Valorization of CO2 to Fuel over MOFs derived SACs: A Machine Learning Guided Experimental Approach

HOME | RESEARCH AREAS

Canadian PI: Dr. Ali Seifitokaldani                                          

Canadian Institution: McGill University

Indian PI: Dr. Sounak Roy

Indian Institution: Birla Institute Technology and Science

Project Summary:

The electrocatalytic reduction of CO2 (ECR), powered by renewable electricity, is the promising strategy to not only mitigate high CO2 levels in the atmosphere, but also to valorize the greenhouse gas to high energy-density carbonaceous fuel. However, the state of the art is far from being optimal and the level of understanding of the mechanistic pathways leading to the products is very poor at present. Also, there are still considerable breakthroughs to be made before it can be considered as a viable economical process. In spite of rich literature, the reaction still suffers from low activity and poor product selectivity primarily due to a variety of multiple proton-coupled electron-transfer (PCET) processes, accompanied by the competitive hydrogen evolution reaction (HER). From the perspective of sustainable environment and economic value, formation of higher order multicarbon products (C2+) is more coveted than that of C1 products, owing to their higher energy densities and a wider applicability. But the reduction process remains extremely challenging due to the bottleneck of controlled C-C coupling over the catalyst surfaces.

This project focuses on designing and development of high surface area, porous and highly conducting metal organic framework (MOF) derived single atom catalysts (SAC) for ECR. The Canadian PI, Prof. Ali Seifitokaldani with the help of machine learning based on Density Functional Theory (DFT) computations proposed a series of potential SACs, while the Indian PI, Prof. Sounak Roy showed effective ECR with a wide range of MOF derived nano-materials. As the effective cleavage of C–O bond and efficient and controlled C–C coupling is the key step for the formation of selective product, our earlier studies indicated that constructing atom-precision active sites may benefit to selectively form the desired product. The experienced collaboration will facilitate fine tuning of the appropriate SAC materials for selective ECR to C2+ products, especially ethanol with high Faradaic Efficiency. In-situ spectroscopic studies along with DFT calculations will be made towards understanding the molecular mechanism with respect to the structural, morphological, and electronic properties of the synthesized SACs. The final aim will be to develop high-fidelity techno-economic-analysis and life cycle-assessment models to evaluate the economic and environmental benefits along with feasibility and scalability of the process.

Research Projects

IC-IMPACTS funded research is driven by a commitment to research excellence and supports the discovery and application of solutions to some of the most pressing issues in both Canadian and Indian communities.

GBM-CLIMPACT: Development of an end-to-end modeling and analysis toolset to assess climate impact and readiness of water sector in the Ganga, Brahmaputra, and Meghna basins

Canadian PI: Dr. Martyn Clark                                   Canadian Institution: University of Saskacthewan Indian PI: Dr. Manabendra Saharia…

Use of deep learning models to understand the impact of climate and land use changes on future groundwater resources, with a focus on data scarce regions.

Canadian PI: Dr. Jan Franklin Adamowski                                             Canadian Institution: Mcgill University Indian PI: Dr. R.Maheswaran Rathinasamy…

Machine learning methods for water quality estimation and control in water resource recovery facilities: Towards Circular Economy and Sustainability

Canadian PI: Dr. Peter Vanrolleghem                      Canadian Institution: Université Laval Indian PI: Dr. Seshagiri Rao Ambati…

FOLLOW US

Ornare quam viverra orci sagittis eu volutpat odio facilisis.

Latest news & article.

Ornare quam viverra orci sagittis eu volutpat odio facilisis.