(521aq) Bifunctional Fe/Co 2D Metal Organic Framework for Enhanced ORR and Oer Activity
AIChE Annual Meeting
2023
2023 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Poster Session: Catalysis and Reaction Engineering (CRE) Division
Wednesday, November 8, 2023 - 3:30pm to 5:00pm
Finding a sustainable bifunctional cheaper catalyst suitable for both the oxygen reduction (ORR) and evolution (OER) reactions has been a major shortcoming in both metal-air battery and fuel-cell technologies. These catalysts need to offer selectivity and stability on top of excellent activity to be able to compete with the current commercial catalyst. This work analyzes the activity and tuning of an inexpensive catalyst; a two-dimensional metal organic framework (2D-MOF) that has been recently synthesized experimentally. Utilizing ab initio spin-polarized DFT calculations, the dominating pathways and rate-limiting steps of the ORR/OER reactions have been simulated. The 2D-MOF was tuned through the addition of a graphene substrate and substrate doping. The 2D-MOF can be synthesized using various transition metals for the two-metal center active sites, however, only cobalt, iron, and a combination of the two metals were simulated in this work due to their history with promising ORR/OER activity. The Co-2D-MOFs were favorable towards OER while the Fe-2D-MOFs were favorable towards ORR. The results show that when the bimetallic Co/Fe-2D-MOF was supported by boron-doped graphene, the ORR overpotential of the Fe-site was found to be 0.56 eV and the OER overpotential of the Co-site was found to be 0.48 eV. The present study allows for us to understand the activity of the 2D-MOF and the effect that a substrate has towards ORR/OER activity.
Acknowledgments
Acknowledgment is made to the State Legislative Fund, New Mexico for financial support. This work used Stampede2 at TACC through allocation [TGDMR140131] from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation (NSF) grants #2138259, #2138286, #2138307, #2137603, and #2138296. This work also utilized resources from the University of Colorado Boulder Research Computing Group, which is supported by NSF (awards ACI-1532235 and ACI-1532236), the University of Colorado Boulder, and Colorado.