Literature DB >> 23781814

A hybrid perturbed-chain SAFT density functional theory for representing fluid behavior in nanopores.

Gulou Shen1, Xiaoyan Ji, Xiaohua Lu.   

Abstract

A hybrid statistical mechanical model, which is fully consistent with the bulk perturbed-chain statistical associating fluid theory (PC-SAFT) in describing properties of fluids, was developed by coupling density functional theory with PC-SAFT for the description of the inhomogeneous behavior of real chain molecules in nanopores. In the developed model, the modified fundamental measure theory was used for the hard sphere contribution; the dispersion free energy functional was represented with weighted density approximation by averaging the density in the range of interaction, and the chain free energy functional from interfacial statistical associating fluid theory was used to account for the chain connectivity. Molecular simulation results of the density profile were compared with model prediction, and the considerable agreement reveals the reliability of the proposed model in representing the confined behaviors of chain molecules in an attractive slit. The developed model was further used to represent the adsorptions of methane and carbon dioxide on activated carbons, in which methane and carbon dioxide were modeled as chain molecules with the parameters taken from the bulk PC-SAFT, while the parameters of solid surface were obtained from the fitting of gas adsorption isotherms measured experimentally. The results show that the model can reliably reproduce the confined behaviors of physically existing substances in nanopores.

Entities:  

Year:  2013        PMID: 23781814     DOI: 10.1063/1.4808160

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  1 in total

1.  Accelerate the Electrolyte Perturbed-Chain Statistical Associating Fluid Theory-Density Functional Theory Calculation With the Chebyshev Pseudo-Spectral Collocation Method. Part II. Spherical Geometry and Anderson Mixing.

Authors:  Yunhao Sun; Zhengxing Dai; Gulou Shen; Xiaohua Lu; Xiang Ling; Xiaoyan Ji
Journal:  Front Chem       Date:  2022-01-24       Impact factor: 5.221

  1 in total

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