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We study & design catalysts (and other energy materials) purely based on computational methods.

Recent advances in computing power mean that it is now possible to tackle complex scientific challenges using computational methods.

We mainly employ density functional theory (DFT) and micro-kinetic modeling (MKM) to take a meaningful step toward achieving the ultimate goal in the field of catalysis, the rational design of catalyst materials.

DFT calculations are used to examine catalytic reactions on atomic scale, and investigate the differences in the reaction energetics among different catalysts.


By utilizing scaling properties of adsorption energies across different catalysts, we can substantially reduce the number of calculations required to estimate the entire reaction energetics for any other catalysts of interests.

We then develop a micro-kinetic model to explicitly calculate the kinetics (reaction rates) of catalytic reactions under various conditions.


By incorporating the scaling properties of adsorption energies in the micro-kinetic model, variations in catalytic activity and selectivity from one catalyst to the next can be mapped as functions of only a few descriptors resulting in so-called “volcano plots”.


Based on these volcano plots, we can not only provide guiding principles to improve current catalysts, but also conveniently identify new promising catalyst materials for more efficient energy storage and conversion.

A similar approach can be taken to design other energy materials such as batteries and photovoltaics.