(296d) Design of Single Atom Catalysts for Ammonia Oxidation Using Density Functional Theory Calculations and Machine Learning

One of the current state-of-the-art technologies to produce green H₂ gas is through H₂O electrolysis, where H₂O is oxidized to O₂ at the anode (E^â—¦=1.23 V_RHE) and H₂ is produced at the cathode (E^â—¦=0.00 V_RHE) with the required thermodynamic potential of 1.23 V_RHE. Alternatively, ammonia (NH₃) oxidation (E^â—¦=0.07 V_RHE) can take place at the anode, reducing the required potential by 94 % compared to the H₂O electrolysis. Further, diverse materials can potentially be utilized for the catalysis since the working potential is less oxidizing compared to H₂O oxidation, in which catalytic materials are generally limited to oxides. Pt catlaysts demonstrated decent catalytic activities for NH₃ oxidation with the observed overpotential of 0.6 V, and alloying Pt with Ir and Ru further reduced the overpotential by 0.3 V (J. Power Sources, 142, 2005). Unfortunately, however, a systematic study to understand challenges in NH₃ oxidation is currently unavailabe in literature.

In this talk, I will first discuss our computational results on pure metal surfaces to understand the challenges in NH₃ oxidation and to provide a catalyst deisgn strategy. I will also discuss the application of the suggested strategy to design active single atom catalysts based on low dimensional materials using density functional theory calculations and machine learning.