Iterative target transformation factor analysis for the resolution of kinetic–spectral data with an unknown kinetic model

The resolution of two-way kinetic–spectral data obtained in the process of spectroscopic reaction with an unknown kinetic model must rely on chemometric algorithms with a non-model-based procedure. Iterative target transformation factor analysis (ITTFA), a type of self-modeling curve resolution (SMCR), is applied to resolve this kind of kinetic–spectral data matrix and the kinetic spectrum of each component is obtained. The construction of the initial iterative vector is the key to ITTFA. A novel approach is proposed to construct the initial vectors based on spectral features like the isoabsorptive points between components in the system to ensure that ITTFA can converge to the real solution without any constraints. The effect of the different initial vectors on the results is discussed and it is shown that the initial vector based on the isoabsorptive points can converge accurately and rapidly. To estimate the scale coefficients, which contribute to the conversion of the iterative results into the real kinetic spectra, a method is improved based on the mass equilibrium principle or isoabsorptive points of the relevant components. With the proposed method, the simulated data matrix for a two-step consecutive reaction with an unknown kinetic model, where all components are absorbing, has been successfully resolved. The data matrix measured for the electrodegradation process of salicylic acid, where the final product has no absorption, can also be resolved to obtain a reliable result.