C 2 Product Formation over the C 1 Product and HER on the 111 Plane of Specific Cu Alloy Nanoparticles Identified through Multiparameter Optimization.
Asif IqbalAnjana TripathiRanjit ThapaPublished in: Inorganic chemistry (2024)
C 2 products are more desirable than C 1 products during CO 2 electroreduction (CO 2 ER) because the former possess higher energy density and greater industrial value. For CO 2 ER, Cu is a well-known catalyst, but the selectivity toward C 2 products is still a big challenge for researchers due to complex intermediates, different final products, and large space of the catalyst due to its morphology, plane, size, host surface etc. Using density functional theory (DFT) calculations, we find that alloying of Cu nanoparticles can help to enhance the selectivity toward C 2 products during CO 2 ER with a low overpotential. By a systematic investigation of 111 planes (which prefer the C 1 product in the case of bulk Cu), the alloys show the generation of C 2 products via *CO-*CO dimerization (* indicates adsorbed state). It also suppresses the counter-pathway of hydrogenation of *CO to *CHO, which leads to C 1 products. Further, we find that *CH 2 CHO is the bifurcating intermediate to distinguish between ethanol and ethylene as the final product. We have used simple graphical construction to identify the catalyst for CO 2 ER over HER, and vice versa. We have also defined the case of hydrogen poisoning and projected a parity plot to recognize the catalyst for C 2 product evolution over the C 1 product. Our study reveals that Cu-Ag and Cu-Zn catalysts selectively promote ethanol production on 111 planes. Moreover, an edge-doped 2SO 2 graphene nanoribbon as the host layer further lowers the barrier and selectively promotes ethanol on Cu 38 - and Cu 79 -based alloys. This work provides new theoretical insights into designing Cu-based nanoalloy catalysts for C 2 product formation on the 111 plane.
Keyphrases
- metal organic framework
- highly efficient
- density functional theory
- aqueous solution
- room temperature
- visible light
- molecular dynamics
- estrogen receptor
- reduced graphene oxide
- quantum dots
- breast cancer cells
- signaling pathway
- risk assessment
- gold nanoparticles
- climate change
- heavy metals
- machine learning
- deep learning
- big data
- walled carbon nanotubes