Aromatic Polyamide Reverse-Osmosis Membrane: An Atomistic

Sep 7, 2016 - Copyright © 2016 American Chemical Society ... Polyamide (PA) membrane-based reverse-osmosis (RO) serves as one of the most important ...
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Aromatic Polyamide Reverse Osmosis Membrane: An Atomistic Molecular Dynamic Simulation Tao Wei, Lin Zhang, Haiyang Zhao, Heng Ma, Md Symon Jahan Sajib, Hua Jiang, and Sohail Murad J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.6b06560 • Publication Date (Web): 07 Sep 2016 Downloaded from http://pubs.acs.org on September 13, 2016

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Aromatic Polyamide Reverse Osmosis Membrane: An Atomistic Molecular Dynamic Simulation Tao Wei,1 Lin Zhang,2* Haiyang Zhao,2 Heng Ma,1 Md Symon Jahan Sajib,1 Hua Jiang3 and Sohail Murad4* 1 Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX 77710, USA 2 Key Laboratory of Biomass Chemical Engineering of MOE, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou, 310027, China 3 Caerulean Environmental Technology Corporation, Tulsa, OK 74133, USA 4 Department of Chemical Engineering, Illinois Institute of Technology, IL, 60616, USA

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ABSTRACT: Polyamide (PA) membranes based reverse osmosis (RO) serves as one of the most important techniques for water desalination and purification. Fundamental understanding of polyamide (PA) reverse osmosis (RO) membranes at the atomistic level is critical to enhance their separation capabilities leading to significant societal and commercial benefits. In this paper, a fully-atomistic molecular dynamics (MD) simulation was performed to investigate PA membrane. Our simulated crosslinked membrane exhibits structural properties similar to those reported in experiments. Our results also reveal the presence of small local two-layer slip structures in PA membrane with 70% crosslinking, primarily due to short-range anisotropic interactions among aromatic benzene rings. Inside the inhomogeneous polymeric structure of the membrane, water molecules show heterogeneous diffusivities and converge adjacent to polar groups. Increased diffusion of water molecules is observed through the less crosslinked pathways. The existence of the fast pathways for water permeation has no effect on membrane’s salt rejections.

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1. INTRODUCTION

Desalination of brackish water and seawater serves as one of the most promising techniques to resolve the serious global issue of water shortage.1 Reverse osmosis (RO) is currently the most important desalination technology, accounting for over 50% of the installed capacity in the world.2 Aromatic polyamide (PA) thin-film membranes have been widely used with commercial success in water desalination and purification.3 PA reverse osmosis membrane consists of a PA thin film coating (thickness < 200 nm) to enable separation for water and ions or other impurities, and a polysulfone (PSF) substrate to provide mechanical support.4-5 PA membranes have high chemical resistance and structural robustness, which results in both tolerance to impurities and durability.3 Aromatic PA thin-film membranes offer water permeability of 3.5 × 10−9 m Pa−1 s−1 with salt rejection of over 99.6%.6 The current challenge is to further enhance water flux of RO polyamide membranes without compromising selectivity7-8. Membrane separation performance is highly correlated with membrane morphology and structure.9-11 Further investigations of the local structure and water diffusion inside the polyamide membrane at the microscopic level will facilitate the design of new PA membrane with improved efficiency. While recent experimental efforts have allowed improved characterization of polyamide thin films,11-15 it is still a challenge to probe atomistic / molecular details in thin films around a hundred nanometers.16 In the synthesis of PA membranes, trimesoyl chloride (TMC) monomers are initially hydrolyzed and then crosslinked with m-phenylenediamine (MPD) monomers at the solution interface. The crosslinking process of monomers takes place at the solution interface which involves the coupling of chemical reactions and diffusion. Phase-transfer catalysts are usually added to aid monomer diffusion.8, 17 The interfacial polymerization can take from a few seconds to a minute. Full atomistic molecular dynamics (MD) simulations are a promising alternative to

