(189j) Challenges and Strategies of Modeling Extra-Framework Metal Cations in Zeolites from First-Principles: Knowledge Learned from Cationic Iron Exchanged in SSZ-13 | AIChE

(189j) Challenges and Strategies of Modeling Extra-Framework Metal Cations in Zeolites from First-Principles: Knowledge Learned from Cationic Iron Exchanged in SSZ-13

Authors 

LI, S. - Presenter, University of Notre Dame
Schneider, W., University of Notre Dame
Metal-exchanged zeolites are widely used as catalysts for various practical applications. The extra-framework cationic metal centers dispersed throughout zeolite support are typically the active sites responsible for the catalysis. Quantum chemistry methods, e.g. density functional theory (DFT), become powerful as to computationally model these cations for rationalization of the corresponding catalytic functions. Accurate modeling, however, involves different challenges, ranging from the reliability of DFT in capturing correct electronic structures of metal cations and relevant properties, to the heterogeneity of the anionic support that charge-compensate metal cations, e.g. framework aluminum distribution and proximity, to the complexity of cation speciation locally, etc. In this work, we use our study on modeling cationic iron (Fe) siting and speciation in SSZ-13 zeolite as an example, to illustrate how these unavoidable challenges can lead to incomplete or even erroneous conclusions if not properly handled, and come up with corresponding strategies. Through benchmarking with wavefunction coupled-cluster method, we parameterize DFT functionals that are more reliable in predicting cationic Fe properties, e.g. coordination preference. A geometry enumeration algorithm is developed to ensure effective (avoiding redundant computational effort) and complete encompassing of Al proximity effect on metal cation siting. Local cation speciation is predicted through comprehensive sampling of cation species followed by ab inito thermodynamics analysis. Integration of these steps allows more systematic and accurate modeling of cationic Fe siting and speciation in SSZ-13, and the strategies are readily transferable to zeolitic metal cation modeling in general within any zeolite topologies of interest.