A comparative study of MCR-based kinetic analyses for chemical reaction systems with rate constant ambiguities

Abstract

The results of multivariate curve resolution (MCR) methods, specially solution’s ambiguity, can be influenced by the chosen MCR approach. We compare three MCR tools that support kinetic modeling in order to investigate this influence. These methods are Hard-Soft-Multivariate Curve Resolution, Multivariate Curve Resolution-Net Analyte Signal and a FACPACK implementation of a hard-modeling approach. As a common roof the more general approach of computing the set of feasible rate constants is used as implemented in the FACPACK kinetic hard-modeling software. The focus is on the comparison of the determined reaction rate constants and the occurrence of the corresponding solution ambiguities.Three spectroscopic data sets are considered in this study: First, an alkaline hydrolysis (UV–Vis) with a two-step consecutive first-order mechanism is used as a reference system. No rate constant ambiguity is present and all MCR methods give comparable, consistent results. The second data set concerns a formation of an iridium acyl complex (FTIR) based on a two-component reversible mechanism. Herein, k1 and k−1 (in h−1) range between 2.0 ​× ​10−3 ​− ​3.0 ​× ​10−3 and 3.0 ​× ​10−4 ​− ​9.0 ​× ​10−4, respectively. Due to similar data and model fit errors below 1%, it is not possible to distinguish the solutions. The reaction of 3-chlorophenylhydrazonopropane dinitrile with 2-mercaptoethanol (UV–Vis) based on a three-component partially reversible mechanism is the third studied data set. The resolved rate constants k1, k−1 and k2 (in min−1) range between 1.89 ​× ​10−1 ​− ​2.30 ​× ​10−1, 6.12 ​× ​10−2 ​− ​9.71 ​× ​10−2 and 3.83 ​× ​10−2 ​− ​4.48 ​× ​10−2, respectively. Analogous to the second data set an intrinsic rate constant ambiguity is observed. With this paper we would like to point out the existence of possible ambiguities when using kinetic models in combination with MCR methods for non-simulated, spectroscopic data. Furthermore we would like to suggest to include the calculation of these ambiguities as a postprocessing step in corresponding analyses, as this can increase the significance and reliability of the results.