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provide additional insight on molecular transfer through nanoporous medium18-22. However, the time scale of polymerization process goes beyond the limitation of current full-atom MD simulations. Moreover, there is no theoretical approach available to handle chemical reactions including quantum-level effects, particularly at the solution-interfaces in the scale of nanometers. Empirical approaches have been employed in recent studies23-27 to model crosslinked polymeric structures in vacuum where bonding has been assumed in monomers when they bump into each other without incorporating the actual chemical kinetics. Several studies using MD simulations have been published on PA membrane performance, including ion diffusion24-25,

28

, water

structure and dynamics26-27, membrane fouling mechanism with different foulant molecules (such as glucose, phenol29 and alginate30) and different solutes (such as methanol, ethanol, 2propanol and urea)28. In this study, we report a fully atomistic MD simulation to investigate crosslinked PA membranes to complement experimental studies at the microscopic level. We first constructed the PA membrane structure by using a hierarchical crosslinking protocol in the vacuum followed by further relaxation through heating-annealing protocol in water. Next, based on the realistic membrane structure, we characterized and compared membrane’s properties from our simulation with experimental measurements, including density, monomer ratio, degree of crosslinking, water content, pore size distribution and salt rejection. Using a realistic membrane model, the membrane’s local structures were systematically analyzed. Another focus was to study the diffusive behavior of water inside the membrane. This fundamental study will facilitate future design of polyamide membranes with improved performance.

2. METHODS

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Atomistic MD simulations were performed by using the GROMACS package (version 4.6.5), CHARMM General Force Field and TIP3P water model.31 The methods of Nose-Hoover and Berendsen were used to maintain temperature in NVT and NPT ensembles at 298.15 K respectively with periodic boundary condition (PBC). Parrinello-Rahman method was used to keep the NPT ensemble at 1 bar. In our simulation, we ignored the solution effects on crosslinking and adopted a two-step procedure to aid computations. The steps included the initial self-assembly of crosslinked membrane in vacuum followed by its solvation to mimic the membrane’s swelling in water. In the first step we started with a mixture of MPD and hydrolyzed TMC (TMO) monomers at a range of ratios and densities. During crosslinking, the mixture configurations were relaxed via MD simulations in the NVT ensemble at 300 K. Polymerization in vacuum was defined based on atom-atom distance criteria, i.e., when the distance between C-atoms of COOH groups and Natoms of NH2 groups was less than 0.5 nm. To enhance computational efficiency, hierarchical crosslinking protocol was adopted (see Figure 1A and 1B). At the initial level, monomers’ crosslinking was initiated in a small cell (2.0 × 2.0 × 2.0 nm3) and then the small cell was expanded by duplicating itself along each axis. More crosslinking was carried out inside the expanded cell. The same procedure was repeated for three more levels until the targeted dimension of the simulation box was achieved. At each level, cross-linking was performed in PBC. The resulting polymer structure also went through five heating-annealing cycles32 during MD simulations using temperature variance between 300 K and 560 K, which is higher than PA glass transition temperature of 445-549 K.33-34 The polymer membrane was found to become homogeneous after about 100-ns in our NVT simulation. As the polymer crosslinking ratio increases, crosslinking with MD simulations becomes more computationally tenuous to achieve due to the increased

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steric hindrance for monomer diffusion. To increase the crosslinking efficiency, additional TMO residues are inserted into the dry membrane. The un-crosslinked TMO residues were finally removed from the simulation cell. The final dry polyamide membrane was found to have a density of 1.28 g/cm3, which is close to the values reported in literature.35 The overall crosslinking degree for the entire surface was 70%. In the second step, polymer membrane was solvated. Two water reservoirs were placed on both sides of the membrane (see Figure 1 (C)). Water molecules were randomly inserted inside the simulation box including the membrane. After the initial relaxation of water molecules during MD simulations of 20-ns at 298.15 K, the entire system was subjected to a heating-annealing protocol between 298.15 K and 368.15 K for four cycles. The solvated membrane system was further equilibrated in the NPT ensemble for another 130 ns at 298.15 K and 1 bar. The size of final equilibrated cell including polymer membrane and two water reservoirs was 8.39 × 8.55 × 21.11 nm3 (see Figure 1 (C)). The ratio of MPD and TMC was found to be 1.32 which is again close to the literature values (1.0-1.3)16, 24-27, 30

. The ratio of oxygen and nitrogen atom numbers in our simulation was 1.32, which agrees with

previous simulation reports (1.12-1.87)24, 30, 35. We note that in our system, the PSF support layer was not explicitly included, due to its negligible effect on the flux and selectivity of the membrane.

