Exploring the guest–host relationship for zeolite Y: a synergistic structural and theoretical investigation

Abstract

Understanding the mobility and distribution of cations in the presence of additional guest species within the zeolite framework is inherently very complex because several thermal and chemical processes occur simultaneously. In this study, the dehydration of zeolite Na-Y was studied using in situ powder X-ray diffraction (XRD). The crystal structure parameters, both the evolution of lattice parameters and the occupancies of sodium at specific positions in the model, were monitored upon heating. A complementary computational study was performed to understand interactions between the framework, cations, and water at the molecular level. Grand Canonical Monte Carlo (GCMC) simulations provided initial insights into water adsorption. Machine Learning Potentials (MLPs) were then trained to the ab initio Potential Energy Surface (PES) using a deep neural network, modeling the dynamics of the framework and cations at various water loadings. Strong agreement between computational results and experimental data reveal that upon dehydration, zeolite Na-Y initially contracts due to water removal, but subsequently expands as sodium cations migrate to the double 6-membered rings (site I). This study demonstrates significant benefits of integrating parametric Rietveld refinement and Machine Learning assisted Molecular Dynamics simulations in understanding dynamic behavior of guest molecules in nanoporous materials at operating conditions and interpreting complex and convoluted experimental data.