1 resultado para Gear selectivity

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The electrocatalytic reduction of CO2 (CO2RR) is a captivating strategy for the conversion of CO2 into fuels, to realize a carbon neutral circular economy. In the recent years, research has focused on the development of new materials and technology capable of capturing and converting CO2 into useful products. The main problem of CO2RR is given by its poor selectivity, which can lead to the formation of numerous reaction products, to the detriment of efficiencies. For this reason, the design of new electrocatalysts that selectively and efficiently reduce CO2 is a fundamental step for the future exploitation of this technology. Here we present a new class of electrocatalysts, designed with a modular approach, namely, deriving from the combination of different building blocks in a single nanostructure. With this approach it is possible to obtain materials with an innovative design and new functionalities, where the interconnections between the various components are essential to obtain a highly selective and efficient reduction of CO2, thus opening up new possibilities in the design of optimized electrocatalytic materials. By combining the unique physic-chemical properties of carbon nanostructures (CNS) with nanocrystalline metal oxides (MO), we were able to modulate the selectivity of CO2RR, with the production of formic acid and syngas at low overpotentials. The CNS have not only the task of stabilizing the MO nanoparticles, but the creation of an optimal interface between two nanostructures is able to improve the catalytic activity of the active phase of the material. While the presence of oxygen atoms in the MO creates defects that accelerate the reaction kinetics and stabilize certain reaction intermediates, selecting the reaction pathway. Finally, a part was dedicated to the study of the experimental parameters influencing the CO2RR, with the aim of improving the experimental setup in order to obtain commercial catalytic performances.