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Figure 1 Polyamide membrane: (A) the crosslinking reactions and definition of polymer degree, n (0 ≤ n ≤ 1; n = 1 for fully cross-linked polyamide and n = 0 for fully linear one); (B) hierarchical crosslinking process (totally 4 levels).

3. RESULTS AND DISCUSSION 3.1. Local Structure of Polyamide Membrane. The density profiles of water, polymer and overall system as measured across the membrane were monitored as shown in Figure 2A. The density distributions display fairly symmetrical patterns of crosslinked PA membranes. It can be observed that the polymer-water interface has a thickness of ~1.4 nm. The densities of water and polyamide atoms of the membrane interior are 0.251 ± 0.029 g/cm3 and 1.076 ± 0.049 g/cm3, respectively. The water content in bulk polyamide membrane is ~20.0% by weight, which is within the experimental range of 10 - 23%.23, 36-37 Figure 2B shows the pore size distribution (PSD) of the simulated PA membrane. This was calculated in the membrane’s interior region (8 nm < z < 11 nm) using the Monte Carlo approach38. The PSD was estimated as the statistical distribution of the radius of the largest sphere that can be inserted inside a pore at a given point.

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Our results show that the pore radius displays inhomogeneous distribution inside PA membrane ranging from 0.05 nm to 0.52 nm (see Figure 2B). The majority of pores are observed to have a pore radius of ~0.20 nm, resulting in the observed selectivity of these membranes. Our results once again are in agreement with experimental measurements of PA membrane using the positron annihilation lifetime spectroscopy (PALS).39 It should be noted that our results for water content and PSD are repeatable. We simulated three PA membrane structures using the same polymer crosslinking procedure with the same crosslinking degree but with different random monomer conformations, and comparable results in terms of pore size distribution and water content were obtained. Similarly, previous studies showed random aggregation processes in the diffusion- or reaction-limited region form structures whose topology may be fairly insensitive to the specifics of aggregation mechanism31 and also demonstrated that different ways to produce the polyamide structure can lead to similar results about membrane in terms of topology or the general appearance of the pore size distribution16. It is also notable that recent study28 performed crosslinking at low temperature of 340 K through MD and energy minimization, after initial relaxation of monomers at 1000 K. The unique crosslinking procedure demonstrated that despite the similar density and the same crosslinking degree, membrane permeation coefficient and the free volume can be quite different, which is probably due to the difference in monomers and crosslinking sites spatial distributions28. Therefore, cares still need to be exerted on empirical crosslinking protocols in order to mimic the solution-interface crosslinking well. The selectivity of a given pore depends on the diameter of the pore and the “effective” diameters of the solvents and ions attempting to permeate the pore. The effective radius of the solvents is determined by the radius of water molecules and the energy associated with its interactions with its neighbors that can effectively increase in size.40 In the case of water associating with other water molecules

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this would be the hydrogen bonding energy, (i.e., enthalpy change ∆H) which is at the order of 23.3 kJ/mol.41 This makes the water clusters relatively flexible. So a pore of 0.2-nm radius allows limited water diffusion, because the pore is in fact larger than the water radius (~ 0.135 nm). On the other hand, a pore with radius of 0.2 nm can block the passage of ions, because the pore is smaller than the radius of the hydrated ion (instead of the ionic radius). For example, the radius of the hydrated Na+ is 0.358 nm40, 42. In addition, its desolvation ∆H is rather large (-440 kJ/mol) 40, which makes stripping waters off to permeate the pore, highly unlikely. Similarly Clions also get solvated and are also unable to permeate the membrane because their effective size is larger than the 0.2-nm pore size available. The diameter of the hydrated shell of a Cl- ion is about 0.28 nm but it is more flexible because of the lower hydration energy of Cl-.43

