The study of multilayer graphene membrane performance in O2 purification process: Molecular dynamics simulation

  • Mohammad Pour Panah Department of Physics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran 14115-111, Iran
  • Bahman Parvandar Asadollahi Mechanical Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-83151, Iran
  • Roozbeh Sabetvand Department of Energy Engineering and Physics, Faculty of Condensed Matter Physics, Amirkabir University of Technology, Tehran 159163-4311, Iran
Ariticle ID: 298
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Keywords: graphene; atomic membrane; molecular dynamics; purification process; oxygen; carbon dioxide

Abstract

We use molecular dynamics (MD) method to describe the atomic behavior of Graphene nanostructure for Oxygen molecules (O2) separation from Carbon dioxide (CO2) molecules. Technically, for the simulation of graphene-based membrane and O2-CO2 gas mixture, we used Tersoff and DREIDING force fields, respectively. The result of equilibrium process of these structures indicated the good stability of them. Physically, this behavior arises from the appropriate MD simulation settings. Furthermore, to describe the purification performance of graphene-based membrane, we report some physical parameters such as purification value, impurity rate, and permeability of membrane after atomic filtering process. Numerically, by defined membranes optimization, the purification value of them reach to 97.31%. Also, by using these atomic structures the CO2 impurity which passed from graphene-based membrane reach to zero value.

References

[1] Bunch JS, Verbridge SS, Alden JS, et al. Impermeable Atomic Membranes from Graphene Sheets. Nano Letters. 2008; 8(8): 2458-2462. doi: 10.1021/nl801457b

[2] Gilje S, Han S, Wang M, et al. A Chemical Route to Graphene for Device Applications. Nano Letters. 2007; 7(11): 3394-3398. doi: 10.1021/nl0717715

[3] Schniepp HC, Li JL, McAllister MJ, et al. Functionalized Single Graphene Sheets Derived from Splitting Graphite Oxide. The Journal of Physical Chemistry B. 2006; 110(17): 8535-8539. doi: 10.1021/jp060936f

[4] Zhou F, Fathizadeh M, Yu M. Single- to Few-Layered, Graphene-Based Separation Membranes. Annual Review of Chemical and Biomolecular Engineering. 2018; 9(1): 17-39. doi: 10.1146/annurev-chembioeng-060817-084046

[5] Geim AK, Novoselov KS. The rise of graphene. Nature Materials. 2007; 6(3): 183-191. doi: 10.1038/nmat1849

[6] Peres NMR, Ribeiro RM. Focus on graphene. New Journal of Physics. 2009; 11(9): 095002. doi: 10.1088/1367-2630/11/9/095002

[7] Boehm HP, Setton R, Stumpp E. Nomenclature and terminology of graphite intercalation compounds (IUPAC Recommendations 1994). Pure and Applied Chemistry. 1994; 66(9): 1893-1901. doi: 10.1351/pac199466091893

[8] Harris P. Transmission Electron Microscopy of Carbon: A Brief History. C. 2018; 4(1): 4. doi: 10.3390/c4010004

[9] Nair RR, Blake P, Grigorenko AN, et al. Fine Structure Constant Defines Visual Transparency of Graphene. Science. 2008; 320(5881): 1308-1308. doi: 10.1126/science.1156965

[10] Lee C, Wei X, Kysar JW, et al. Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene. Science. 2008; 321(5887): 385-388. doi: 10.1126/science.1157996

[11] Tsang ACH, Kwok HYH, Leung DYC. The use of graphene based materials for fuel cell, photovoltaics, and supercapacitor electrode materials. Solid State Sciences. 2017; 67: A1-A14. doi: 10.1016/j.solidstatesciences.2017.03.015

[12] Qu L, Liu Y, Baek JB, et al. Nitrogen-Doped Graphene as Efficient Metal-Free Electrocatalyst for Oxygen Reduction in Fuel Cells. ACS Nano. 2010; 4(3): 1321-1326. doi: 10.1021/nn901850u

[13] Vivekchand SRC, Rout CS, Subrahmanyam KS, et al. Graphene-based electrochemical supercapacitors. Journal of Chemical Sciences. 2008; 120(1): 9-13. doi: 10.1007/s12039-008-0002-7

[14] Zhang LL, Zhou R, Zhao XS. Graphene-based materials as supercapacitor electrodes. Journal of Materials Chemistry. 2010; 20(29): 5983. doi: 10.1039/c000417k

[15] Li H, Zou L, Pan L, et al. Novel Graphene-Like Electrodes for Capacitive Deionization. Environmental Science & Technology. 2010; 44(22): 8692-8697. doi: 10.1021/es101888j

[16] Zhang D, Yan T, Shi L, et al. Enhanced capacitive deionization performance of graphene/carbon nanotube composites. Journal of Materials Chemistry. 2012; 22(29): 14696. doi: 10.1039/c2jm31393f

[17] Yin H, Zhao S, Wan J, et al. Three-Dimensional Graphene/Metal Oxide Nanoparticle Hybrids for High‐Performance Capacitive Deionization of Saline Water. Advanced Materials. 2013; 25(43): 6270-6276. doi: 10.1002/adma.201302223

[18] Cohen-Tanugi D, Grossman JC. Water Desalination across Nanoporous Graphene. Nano Letters. 2012; 12(7): 3602-3608. doi: 10.1021/nl3012853

[19] You Y, Sahajwalla V, Yoshimura M, et al. Graphene and graphene oxide for desalination. Nanoscale. 2016; 8(1): 117-119. doi: 10.1039/c5nr06154g

