(661b) Competition between Mononuclear and Binuclear Copper Sites across Different Zeolite Topologies | AIChE

(661b) Competition between Mononuclear and Binuclear Copper Sites across Different Zeolite Topologies


Wijerathne, A. - Presenter, University of Virginia
Daya, R., Cummins Inc.
Sawyer, A., University of Virginia
Competition between monomers and dimers affects the reactivity of Cu-exchanged zeolites for applications such as the methane-to-methanol (MTM) reaction and high-temperature selective catalytic reduction of NOx. The Al distribution in a zeolite is kinetically controlled during synthesis, and Cu speciation is primarily thermodynamically controlled during the ion exchange. We used density functional theory (DFT) calculations and ab initio thermodynamics to predict the percentage of Cu dimers formed in chabazite (CHA) and mordenite (MOR). MOR has shown higher Cu efficiency than CHA for MTM, where the active sites are proposed to be Cu dimers. We hypothesized that a higher Cu dimer population is responsible for the higher Cu efficiency of Cu-MOR.

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.