(A)

(B)

Figure 2 (A) density profiles of water, polymer and the whole system; and (B) pore size distribution. By using the “synthesis” of the membrane in our simulation, we analyzed the membrane’s local structure and water permeation. The local structure of PA membranes is mainly determined by the interactions between the residual benzene groups, which are constrained by bonded and non-bonded interactions, i.e., π-π stacking (“stacked” or “T-shaped” )44. To characterize the

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packing of the residual benzenes in the polyamide membrane, the order parameter S(r) was investigated,  =


(1)

where r is the radial distance and θ(r) is the angle defined by normal vectors of benzene rings at r (see Figure 3).32 The relative local density of benzene rings is determined from the radial distribution, G(r),  =

 

(2)



where ρ(r) is the benzene ring density at r, and the bulk density, ρbulk is defined at r > 1.2 nm. S = 0 corresponds to a random structure and S = 1 represents completely ordered packing. As shown in Figure 3, at r~0.34 nm on the S(r) profile, there is a sudden sharp peak matching the stacked π-π interactions. As S(r) decreases, a small drop is observed at r ~ 0.48 nm, corresponding to the “T-shaped” stacking. At r ~0.65 nm before S(r) decays to zero value, an obvious increase appears, which is attributed to the neighboring bonded benzene rings and π-π stacked conformation. Our results of G(r) also show increases at those three positions. It should be noted that we only show the data up to r = 1.0 nm. For r > 0.65 nm, no further peaks are observed in the S(r) profile, which suggests the absence of multiple stacking of benzene rings. The fast decay of the order parameter profile observed within r values of 0.4 nm indicates benzene rings’ short-range anisotropic interactions. It also implies that there is no long layer structure inside a polymer membrane. Slip structures cannot propagate over a distance of more than two bonded benzene rings. To the best of our knowledge, there is no experimental measurement available regarding PA thin film membrane local structure with atomistic resolution at present. Only some results of different systems were reported. For example, the

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stacking structures of aromatic rings for proteins were analyzed by using the experimental data of high resolution X-ray spectrometer and nuclear magnetic resonance (NMR).44

Figure 3. Benzene rings’ order parameter S(r), and density profile G(r), as a function of radial distance r. 3.2. Water Diffusive Behavior inside Membrane. The diffusion of water in different regions (bulk water reservoirs, water-polymer interface and inside membrane) (see Figure 4(A)) was obtained by solving the diffusion equation (subject to absorbing boundary conditions) from the MD trajectories32, 45. Water diffusivity components ( ,  and  ) were calculated by using the autocorrelation functions below,  =  

→"

+, = - ∑-02  =

〈∆  〉&',)  * 

, with similar equation for 

/0,01 

(4)

/0

34 5∙〈78 90:;8 



?4 @ = A2/DEF 

(3)

4GH 5



(6)

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with the boundary locations a and b; the water slab thickness L (= b – a); the total number of time steps T; the numbers N(t) and N(t,t+τ) of water molecules which stay inside the slab at time t and within the time window (from t to t+τ) respectively; and the autocorrelation function time step τ. In the bulk water reservoirs, we obtained a diffusion coefficient Dw of 5.0 ± 0.2 × 10-5 cm2/s, which is greater than the experimental result (2.3 × 10-5 cm2/s), but matches other results using TIPS3P water model.46-47 At the polyamide-water interface, the diffusion coefficient Dinter was found to be 2.5 ± 0.2 × 10-5 cm2/s, which is about 50% of the bulk value. However, the diffusion coefficient in the membrane interior (i.e., 8 nm < z < 11 nm),  , along the normal direction to the surface, which varies with τ, ranged from 0.6 × 10-5 cm2/s to 0.2 × 10-5 cm2/s over 2 ns (see Figure 4B). Our result of  shows the same order of magnitude as those reported in previous studies.16, 24, 27 The heterogeneous behavior inside the membrane is attributed to the heterogeneity of the local membrane structure48 and the local chemical environment49 at the microscopic level. Similar heterogeneous diffusion in the membrane has also been reported by Freger, et al.35

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Figure 4. (A) PA membrane in water: water molecules in two reservoirs (red); polymers (blue); water molecules inside membrane (green) and water fast-pathway (red) and different areas are labeled ((1) bulk area (2) polymer-water interface (3) internal membrane); (B) diffusion component  as a function of the autocorrelation time τ; (C) water fast pathway colored red.

