Computational Design of Electrocatalysts for Oxygen Reduction Reaction

The ever increasing fossil fuel consumption has been linked to anthropogenic global warming, which might result in a 4◦C increase in the global mean temperature during the 21st century under certain “business as usual” fossilrich scenarios. Apart from carbon dioxide emission, fossil fuel combustion is also responsible for the emission of many other toxic air pollutants. The synergistic effect between climatic change and air pollution can magnify health hazards. Thus, technologies for more environmentally friendly energy conversion are therefore actively being pursued. One such technology is the polymer electrolyte membrane fuel cell (PEMFC).
In PEMFCs, a fuel such as methanol or hydrogen is oxidized at the anode and oxygen is reduced to water at the cathode. Possible applications of PEMFC ranges from stationary to mobile and portable applications, in e.g. auxiliary power units (APU) and fuel cell electric vehicles (FCEV). However, the widespread use of hydrogen fuel cells continue to face several challenges, the most significant of which is the high cost of the platinumbased catalyst used in the electrodes, which contributes to almost 55% of the total cost. Ideally, to decrease the overall cost of PEMFCs, development of new and costefficient catalyst candidates for both cathode and anode is highly desirable but the slow oxygen reduction reaction (ORR) at the cathode requires much more platinum than the much faster hydrogen oxidation reaction at the anode. The sluggish kinetics of the ORR at the PEMFC cathode can lead to nearly 30% efficiency decrease of the PEMFCs. Thus, in particular, the development of costefficient, nonprecious metal catalysts for the ORR with a high catalytic efficiency has received much attention.
Some of the possible alternatives can be catalysts based on transition metals in nitrogen doped graphitic cathodes, oxides and oxynitrides of transition metals e.g. tantalum, zirconium oxide based catalysts with multiwalled carbon nanotubes (MWCNTs) support and niobiumtitanium complex oxides among others.
In this thesis, zirconium based catalysts were systematically studied to understand the possibility of achieving enhanced ORR activity using a non platinum group metal (nonPGM) transition metal catalyst using Density Functional Theory (DFT).
In the first study, DFT was used to explore the viability of zirconium oxynitride as an ORR catalyst. The catalyst surface was studied systematically to explore the presence of active catalytic sites along with computation of adsorption energies of various intermediates. For ORR the adsorption energies of different intermediates, irrespective of the catalyst material, are related by the socalled standard scaling relations. We explored the possibility of deviation from the standard scaling relations for ORR taking place over zirconium oxynitride catalyst which can give rise to enhanced electrocatlysis.
In the second study, we explored electronic descriptors in order to predict adsorption energy of the ORR intermediates and consequently the ORR activity over zirconium based catalysts. During the course of our first study, we studied several electronic descriptors, however none of them could fully capture the complexity of the zirconium oxynitride catalyst surface. Integrated crystal orbital Hamiltonian population (ICOHP) had been previously successfully used as an electronic descriptor to understand trends in O* and OH adsorption on transition metal oxides. Hence, we investigated ICOHP as an electronic descriptor for a simplified model catalyst system, i.e anion substituted zirconia.