AI Article Synopsis

  • Mass transport of chemical mixtures in nanoporous materials, like metal-organic frameworks (MOFs), is crucial for applications such as membrane separations, but experimentally measuring diffusion is difficult.
  • The paper tests the Skoulidas, Sholl, and Krishna (SSK) method for predicting multicomponent diffusion coefficients using molecular simulations of H₂/CH₄ mixtures in CuBTC.
  • Results show that the SSK method’s predictions align well with direct simulations, indicating its potential effectiveness for analyzing multicomponent diffusion in MOFs, alongside tests on other predictive methods for binary adsorption and diffusion.

Article Abstract

Mass transport of chemical mixtures in nanoporous materials is important in applications such as membrane separations, but measuring diffusion of mixtures experimentally is challenging. Methods that can predict multicomponent diffusion coefficients from single-component data can be extremely useful if these methods are known to be accurate. We present the first test of a method of this kind for molecules adsorbed in a metal-organic framework (MOF). Specifically, we examine the method proposed by Skoulidas, Sholl, and Krishna (SSK) ( Langmuir, 2003, 19, 7977) by comparing predictions made with this method to molecular simulations of mixture transport of H 2/CH 4 mixtures in CuBTC. These calculations provide the first direct information on mixture transport of any species in a MOF. The predictions of the SSK approach are in good agreement with our direct simulations of binary diffusion, suggesting that this approach may be a powerful one for examining multicomponent diffusion in MOFs. We also use our molecular simulation data to test the ideal adsorbed solution theory method for predicting binary adsorption isotherms and a method for predicting mixture self-diffusion coefficients.

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Source
http://dx.doi.org/10.1021/la800486fDOI Listing

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