Computational Design of Catalysts
About This Course
This course equips learners with a rigorous, quantitative framework for designing and understanding catalysts using computational methods. This course is designed for learners in chemistry, chemical engineering, materials science, physics, or a related field, especially if they are interested in modeling, simulation, or theory-driven interpretation of catalytic phenomena. By taking this course, learners will be able to critically analyze catalytic systems and to design new catalysts based on physical principles rather than trial and error. The insights and skills gained during the course are directly valuable for research careers in academia, national laboratories, and the chemical industry.
As this micro-credential course is only offered in the FlexiMasters in Computational Chemical Modelling and AI programme, learners are required to enrol into the programme and complete all required courses within this programme.
What You'll Learn
• Construct and interpret potential energy and free energy diagrams for adsorption, surface reactions, diffusion, and electrocatalytic processes
• Calculate and analyze rate constants and reaction kinetics using transition state theory and microkinetic modeling to predict catalytic activity and selectivity of thermocatalytic and electrocatalytic processes.
• Apply scaling relations, energy trends, and activity/selectivity maps to rationalize trends across catalysts and identify optimal materials for specific reactions.
• Analyse and evaluate how catalytic performance arises from electronic structure and active-site geometry, by applying concepts such as the d-band model, Newns- Anderson theory, and structure sensitivity in heterogeneous catalysis.
Entry Requirements
No pre-requisites are needed to enroll in the individual courses; however, learners without qualifications or work experience in relevant engineering or the related fields may find the course contents challenging.
Note: Shortlisting will be conducted for the courses