Estimating reaction rate constants: comparison between traditional curve fitting and curve resolution

Abstract

A traditional curve fitting (TCF) algorithm is compared with a classical curve resolution (CCR) approach for estimating reaction rate constants from spectral data obtained in time of a chemical reaction. In the TCF algorithm, reaction rate constants are estimated from the absorbance versus time data obtained from selective wavelengths. In this case, wavelengths are selected at which mainly one species is absorbing in time. In CCR, pure spectra of reacting absorbing species and the reaction rate constants are estimated simultaneously. Both TCF and CCR have been applied to experimental data. The reaction rate constants and the individual pure spectra of the reacting absorbing species were estimated simultaneously from the UV–VIS spectra taken in time of the two-step biochemical consecutive reaction of 3-chlorophenylhydrazonopropane dinitrile with 2-mercaptoethanol. This reaction was performed under second order and pseudo-first order conditions. For both conditions, the signal-to-noise ratio was approximately the same. However, if second order conditions are chosen, the first reaction step is very slow, which results in small absorbance differences in time. For the pseudo-first order dataset, the best precision of the reaction rate constant estimates has been obtained with TCF. For the second order dataset, CCR performed the best with respect to the precision of the reaction rate constant estimates.