In our simulation, the system was allowed to relax for 130-ns; only the data of last 35-ns was used for the analysis. 30 out of 223152 water molecules were observed to permeate the membrane of 8-nm-thickness from either side of the membrane over the last 35-ns. The trajectories of the faster diffusing water molecules were mapped to identify the faster pathways for water permeation (see Figure 4C). The snapshot shows clusters of water molecules observed along the fast pathway. To characterize water structure in different regions, the radial distribution functions (RDF) of oxygen atoms of water are compared with those of bulk water (see Figure 5A). The main hydration peaks in bulk water, the fast pathway channel and the bulk membrane are observed at the same position at 0.3 nm primarily due to water hydrogen bonding, but the peaks become less pronounced in the order of bulk water, bulk membrane and fast pathway. The

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coordination number of water molecules was estimated by the integration of RDF at the cutoff distance of 0.33 nm, including the main hydration peak (see Figure 5B). Inside the membrane, the coordination number Nc is 2.7, which contrasts with the value of 4.5 for bulk water, and is also different from the value of 4.0 for water molecules along the fast pathway. Our results are in agreement with literature values reported in other simulations (4.4 in the bulk phase and 2.4 inside the membrane)27. This suggests that the water molecules along the fast pathway are more connected with neighboring water molecules compared to the average water molecules inside the membrane. Previous research50 also showed that water forms “water fingers” (i.e., water pathway) inside the pore due to strong hydrogen bonding, which then facilitates the transfer of water in those pores. Thus, if one water molecule joins the finger near the entrance then one can leave it near the exit of the pore. This increases the transport rate of water in these pores. However, ions cannot form such networks because they are stopped from entering the pores, because of their larger effective kinetic diameter. More results about ions distribution across the membrane will be discussed in the following section (see Figure 7).

Figure 5. (A) Radial distribution function (RDF) between water oxygen atoms (OW), which are normalized by bulk water density and (B) coordination number of water molecules Nc in the

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water bulk, inside the water channels and in the membrane bulk. The position at r = 3.3 nm is indicated by a black dash line.

The behavior of water in these regions was also examined by comparing RDFs for water atoms and polymer atoms. As could have been expected, more water molecules are distributed adjacent to the polar groups (–OH, –NH2, –NH–, –COOH and –CONH–) (see Figure 6A and 6B) than the nonpolar benzene groups. Along the fast pathways, slightly lower densities of the nonpolar benzene atoms are detected compared to the average density inside the membrane. By tracking the trajectory of each individual fast water molecule, it is observed that the fast pathways are mostly located around the duplicated smaller cells’ edges of the degree of polymer crosslinking (~ 42%), which is lower than the overall average value of 70%. At the final level of hierarchical crosslinking to construct the membrane, less crosslinking was performed for the atoms at duplicated cells’ edges due to the increasing computation load for crosslinking. The membrane is sliced into smaller regions along both X- and Y- axes (resolutions of 1.05 nm2 along X-axis and 1.07 nm2 along Y-axis) to examine the spatial variance of crosslinking degree. The standard deviation of crosslinking degree for those regions is found to be around 9%. It was also observed that there were no differences in the pore size distribution along the fast pathways when compared to the overall membrane; this implies that the porosity (φ) remains unchanged. Because diffusivity inside the membrane is strongly correlated with porosity (φ) and tortuosity(τ), ∅

I = KL3M

(7)

we conjecture that the pores along the fast pathways are more connected leading to smaller membrane’s tortuosity and fast water diffusion. Previous studies demonstrated that thermal fluctuations of hydrophilic surfaces of nanochannels can affect water permeation.51 It was also

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reported that dynamic heterogeneities in the nanoporous silica network can lead to heterogeneity in the dynamics of water.52 We plan to further investigate the relationship between water permeation, salt rejections, degree of crosslinking and membrane mechanical properties at the microscopic level which will be reported in our future work.

