University of Cartagena, Colombia
Miguel Ángel Mueses is a distinguished academic and researcher, recognized as a Senior Researcher by Colombia’s National System for Science, Technology, and Innovation (MinCiencias). His expertise spans a wide array of cutting-edge topics in chemical engineering, including solar photocatalysis, solar photoreactor engineering, and applied mathematical modeling in photocatalytic processes. He also conducts advanced research in environmental catalysis, molecular adsorption, Advanced Oxidation Technologies (AOTs), wastewater treatment, photocatalytic kinetics, scattering and absorption of radiant energy (VRPA), and quantification of quantum yields.
Dr. Mueses holds an h-index of 18, underscoring the significant scientific impact of his work. He plays an active role in academic publishing and scientific leadership as an Editorial Board Member of the Chemical Engineering Journal Advances (Elsevier) and Editor-in-Chief of Revista Ing-Nova at the University of Cartagena. He also serves on the Editorial Board of Revista Ingeniería y Competitividad (ISSN 0123-3033) and is a committed member of the Colombian Association for the Advancement of Science, contributing to the advancement of knowledge and innovation in Colombia and beyond.
Mathematical modeling of a phenomenon can be defined as the “Representation of natural phenomena using mathematical structures (equations) that allow to describe an approximation of the behavior of the same, with the smallest possible discrepancy, in a set range of operating conditions”. This definition is obviously applicable to Advanced Oxidation Processes. Mathematical modeling of AOPx is based on important steps that include: 1. An adequate understanding of the phenomena; 2. A pertinent graphic representation of the phenomenon (which implies a good understanding of it); 3. A correct delimitation of boundaries and conditions that guarantee the necessary approximations for the formulation of equations and reduction of the complexity of the system; 4. Methodological structuring of the components to be modeled in the system; 5. Formulation or implementation of equations, and 6. Numerical solution, validation and simulation of the phenomenon.
An adequate mathematical model can guarantee savings in experimental resources by allowing phenomena to be evaluated using simulation with high precision or minimal discrepancies with respect to natural behavior.
In the particular case of PAOx, the use of mathematical models and simulation has made it possible to describe, evaluate, and optimize new materials, photoreactors, contaminant degradation, radiant field, and intensified processes, and even to evaluate the performance of these processes at different scales (lab, pilot and comercial scale), at extremely low costs (computational and economic).