Acknowledgement
본 논문은 산업통상자원부 및 산업기술평가관리원의 지원(20019441)과 정부(교육부)의 재원으로 한국연구재단의 지원(No. 2020R1A6A03038697)을 받아 수행됨.
References
- H. Strathmann, Introduction to Membrane Science and Technology, Wiley, Weinheim, Germany (2011).
- A. Basile and C. Charcosset, Integrated membrane systems and processes, Wiley, Newark, California (2015).
- K. P. Lee, T. C. Arnot, and D. Mattia, A review of reverse osmosis membrane materials for desalination-Development to date and future potential, J. Membr. Sci. 370, 1-22 (2011). https://doi.org/10.1016/j.memsci.2010.12.036
- S. Krishna, I. Sreedhar, and C. M. Patel, Molecular dynamics simulation of polyamide-based materials -A review, Comput. Mater. Sci., 200, 110853 (2021). https://doi.org/10.1016/j.commatsci.2021.110853
- D. Cohen-Tanugi and J. C. Grossman, Nanoporous graphene as a reverse osmosis membrane: Recent insights from theory and simulation, Desalination, 366, 59-70 (2015). https://doi.org/10.1016/j.desal.2014.12.046
- S. L. Mayo, B. D. Olafson, and W. A. Goddard, DREIDING: A generic force field for molecular simulations, J. Phys. Chem., 94, 8897-8909 (1990). https://doi.org/10.1021/j100389a010
- H. Sun, P. Ren, and J. R. Fried, The COMPASS force field: Parameterization and validation for phosphazenes, Comput. Theor. Polym. Sci., 8, 229-246 (1998). https://doi.org/10.1016/S1089-3156(98)00042-7
- P. Cieplak, C. I. Bayly, I. R. Gould, K. M. Merz, D. M. Ferguson, D. C. Spellmeyer, T. Fox, J. W. Caldwell, and P. A. Kollman, A 2nd generation force-field for the simulation of proteins, nucleic-acids, and organic-molecules, J. Am. Chem. Soc., 117, 5179- 5197 (1995). https://doi.org/10.1021/ja00124a002
- A. D. MacKerell, D. Bashford, M. Bellott, R. L. Dunbrack, J. D. Evanseck, M. J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, D. Joseph-McCarthy, L. Kuchnir, K. Kuczera, F. T. K. Lau, C. Mattos, S. Michnick, T. Ngo, D. T. Nguyen, B. Prodhom, W. E. Reiher, B. Roux, M. Schlenkrich, J. C. Smith, R. Stote, J. Straub, M. Watanabe, J. Wiorkiewicz-Kuczera, D. Yin, and M. Karplus, All-atom empirical potential for molecular modeling and dynamics studies of proteins, J. Phys. Chem. B, 102, 3586-3616 (1998). https://doi.org/10.1021/jp973084f
- J. Wang, R. M. Wolf, J. W. Caldwell, P. A. Kollman, and D. A. Case, Development and testing of a general Amber force field, J. Comput. Chem., 25, 1157-1174 (2004). https://doi.org/10.1002/jcc.20035
- D. Kony, W. Damm, S. Stoll, and W. F. Van Gunsteren, An improved OPLS-AA force field for carbohydrates, J. Comput. Chem., 23, 1416-1429 (2002). https://doi.org/10.1002/jcc.10139
- K. Gaedt and H.-D. H ltje, Consistent valence force-field parameterization of bond lengths and angles with quantum chemical ab initio methods applied to some heterocyclic dopamine D3-receptor agonists, J. Comput. Chem., 19, 935-946 (1998). https://doi.org/10.1002/(SICI)1096-987X(199806)19:8<935::AID-JCC12>3.0.CO;2-6
- S. Plimpton, Fast Parallel Algorithms for Short-Range Molecular Dynamics, J. Comput. Phys., 117, 1-19 (1995). https://doi.org/10.1006/jcph.1995.1039
- D. Van Der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark, and H. J. C. Berendsen, GROMACS: Fast, flexible, and free, J. Comput. Chem., 26, 1701-1718 (2005). https://doi.org/10.1002/jcc.20291
- Materials Studio, BIOVIA Inc.: San Diego, CA.
