DFT Studies on Metal Surfaces in Catalysis

Density functional theory (DFT) is a computational quantum mechanical modelling method which can be used to investigate the structures and properties of atoms and molecules. In this theory the many-body system can be described with functionals, which are much easier to solve than wave functions. Using the DFT method, the adsorption energy and geometry of an adsorbate on a catalyst can be simulated. Kinetic Monte Carlo (KMC) is a statistical tool which is widely used in surface science to estimate the activity and selectivity of a reaction step in real time on more realistic catalysts under more realistic conditions.

                                                 Figure 1: Pathway for DFT guided catalyst design                                        
Figure 2: DFT calculated adsorption energy for H2O adsorption on Au.

The alkaline fuel cell (AFC) uses an alkaline solution as electrolyte. More importantly, AFCs can work with non-precious catalysts, which help in lowering the cost. Our study focuses on the oxygen reduction reaction (ORR), which typically exhibits a high over potential due to slow kinetics. The development of viable catalysts is limited by a lack of detailed mechanistic understanding of the reaction pathway. Combined density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations can be used to gain an improved understanding of the ORR on Pt.

Figure 3: KMC calculations on Pt catalyst for ORR.

Results show that the consideration of solvation effect by water as well as the dynamic coverage effect of *OH are essential to properly describe the reaction kinetics. In addition, a chemisorbed water-mediated mechanism is identified, where the reduction steps are potential-independent via a water molecule adsorbed on the surface and only the final removal of *OH from the surface in the form of OH-aq contributes to the current.