[20] Cohen-Tanugi D, Lin LC, Grossman JC. Multilayer Nanoporous Graphene Membranes for Water Desalination. Nano Letters. 2016; 16(2): 1027-1033. doi: 10.1021/acs.nanolett.5b04089

[21] Xue C, Wang X, Zhu W, et al. Electrochemical serotonin sensing interface based on double-layered membrane of reduced graphene oxide/polyaniline nanocomposites and molecularly imprinted polymers embedded with gold nanoparticles. Sensors and Actuators B: Chemical. 2014; 196: 57-63. doi: 10.1016/j.snb.2014.01.100

[22] Asgari A, Nguyen Q, Karimipour A, et al. Investigation of additives nanoparticles and sphere barriers effects on the fluid flow inside a nanochannel impressed by an extrinsic electric field: A molecular dynamics simulation. Journal of Molecular Liquids. 2020; 318: 114023. doi: 10.1016/j.molliq.2020.114023

[23] Ashkezari AZ, Jolfaei NA, Jolfaei NA, et al. Calculation of the thermal conductivity of human serum albumin (HSA) with equilibrium/non-equilibrium molecular dynamics approaches. Computer Methods and Programs in Biomedicine. 2020; 188: 105256. doi: 10.1016/j.cmpb.2019.105256

[24] Ghanbari A, Warchomicka F, Sommitsch C, et al. Investigation of the Oxidation Mechanism of Dopamine Functionalization in an AZ31 Magnesium Alloy for Biomedical Applications. Coatings. 2019; 9(9): 584. doi: 10.3390/coatings9090584

[25] Sabetvand R, Ghazi ME, Izadifard M. Studying temperature effects on electronic and optical properties of cubic CH3NH3SnI3 perovskite. Journal of Computational Electronics. 2020; 19(1): 70-79. doi: 10.1007/s10825-020-01443-3

[26] Cohen-Tanugi D, Grossman JC. Water Desalination across Nanoporous Graphene. Nano Letters. 2012; 12(7): 3602-3608. doi: 10.1021/nl3012853

[27] Cohen-Tanugi D, Lin LC, Grossman JC. Multilayer Nanoporous Graphene Membranes for Water Desalination. Nano Letters. 2016; 16(2): 1027-1033. doi: 10.1021/acs.nanolett.5b04089

[28] Kim HW, Yoon HW, Yoon SM, et al. Selective Gas Transport Through Few-Layered Graphene and Graphene Oxide Membranes. Science. 2013; 342(6154): 91-95. doi: 10.1126/science.1236098

[29] Wang J, Zhang P, Liang B, et al. Graphene Oxide as an Effective Barrier on a Porous Nanofibrous Membrane for Water Treatment. ACS Applied Materials & Interfaces. 2016; 8(9): 6211-6218. doi: 10.1021/acsami.5b12723

[30] Plimpton S. Fast Parallel Algorithms for Short-Range Molecular Dynamics. Journal of Computational Physics. 1995; 117(1): 1-19. doi: 10.1006/jcph.1995.1039

[31] Plimpton SJ, Thompson AP. Computational aspects of many-body potentials. MRS Bulletin. 2012; 37(5): 513-521. doi: 10.1557/mrs.2012.96

[32] Aktulga HM, Fogarty JC, Pandit SA, et al. Parallel reactive molecular dynamics: Numerical methods and algorithmic techniques. Parallel Computing. 2012; 38(4-5): 245-259. doi: 10.1016/j.parco.2011.08.005

[33] Brown WM, Wang P, Plimpton SJ, et al. Implementing molecular dynamics on hybrid high performance computers – short range forces. Computer Physics Communications. 2011; 182(4): 898-911. doi: 10.1016/j.cpc.2010.12.021

[34] Stukowski A. Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool. Modelling and Simulation in Materials Science and Engineering. 2009; 18(1): 015012. doi: 10.1088/0965-0393/18/1/015012

[35] Rapaport DC. The Art of Molecular Dynamics Simulation, 2nd ed. Cambridge University Press; 2004.

[36] Nosé S. A unified formulation of the constant temperature molecular dynamics methods. The Journal of Chemical Physics. 1984; 81(1): 511-519. doi: 10.1063/1.447334

[37] Hoover WG. Canonical dynamics: Equilibrium phase-space distributions. Physical Review A. 1985; 31(3): 1695-1697. doi: 10.1103/physreva.31.1695

[38] Mayo SL, Olafson BD, Goddard WA. DREIDING: a generic force field for molecular simulations. The Journal of Physical Chemistry. 1990; 94(26): 8897-8909. doi: 10.1021/j100389a010

[39] Tersoff J. New empirical approach for the structure and energy of covalent systems. Physical Review B. 1988; 37(12): 6991-7000. doi: 10.1103/physrevb.37.6991

[40] Lennard-Jones JE. On the Determination of Molecular Fields. Proceedings of the Royal Society of London. 1924; 106(738): 463–477.

[41] Cohen-Tanugi D, Grossman JC. Water permeability of nanoporous graphene at realistic pressures for reverse osmosis desalination. The Journal of Chemical Physics. 2014; 141(7). doi: 10.1063/1.4892638

[42] Nair RR, Wu HA, Jayaram PN, et al. Unimpeded Permeation of Water Through Helium-Leak–Tight Graphene-Based Membranes. Science. 2012; 335(6067): 442-444. doi: 10.1126/science.1211694

Published
2024-04-09
How to Cite
Pour Panah, M., Asadollahi, B. P., & Sabetvand, R. (2024). The study of multilayer graphene membrane performance in O2 purification process: Molecular dynamics simulation. Nano Carbons, 2(1), 298. https://doi.org/10.59400/n-c.v2i1.298
Section
Original Research Article