(178j) Theoretical Study On the Kinetics and Mechanisms of the Oxidation of Phenol by Advanced Oxidation Processes: Some Insights On QM Calculations as Applied to Chemical Engineering Studies

It has been recently proposed that Molecular Modeling (MM) would be an essential tool of research in Chemical Engineering. In fact, it has been suggested to be in the core of the emerging paradigm in Chemical Engineering. How accurate is this? What exactly, in the present time, computational chemistry calculations may offer to Chemical Engineers? In this work, some conventional MM techniques were tested to study part of the reactions involved in the degradation of phenol by Advanced Oxidation Processes (AOP), aiming: (i) the identification of molecular-reactions intermediates, (ii) the evaluation of a method to obtain ab initio kinetic constants estimations, (iii) the study of the effect of water solvation in the calculations, and, (iv) by comparison with the available experimental data, discuss different theoretical methods with respect to the accuracy and correlation with experiment.

The results suggest that DFT (Density Functional Theory) functionals play a better role in thermodynamical and kinetic parameters calculation than the semi-empirical AM1 (Austin Model 1) or the ab initio HF (Hartree-Fock) for these systems. As for the algorithms used, it was found that Eigenvector Following with tighter convergence criteria for geometry optimizations offers a higher accuracy to experiment than Steepest Descent method or a standard set of convergence criteria. For the only elementary reaction with experimental data available, it was found that the activation free energy calculated by DFT shows a deviation of 4 kcal mol-1 (the experimental uncertainty of energy measurements is reported as 2 kcal mol-1). The kinetic constant found for this reaction is within the order found in experiments. Applying the same set of functional, basis functions and mathematical convergence criteria, other reactions were studied and new, unreported and experimentally unavailable kinetic constants were found for elementary reactions within the process. Three different solvation models were tested, and the results show that the semi-empirical AM1 model, combined with SM5.42R solvation model, exhibits a very good agreement with the experimental value for phenol. However, since the reactions in this process involve electron transfer and the solvation stabilization relies strongly upon hydrogen-bonding interactions, explicit models using water molecules clusters around the solute molecule were also tested and are reported in this work.

Under the lights of the results obtained and their correlation with experimental data, it is reasonable to suggest that MM can yes be used to produce estimations of kinetic constants. It should be stressed, however, some important aspects on the choice of the method. Molecular Modeling involves a myriad of methods and models, and it is important that the researchers know how to make a choice between these countless options. The choice depends basically on five factors: (i) the system under study; (ii) the level of accuracy desired; (iii) the time available; (iv) the hardware available; (v) the parameterization of the model (if a parameterized model is to be used). The results of this work are compared with a previous theoretical study, stressing the importance of the knowledge of the chemical system being dealt with, and the physical assumptions underlying the different MM models applied to describe it.