Sequential Identification of Model Parameters by Derivative Double Two-Dimensional Correlation Spectroscopy and Calibration-Free Approach for Chemical Reaction Systems

Abstract

A sequential identification approach by two-dimensional (2D) correlation analysis for the identification of a chemical reaction model, activation, and thermodynamic parameters is presented in this paper. The identification task is decomposed into a sequence of subproblems. The first step is the construction of a reaction model with the suggested information by model-free 2D correlation analysis using a novel technique called derivative double 2D correlation spectroscopy (DD2DCOS), which enables one to analyze intensities with nonlinear behavior and overlapped bands. The second step is a model-based 2D correlation analysis where the activation and thermodynamic parameters are estimated by an indirect implicit calibration or a calibration-free approach. In this way, a minimization process for the spectral information by sample-sample 2D correlation spectroscopy and kinetic hard modeling (using ordinary differential equations) of the chemical reaction model is carried out. The sequential identification by 2D correlation analysis is illustrated with reference to the isomeric structure of diphenylurethane synthesized from phenylisocyanate and phenol. The reaction was investigated by FT-IR spectroscopy. The activation and thermodynamic parameters of the isomeric structures of diphenylurethane linked through a hydrogen bonding equilibrium were studied by means of an integration of model-free and model-based 2D correlation analysis called a sequential identification approach. The study determined the enthalpy (ΔH = 15.25 kJ/mol) and entropy (TΔS = 13.20 kJ/mol) of C═O···H hydrogen bonding of diphenylurethane through direct calculation from the differences in the kinetic parameters (δΔ(‡)H, -TδΔ(‡)S) at equilibrium in the chemical reaction system.