In-silico design of metal-carbonaceous catalysts for the CO2 transformation into added-value chemicals

Catalysts capable of converting carbon dioxide (CO2) into value-added chemicals have the potential to not only mitigate the high atmospheric CO2 concentration but also produce renewable fuels to relieve the shortage of energy. The task is challenging due to the inherent inertness of the CO2 molecule. The aim of this PhD project is the development of computational chemistry tools, based on quantum chemistry and machine learning methods, to aid the discovery of novel metal carbonaceous materials for the electro-catalytic reduction of CO2.