- J. C. Phillips, D. J. Hardy, J. D. C. Maia, J. E. Stone, J. V. Ribeiro, R. C. Bernardi, R. Buch, G. Fiorin, J. Henin, W. Jiang, R. McGreevy, M. C. R. Melo, B. K. Radak, R. D. Skeel, A. Singharoy, Y. Wang, B. Roux, A. Aksimentiev, Z. Luthey-Schulten, L. V. Kale, K. Schulten, C. Chipot, and E. Tajkhorshid, Scalable molecular dynamics on CPU and GPU architectures with NAMD, J. Chem. Phys., 153, 044130 (2020). https://doi.org/10.1063/5.0014475
- D. A. Case, T. E. Cheatham, T. Darden, H. Gohlke, R. Luo, K. M. Merz, A. Onufriev, C. Simmerling, B. Wang, and R. J. Woods, The Amber biomolecular simulation programs, J. Comput. Chem., 26, 1668-1688 (2005). https://doi.org/10.1002/jcc.20290
- M. Ding, A. Szymczyk, F. Goujon, A. Soldera, and A. Ghoufi, Structure and dynamics of water confined in a polyamide reverse-osmosis membrane: A molecular-simulation study, J. Membr. Sci., 458, 236-244 (2014). https://doi.org/10.1016/j.memsci.2014.01.054
- N. Zhang, S. Chen, B. Yang, J. Huo, X. Zhang, J. Bao, X. Ruan, and G. He, Effect of hydrogen-bonding interaction on the arrangement and dynamics of water confined in a polyamide membrane: A molecular dynamics simulation, J. Phys. Chem. B, 122, 4719-4728 (2018). https://doi.org/10.1021/acs.jpcb.7b12790
- M. Shen, S. Keten, and R. M. Lueptow, Dynamics of water and solute transport in polymeric reverse osmosis membranes via molecular dynamics simulations, J. Membr. Sci., 506, 95-108 (2016). https://doi.org/10.1016/j.memsci.2016.01.051
- Y. Song, F. Xu, M. Wei, and Y. Wang, Water flow inside polamide reverse osmosis membranes: A non-equilibrium molecular dynamics study, J. Phys. Chem. B, 121, 1715-1722 (2017). https://doi.org/10.1021/acs.jpcb.6b11536
- Z. E. Hughes and J. D. Gale, A computational investigation of the properties of a reverse osmosis membrane, J. Mater. Chem., 20, 7788-7799 (2010). https://doi.org/10.1039/c0jm01545h
- Y. Luo, E. Harder, R. S. Faibish, and B. Roux, Computer simulations of water flux and salt permeability of the reverse osmosis FT-30 aromatic polyamide membrane, J. Membr. Sci., 384, 1-9 (2011). https://doi.org/10.1016/j.memsci.2011.08.057
- H. Ebro, Y. M. Kim, and J. H. Kim, Molecular dynamics simulations in membrane-based water treatment process: A systematic overview, J. Membr. Sci., 438, 112-125 (2013). https://doi.org/10.1016/j.memsci.2013.03.027
- Y. Xiang, Y. Liu, B. Mi, and Y. Leng, Hydrated polyamide membrane and its interaction with alginate: A molecular dynamics study, Langmuir, 29, 11600-11608 (2013). https://doi.org/10.1021/la401442r
- Z. E. Hughes and J. D. Gale, Molecular dynamics simulations of the interactions of potential foulant molecules and a reverse osmosis membrane, J. Mater. Chem., 22, 175-184 (2012). https://doi.org/10.1039/c1jm13230j
- M. S. J. Sajib, Y. Wei, A. Mishra, L. Zhang, K.-I. Nomura, R. K. Kalia, P. Vashishta, A. Nakano, S. Murad, and T. Wei, Atomistic simulations of biofouling and molecular transfer of a cross- linked aromatic polyamide membrane for desalination, Langmuir, 36, 7658-7668 (2020). https://doi.org/10.1021/acs.langmuir.0c01308
- T. Yoshioka, K. Kotaka, K. Nakagawa, T. Shintani, H.-C. Wu, H. Matsuyama, Y. Fujimura, and T. Kawakatsu, Molecular dynamics simulation study of polyamide membrane structures and RO/FO water permeation properties, Membranes, 8, 127 (2018). https://doi.org/10.3390/membranes8040127
- D. Cohen-Tanugi and J. C. Grossman, Water desalination across nanoporous graphene, Nano Lett., 12, 3602-3608 (2012). https://doi.org/10.1021/nl3012853
- D. Konathan, J. Yu, T. A. Ho, and A. Striolo, Simulation insights for graphene-based water desalination membranes, Langmuir, 29, 11884-11897 (2013). https://doi.org/10.1021/la4018695
- D. Cohen-Tanugi and J. C. Grossman, Mechanical strength of nanoporous graphene as a desalination membrane, Nano Lett., 14, 6171-6178 (2014). https://doi.org/10.1021/nl502399y
- S. C. O'Hern, M. S. H. Boutilier, J.-C. Idrobo, Y. Song, J. Kong, T. Laoui, M. Atieh, and R. Karnik, Seletive ionic transport through tunable subnanometer poresin single-layer graphene membranes, Nano Lett., 14, 1234-1241 (2014). https://doi.org/10.1021/nl404118f
- Y. Liu and X. Chen, Mechanical properties of nanoporous graphene membrane, J. Appl. Phys., 115, 034303 (2014). https://doi.org/10.1063/1.4862312
- E. Harder, D. E. Walters, Y. D. Bodnar, R. S. Faibish, and B. Roux, Molecular dynamics study of a polymeric reverse osmosis, J. Phys. Chem. B, 113, 10177-10182 (2009). https://doi.org/10.1021/jp902715f
- L. Malaeb and G. M. Ayoub, Reverse osmosis technology for water treatment: State of the art review, Desalination, 267, 1-8 (2011). https://doi.org/10.1016/j.desal.2010.09.001
- Z. He, J. Zhou, X. Lu, and B. Corry, Bioinspired graphene nanopores with voltage-tunable ion selectivity for Na+ and K+, ACS Nano, 7, 10148-10157 (2013). https://doi.org/10.1021/nn4043628