahashi, M., Noda, I. Ozaki, Y. (2007). Self-modeling Curve Resolution (SMCR) by Particle Swarm Optimization (ISO). Analytica Chimica Acta, Vol. 595, No. 1-2, pp. 275-281... 

Self-modeling curve resolution (SMCR) analysis was applied to on-line NIR spectra of the melt-extrusion transesteriflcation of ethylene/vinylacetate copolymer. SMCR techniques include orthogonal projection analysis (OPA) and simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) [63]. 

SMCR self-modeling curve resolution UV-vis ultraviolet-visible... 

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