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Trilinear self‐modeling curve resolution using Borgen‐Rajkó plot

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Modern analytical instruments provide measurement data arrays with full of hidden and redundant information. Multivariate curve resolution (MCR) techniques decompose data set to physic‐chemically meaningful abstract profiles. On the other… Click to show full abstract

Modern analytical instruments provide measurement data arrays with full of hidden and redundant information. Multivariate curve resolution (MCR) techniques decompose data set to physic‐chemically meaningful abstract profiles. On the other hand, for such data matrices, Borgen‐Rajkó self‐modeling curve resolution (SMCR) techniques reveal all possible solutions analytically under the minimal assumption. Although Lawton‐Sylvestre (LS) and Borgen methods have been proposed for the non‐negative curve resolution of two‐component and three‐component systems, there is still a great deal of interest to include further restrictions on the Borgen‐Rajkó SMCR. As modern hyphenated analytical instruments produce multiway (eg, three‐way) arrays, multiway analysis (eg, trilinear decomposition) was received much more popularity by chemists.

Keywords: resolution; borgen rajk; curve resolution; self modeling

Journal Title: Journal of Chemometrics
Year Published: 2020

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