Computational Study on the Performance of Iron-Polypyridine Catalysts in Artificial Photosynthesis

As contemporary society faces increasingly difficult challenges arising from climate change, devising means for the reduction of anthropogenic greenhouse emissions has become a focal point of research. The reduction of CO2 to profitable products such as CO is a promising means to that end. Unfortunately, the highly inert CO2 makes this endeavour practically impossible without the use of sophisticated catalytic procedures. Iron-polypyridine (FePP) complexes, were found to be promising candidates, triggering a race to find the optimal catalytic system. Computational studies (including by me) have provided essential insights to groups in this race but have so far been solely used to rationalise experimental results. By combining my in-depth knowledge on the computational investigation of transition metal complexes with the Rulíšek group’s expertise in the handling large chemical sampling spaces and the description of solvation effects and the IOCB’s vast computational resources, we propose a proactive computational investigation into the space of potential FePP catalysts. Therein, we will use a robust quantum chemical protocol, tested in the investigation of FePP properties, in combination with a stepwise elimination procedure to evaluate the expectable suitability of a large sampling space of FePP catalysts w.r.t. the reduction of CO2 to CO. We will further use these data to elucidate the relevance of the chemical features of the FePP class for this reduction reaction. We expect that our data will considerably advance the race for the most active, cost-efficient and selective catalyst for the reduction of CO2 and, therefore, accelerate the development of economical applications the significantly reduce human CO2 emissions. Personally, this project will enhance my scientific knowledge as well as my presentation and tutoring skills, thereby boosting my development as an independent researcher.