The Mathematical Catalysis Research Team at NIMS is trying to understand the kinetics of electrocatalytic reactions using mathematics, data science, and experiments. We understand what happens when we throw a ball. We can predict the exact trajectory, including when and where it will land. Can we understand catalytic reactions in the same way? Our target is chemistry for sustainable energy applications, but by borrowing techniques from mathematics and data science, we will turn catalysis from a qualitative art into a predictive science.

[Examples of Target Challenges]
How can kinetic mechanisms of catalytic reactions be inferred from experimental data?
How can experiments and theory be combined to make predictive models of catalysis?
What kind of universal principles underly catalysis?
How can chemical reaction network theory be incorporated to yield new data analysis algorithms?
Are there physical limitations on the rate and longevity of catalytic systems?
What kind of chemical reaction networks maximize efficiency and sustainability?

We use mathematics, data science, and advanced experimental techniques such as in-situ spectroscopy to understand the kinetics of electrocatalytic reactions. Further details on our work can be found from the lab HP（URL）or Google Scholar（URL）.