Oleophobic nanopore in graphene membrane enhances CO2 capture and separation after spontaneous hydrocarbon adsorption

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Zonglin Gu, Wenjing Gao, Jia Chen, Shuming Zeng
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引用次数: 0

Abstract

Context

Membrane separation technology is a great candidate for capturing and separating CO2 from air and flue gas, aiming at combating global warming. In particular, numerous experimental and theoretical investigations have revealed the outstanding performance of porous graphene membrane in sieving CO2 due to its high-selectivity and energy-efficiency. Some experimental studies have confirmed that the graphene can be spontaneously contaminated by the hydrocarbons in ambient air, due to its large surface energy. However, how the covered hydrocarbons on porous graphene membrane affect the CO2 capture and separation remains elusive. In this study, we employed molecular dynamics (MD) simulation approach to investigate CO2/N2 separation capacity of the oleophobic N24 nanopores and the oleophilic C24 nanopores in graphene membrane after covering the oleaginous hydrocarbon, C8H18, films. Interestingly, our MD simulations demonstrate that the oleophobic N24 nanopore shows higher CO2 transport rate and CO2/N2 selectivity compared with the oleophilic C24 nanopore after the membrane adsorbed by C8H18 films, indicating that the oleophobic N24 graphene nanopore can ameliorate CO2 capture and separation upon C8H18 films adsorption. Mechanically, on the one hand, C8H18 can more likely block the C24 nanopore, due to the stronger affinity of C8H18 to the C24 pore, which results in the reduced gas transport rate. On the other hand, the quadrupole interaction between CO2 and N24 nanopore helps the favorable capture and separation of CO2 by N24 nanopore. The combined effect thus determines the better CO2 separation performance of hydrocarbon covered N24 nanopore. Therefore, our findings not only reveal the carbon capture and separation performance of porous graphene membrane upon spontaneously adsorbing hydrocarbon from the ambient air or the flue gas for the first time, but also exploit the oleophobic nanopore capable of ameliorating the membrane capacity, which is beneficial to future practical application of porous graphene membrane in CO2 separation.

Methods

We conducted all MD simulations with GROMACS software package. VMD software package was used to visualizing the simulation conformations and trajectories. Periodic boundary conditions were applied in all directions (x, y, and z). Temperature was constrained at 350 K using the v-rescale thermostat. Long-range electrostatic interactions were computed using the PME method, and van der Waals (vdW) interactions were calculated with a cutoff distance of 12 Å. Bonds involving hydrogen atoms were constrained to their equilibrium values using the LINCS algorithm. 

石墨烯膜上的疏油纳米孔增强了自发碳氢吸附后CO2的捕获和分离
膜分离技术是从空气和烟气中捕获和分离二氧化碳的一个很好的候选技术,旨在对抗全球变暖。特别是,大量的实验和理论研究表明,多孔石墨烯膜由于其高选择性和高能效而具有出色的CO2筛分性能。一些实验研究证实,由于石墨烯具有较大的表面能,它可以被周围空气中的碳氢化合物自发污染。然而,多孔石墨烯膜上覆盖的碳氢化合物如何影响CO2的捕获和分离仍然是一个谜。在这项研究中,我们采用分子动力学(MD)模拟的方法研究了石墨烯膜上覆盖含油烃C8H18膜后,疏油纳米孔N24和亲油纳米孔C24的CO2/N2分离能力。有趣的是,我们的MD模拟表明,在膜被C8H18膜吸附后,疏油的N24纳米孔比亲油的C24纳米孔表现出更高的CO2输运率和CO2/N2选择性,这表明疏油的N24纳米孔可以改善C8H18膜吸附后CO2的捕获和分离。机械方面,一方面,C8H18对C24纳米孔的亲和力更强,更容易阻断C24纳米孔,导致气体输运率降低。另一方面,CO2与N24纳米孔之间的四极相互作用有利于N24纳米孔对CO2的捕获和分离。综合作用决定了碳氢化合物覆盖的N24纳米孔具有较好的CO2分离性能。因此,我们的研究结果不仅首次揭示了多孔石墨烯膜在自发吸附环境空气或烟气中的碳氢化合物时的碳捕获和分离性能,而且还开发了能够改善膜容量的疏油纳米孔,这有利于未来多孔石墨烯膜在CO2分离中的实际应用。方法采用GROMACS软件包进行MD模拟。利用VMD软件包对仿真构象和轨迹进行可视化。在所有方向(x, y和z)上应用周期性边界条件。使用v-rescale恒温器将温度限制在350 K。采用PME方法计算了远距离静电相互作用,并计算了截止距离为12 Å的范德华相互作用。使用LINCS算法将涉及氢原子的键约束到其平衡值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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