Transport diffusivity of propane and propylene inside SWNTs from equilibrium molecular dynamics simulations

文献信息

发布日期 2014-09-29
DOI 10.1039/C4CP03881A
影响因子 3.676
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摘要

The gas transport of two model gases (propane and propylene) inside the single-walled nanotubes (SWNTs) of various diameters was systematically investigated using the molecular dynamics (MD) simulations. The thermodynamic factor can be obtained directly from equilibrium MD simulations following the newly-minted method proposed by Schnell et al. (Chem. Phys. Lett., 2011, 504, 199–201). This process eliminates the need to implement the tedious and challenging Monte Carlo simulations for the adsorption isotherm, from which the thermodynamic factor is usually extracted. The satisfactory agreement between simulation and the literature is found for self-diffusivity, corrected diffusivity and transport diffusivity, as well as for the thermodynamic factor. The ideal selectivity for a propane–propylene mixture through SWNT membranes could be optimized through adjusting the concentration gradient. This method can be readily extended to the binary and multiple-component systems.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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