1.25

(A)

Membrane Channel

Peak 3

0.50 0.25

Peak 1

0.00 0.0

1.00 HW_Polyamide

Peak 2

0.75

1.25

(B)

g

OW_Polyamide

1.00

g

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Membrane Channel

Peak 2

0.75 0.50 Peak 1 0.25 0.00

0.2

0.4

0.6

0.8

1.0

0.0

0.2

R (nm)

0.4

0.6

0.8

1.0

R (nm)

Figure 6. (A) Radial distribution function (RDF) for water oxygen atoms and polyamide atoms in the membrane bulk and water channels: Peak 1 at R = 2.0 nm for hydrogen atoms in the polar groups (–OH, –NH2 and –NH–); Peak 2 at R = 0.28 nm for the benzene hydrogen; and Peak 3 at R = 0.38 nm for the benzene carbon. (B) RDF for water hydrogen atoms and polyamide atoms in the membrane bulk and water channels: Peak 1 at R = 0.19 nm, stands for the oxygen atoms in the carbonyl groups (–COOH and –CONH–) and peak 2 for the nitrogen atoms in –NH2 and – NH– groups. Note that the peak assignment here is based on the individual RDF profile for each pair. For the purpose of clarity, we do not include each individual RDF. Finally we also simulated PA membrane in saline water. On both sides of the fully solvated polymer membrane, ions of Na+ and Cl- were added into reservoirs to maintain a bulk ion concentration of 9.0 M. The entire system was equilibrated for 100 ns at 298 K in the NVT ensemble. Using the last 10-ns of the MD trajectory, the densities of water, polymer and ions (Na+ and Cl-) obtained are shown in Figure 7. One can observe that membrane-water interface

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effectively rejects ions from bulk saline solution (see Figure 7) while decreasing water content. Despite the presence of the fast water pathways, no ion permeation through the membrane is detected during the entire simulation of 100 ns and the ion concentration inside the membrane is zero in our simulation time scale.

Figure 7. Density profiles of water, polymer atoms and ions (Na+ and Cl-) across the PA membrane.

4. CONCLUSION In summary, we have successfully developed a realistic and reliable atomistic model for crosslinked polyamide membrane with properties (density, monomer ratio, crosslinking degree, water content, pore size distribution, water diffusion and salt rejection) in agreement with results from experimentally synthesized membranes and previous simulation studies. Our hierarchical crosslinking protocol offers an efficient method to construct a reliable polymer membrane structure of high-crosslinking degree. We analyzed the local structure membrane and water permeation. Our results demonstrate short-range π-π stacked interactions of benzene rings, which results in a thin two-layer slip structure with the length not more than two linked benzene rings.

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Our simulations also showed the presence of benzene rings with “T-shaped” stacking inside the membrane. Water molecules with larger coordination numbers and faster diffusion are observed in the fast pathways with lower degree of crosslinking. The simulated membrane also shows high salt rejection in the fast pathways for water permeation. We note the commercial PA reverse osmosis membranes are operated at large pressure difference (5-7 MPa for seawater desalination and 1 MPa for brackish water) for water desalination. The degree of crosslinking can be expected to affect the mechanical properties of membranes, which we plan to investigate in a future study.

Supporting Information The constructed polyamide memebrane conformation in PDB format (PAmembrane.pdb). This material is available free of charge via the Internet at http://pubs.acs.org. ACKNOWLEDGEMENTS T. W. thanks the Center of Air and Water Quality at Lamar University and the NSF/XSEDE program for funding and support. L. Z. thanks National Basic Research Program of China (2015CB655303), National Natural Science Foundation of China (51578485), the Research Fund for the Doctoral Program of Higher Education of China (No. 20130101110064) for support. S. M. was supported by a grant from the National Science Foundation (CBET-0730026/1263107). Corresponding Author *Email: [email protected] (T. Wei), [email protected] (L. Zhang), [email protected] (S. Murad)

Notes

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The authors declare no competing financial interest. REFERENCES 1.

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