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Effect of Solvent on the Local Structure, Dynamics, and Vibrational Density of States in Sn-BEA Zeolite

  • Woodrow Wilson
  • , John Michael Lane
  • , William Humphreys
  • , Vivek Bharadwaj
  • , Neeraj Rai
  • Mississippi State University
  • University of Alabama, Tuscaloosa

Research output: Contribution to journal › Article › peer-review

Abstract

Lewis acid zeolites are attractive catalysts for epoxidation and biomass valorization, as they are highly active and selective in the liquid phase and can operate at or near ambient conditions. While a rich experimental literature exists on liquid-phase Lewis acid zeolite catalysis, our understanding of the molecular organization and solvent dynamics in the vicinity of Lewis acid sites with differing metal site speciation remains limited. In this work, we investigate the molecular coordination and diffusion of two common solvents (methanol and water) around the closed and open Sn-BEA zeolite active sites using molecular dynamics simulations with a machine-learned interatomic potential trained on ab initio molecular dynamics trajectories. Molecular dynamics simulations reveal that introducing active sites significantly enhances local order in the first and second solvation shells compared to the pure silica case. For methanol, both closed and open active sites are singly coordinated, while more than two water molecules coordinate the open site. In contrast to methanol, we observed that water molecules dissociate, leading to the formation of additional Sn-OH and silanol groups away from the active site. The diffusion coefficients of water and methanol are functions of the solvent population in the pore. Our work provides insights into how active site speciation in Lewis acid zeolites affects solvent coordination, diffusion, and vibrational signature. This information is foundational for catalyst design and optimization of liquid-phase catalytic processes in zeolites. It also demonstrates the suitability of machine-learned interatomic potentials for modeling reactive systems, enabling sufficiently long trajectories for appropriate statistical averaging.
Original languageAmerican English
Pages (from-to)6715-6728
Number of pages14
JournalJournal of Physical Chemistry C
Volume130
Issue number19
DOIs
StatePublished - 2026

NLR Publication Number

  • NLR/JA-2800-96082

Keywords

  • condensed phase catalysis
  • density functional theory
  • Lewis acid zeolites
  • machine-learned interatomic potentials
  • reactive molecular dynamics

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