Objective
"The present-day chemicals industry heavily depends on fossil fuels, contributing significantly to the concerning rise in global CO2 emissions. However, for transitioning to renewables, large-scale and high energy-density energy storage is needed. The CO2 electroreduction reaction holds promise in this direction, due to its unique ability to convert waste CO2 emissions back into valuable base chemicals at ambient conditions, using renewable electricity. However, it currently lacks industrial adoption, due to the lack of highly selective and stable catalysts. Understanding the catalytic properties such as selectivity and stability at the atomic scale requires fundamental insights about the ""real"" catalyst structure under reaction conditions and its effects on the reaction mechanisms. The goal of this project is to investigate this structure sensitivity of the Cu-based CO2 electroreduction reaction by developing a structure-dependent microkinetic model. To achieve this, I will use Boltzmann statistics and DFT calculations to predict ensembles of Cu nanoparticles with thermodynamically most stable morphologies under experimental reaction conditions and account for the respective distribution of active sites. Thereafter, the reaction pathways towards key products such as hydrogen, methane and ethylene over the active sites will be investigated. The multiscale analysis based on the structure-dependent microkinetic modeling will connect the experimentally observed macroscopic reaction rates with the nanoscale true structure of the catalyst, revealing the structure-property relationships of the CO2 electroreduction catalyst. The potential outcomes are: 1) understanding how catalyst structure at the nanoscale affects its properties in the CO2 electroreduction process; 2) achieving a wider adoption of multiscale modelling as a tool for rational electrocatalyst design; and 3) establishing stronger collaborations between experimental and theoretical catalysis."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural scienceschemical sciencescatalysiselectrocatalysis
- natural scienceschemical sciencesorganic chemistryaliphatic compounds
- engineering and technologyenvironmental engineeringenergy and fuels
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
20133 Milano
Italy