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使用富勒烯柱撑石墨烯纳米复合材料对CH、H、CO和N进行吸附分离:分子模拟的见解

Adsorptive separation of CH, H, CO, and N using fullerene pillared graphene nanocomposites: Insights from molecular simulations.

作者信息

Mert Humeyra, Deniz Celal Utku, Baykasoglu Cengiz

机构信息

Faculty of Engineering, Department of Polymer Materials Engineering, Hitit University, Çorum, Türkiye.

Faculty of Engineering, Department of Chemical Engineering, Hitit University, Cevre Yolu Avenue, 19030, Çorum, Türkiye.

出版信息

J Mol Model. 2023 Sep 14;29(10):315. doi: 10.1007/s00894-023-05715-0.

Abstract

CONTEXT

The adsorptive separation performances of fullerene pillared graphene nanocomposites (FPGNs) with tunable micro and meso porous morphology are investigated for the binary mixtures of CH, H, CO and N by using grand canonical Monte Carlo (GCMC) simulations. Different fullerene types are considered in designs as pillar to investigate the effects of porosity on the gas separation performances of FPGNs, and the GCMC simulations are performed for an equimolar binary mixture of CO/H, CO/CH, CO/N and CH/H inspired by industrial gas mixtures. It is found that CO/N, CO/H and CH/H selectivity of FPGNs are about 72, 410 and 145 at 298 K and 1 bar, which are higher than those for several adsorbent materials reported.

METHODS

Five different FPGN models which contain covalently bonded periodical fullerene and graphene units were constructed using C, C, C, C and C fullerenes, followed by geometry optimization using Open Babel. All GCMC simulations of adsorption were performed in the RASPA. The adsorption isotherms of FPGNs for pure gases are comparatively examined, and their performances are discussed based on the pore structure and isosteric heat of adsorption. Then, the separation factors of FPGNs for equimolar binary mixtures of these gases are elucidated from the difference in the heat of adsorption and the adsorption selectivity.

摘要

背景

通过巨正则蒙特卡罗(GCMC)模拟研究了具有可调微孔和介孔形态的富勒烯柱撑石墨烯纳米复合材料(FPGNs)对CH、H、CO和N二元混合物的吸附分离性能。在设计中考虑了不同类型的富勒烯作为柱撑,以研究孔隙率对FPGNs气体分离性能的影响,并针对受工业气体混合物启发的CO/H、CO/CH、CO/N和CH/H等摩尔二元混合物进行了GCMC模拟。研究发现,在298K和1bar条件下,FPGNs对CO/N、CO/H和CH/H的选择性分别约为72、410和145,高于已报道的几种吸附剂材料。

方法

使用C、C、C、C和C富勒烯构建了五个不同的包含共价键合周期性富勒烯和石墨烯单元的FPGN模型,然后使用Open Babel进行几何优化。所有吸附的GCMC模拟均在RASPA中进行。比较研究了FPGNs对纯气体的吸附等温线,并基于孔结构和吸附等量热讨论了它们的性能。然后,根据吸附热和吸附选择性的差异阐明了FPGNs对这些气体等摩尔二元混合物的分离因子。

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