(661b) Competition between Mononuclear and Binuclear Copper Sites across Different Zeolite Topologies
AIChE Annual Meeting
2023
2023 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Data Science and Machine Learning Approaches to Catalysis I: Data-enhanced Multiscale Simulations
Monday, November 6, 2023 - 8:36am to 8:54am
To test our hypothesis, we modeled the partition of exchanged Cu2+ into monomers and dimers. We considered multiple species (Figure1 a-f) for ion exchanged Cu2+ based on previous studies and used a machine learning interatomic potential and a classical force field to accelerate and minimize the number of DFT calculations required for Cu exchange energy evaluations. We found that for a random Al distribution, Cu dimer formation is more favorable (Figure 1 g-h) in MOR than in CHA. In CHA, Cu is primarily exchanged as monomers in six-membered rings, and Cu dimers are formed only at higher Cu loadings (>1% wt.). In contrast, exchanged Cu2+ in MOR formed a mixture of dimers and monomers even at lower Cu loadings (<0.05 % wt.), resulting in a higher proportion of Cu dimers at a given Cu loading. Higher populations of Cu dimers in MOR materials could explain why MOR is more active for MTM. We then extended this workflow to BEA, AFX, and FER zeolites, and used these data combined with CHA and MOR to generate a predictive model for dimer probabilities of other zeolite topologies, without the need for DFT calculations.