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Sodium Diffusion Through Aluminum-Doped Zeolite BEA System: Effect of Water Solvation

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Multiscale and Multiphysics Computational Frameworks for Nano- and Bio-Systems

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Abstract

To investigate the effect of hydration on the diffusion of sodium ions through the aluminum-doped zeolite BEA system (Si/Al = 30), we used the grand canonical Monte Carlo (GCMC) method to predict the water absorption into aluminosilicate zeolite structure under various conditions of vapor pressure and temperature, followed by molecular dynamics (MD) simulations to investigate how the sodium diffusion depends on the concentration of water molecules. The predicted absorption isotherm shows first-order-like transition, which is commonly observed in hydrophobic porous systems. The MD trajectories indicate that the sodium ions diffuse through zeolite porous structures via hopping mechanism, as previously discussed for similar solid electrolyte systems. These results show that above 15 wt % hydration (good solvation regime) the formation of the solvation cage dramatically increases sodium diffusion by reducing the hopping energy barrier by 25% from the value of 3.8 kcal/mol observed in the poor solvation regime.

Reprinted with permission from Kim, H; Deng, W.-Q.; Goddard, W. A.; Jang S. S.; Davis M. E.; Yan Y. J. Phys. Chem. C 2009, 113 (3), 819-826. Copyright 2009 American Chemical Society.

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Acknowledgments

This research was supported in part by the Department of Energy (DE-FG02-05ER15716, William S. Millman). The facilities of the Materials and Process Simulation Center used for these studies were supported by DURIP-ARO, DURIP-ONR.

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Authors and Affiliations

  1. Center for Materials Simulations & Design, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

    Hyungjun Kim

  2. Materials and Process Simulation Center, California Institute of Technology, Pasadena, USA

    Hyungjun Kim

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Kim, H. (2011). Sodium Diffusion Through Aluminum-Doped Zeolite BEA System: Effect of Water Solvation. In: Multiscale and Multiphysics Computational Frameworks for Nano- and Bio-Systems. Springer Theses. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7601-7_4

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