Abstract
Soft modeling (SM) methods can be used to resolve spectroscopic data from complicated reaction processes with unknown kinetics, with the exception of data containing a component for which there is no spectroscopic information available, such as an intermediate that does not absorb in the UV–visible region. In this work, modified SM methods were developed to resolve these undetectable components. Based on the mass balance principle, the mass balance error (MBE) method was first applied to determine whether the undetectable component existed. Next, the evolving error analysis (EEA) method was developed to search the local mass balance region (LMBR) where the concentration of the non-absorptive component was low enough to be neglected. In the LMBR, the concentration profiles of all absorptive components were scaled according to least squares regression. Subsequently, more reliable results were obtained using the evolving time region iteration (ETRI) method. Based on the mass balance principle, the concentration profile of the undetectable component was resolved for the entire time period. Both simulated and experimental data from an autocatalytic reaction were used to demonstrate the feasibility of the proposed method. In the autocatalytic oxidation of sodium oxalate by acidic potassium permanganate, the product Mn(II) was determined to be non-absorptive. Using the methods described above, the pure spectra of three other absorptive components and the scaled concentration profiles of four Mn species, including two intermediates, were all resolved. As a result, the mechanism of the reaction was more clearly described.
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