Rate constant calculations for the photo-catalytic production of fuels from solar energy

• Applicant: Thomas Stecher, Ph.D.
• Subject Area: Theoretical Chemistry: Molecules, Materials, Surfaces
• Term: from 2015 to 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 271932321

The exploitation of solar energy is imperative if we are to reduce our dependence on fossil fuels. Traditionally, this is achieved via photovoltaic cells, which convert solar energy into electricity. While much of our energy consumption is in this form, electricity has two major drawbacks: it is difficult to store and it relies on grid infrastructure, which limits both time and place of its consumption. More recent research efforts have been investigating the possibility of converting solar energy directly into chemical fuels such as methanol or hydrogen, which are more easily stored and have the potential to replace fossil fuels in off-grid situations (e.g. cars). Finding efficient catalysts for these processes is a research-intensive task, but recent advances in computational modelling promise to streamline this screening process. Most existing models focus on the thermodynamic stability of the expected intermediate reaction species. While this can give a good first indication about the feasibility of a certain catalytic system, this description is incomplete. The proposed project will advance this state-of-the-art by taking dynamical effects, such as reaction barriers and proton-tunnelling, into account, which will allow the prediction of reaction rates. The resulting methodology will be very general and two distinct applications will be considered: (1) the reduction of CO2 on a pyridine catalyst and (2) water-splitting on metal-clusters. Efficient Density Functional Theory (DFT) methods will be employed to accurately describe electronic structure phenomena, such as breaking and forming of chemical bonds together with a Feynman path-integral description of the nuclear quantum statistics to describe proton-tunnelling effects. The considerable computational cost of combining a path-integral simulation with DFT will limit the amount of simulation data that can be produced. A key methodological challenge will thus be to extract accurate (free-energy) reaction barriers from this limited amount of data. This will be tackled with modern machine-learning techniques, adapted for the present purpose. The impact of the project will therefore not only lie in the application to the highly relevant technological problems outlined above, but the methods to be developed will themselves be of great interest to the wider field.

• DFG Programme: Research Grants