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Selective Transport through Membranes with Charged Nanochannels Formed by Scalable Self-Assembly of Random Copolymer Micelles

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Chemical and Biological Engineering Department, Tufts University, Medford, Massachusetts 02155, United States
Cite this: ACS Nano 2018, 12, 1, 95–108
Publication Date (Web):December 5, 2017
https://doi.org/10.1021/acsnano.7b07596

Copyright © 2017 American Chemical Society. This publication is licensed under these Terms of Use.

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Abstract

Membranes that can separate compounds based on molecular properties can revolutionize the chemical and pharmaceutical industries. This study reports membranes capable of separating organic molecules of similar size based on their electrostatic charge. These membranes feature a network of carboxylate-functionalized 1–3 nm nanochannels, manufactured by a simple, scalable coating process: a porous support is coated with a packed array of polymer micelles in alcohol, formed by the self-assembly of a water-insoluble random copolymer with fluorinated and carboxyl functional repeat units. The interstices between these micelles serve as charged nanochannels through which water and solutes can pass. The negatively charged carboxylate groups lead to high separation selectivities between organic solutes of similar size but different charge. In single-solute diffusion experiments, neutral solutes permeate up to 263 times faster than negatively charged compounds of similar size. This selectivity is further enhanced in experiments with mixtures of these solutes. No permeation of the anionic compound was observed for over 24 h. In filtration experiments, these membranes separate anionic and neutral organic compounds while exhibiting water fluxes comparable to that of commercial membranes. Furthermore, carboxylate groups can be functionalized, creating membranes with nanopores with customizable functionality to enable a broad range of selective separations.

Membrane separations are used in a wide array of applications, from water treatment (1-3) and the purification of biopharmaceuticals (4) to the food industry. (5) However, this green, energy-efficient, scalable method is often limited by the types of separations in which it is utilized. Today, most membrane-based separations rely on differences in solute size relative to membrane pore size. Membranes that combine this size-based selectivity with a capability to differentiate between solutes that feature different functional groups can enable us to design membranes for custom applications and expand their use in chemical and pharmaceutical manufacturing. Such “chemoselective” membranes also have potential applications in chemical and bio-sensors, (6, 7) DNA detection and analysis, (8, 9) nanofluidics, (10) and drug delivery. (11)
Biological pores such as porins, proton channels, and ion channels display this chemical selectivity exquisitely. (12) For example, ion channels present in the cell membrane are indispensable in controlling electrical signaling in nerves and muscles, and thus maintaining cell balance through highly permeable and selective transportation of ions. These structures have some distinctive features in common: hydrophobic pores only slightly larger than the target they transport (e.g., ∼1 nm for ion channels), lined with functional groups that reversibly but selectively interact with the target (e.g., charged groups in ion channels, hydrogen bonding, and hydrophobic groups in porins). (12) Their superior selectivity and permeability arises from the synergistic effect of nanoconfinement of permeation with chemical functionality. The small pore diameter forces all solutes to closely interact with functional groups on the pore walls. The interactions between the solute and the functional groups in the pore control the partitioning and transport of the solutes in the pores. Thus, creating a simplified membrane that mimics their behavior can create a new generation of membranes with superior selectivity with a range of applications that span water treatment to the separation of small organic and biomolecules in chemical and pharmaceutical manufacturing.
Membranes that can separate small organic molecules of similar size but differing charges have several applications, especially in the extraction and purification of small pharmaceutical molecules such as amino acids (13-15) and antibiotics. (16, 17) Membranes with pore walls that feature charged groups can accomplish this by favoring the passage of solutes that are uncharged or of opposite charge but hindering the passage of co-ions. This effect is especially prevalent when the membrane pore size is decreased down to the Debye length of the electrolyte, on the order of about 0.2–10 nm for electrolyte concentrations of 0.001–0.1 M. (18)
Designing such selective membranes requires the creation of very small <3 nm nanopores and the integration of chemical functionality into the nanopores to tailor their surface chemistry to induce desired chemical interaction with the target molecule. To date, most attempts to create functionalized nanochannels have focused on narrowing and modifying the pores of track-etched (TE) or anodized alumina membranes, which feature cylindrical through-pores down to 20 nm in diameter. These methods include the electroless deposition of gold onto pore walls followed by chemisorption of an end-functionalized thiol onto the gold surface to tailor the membrane surface chemistry (19-23) or using chemical vapor deposition (CVD) techniques to narrow and functionalize the pore walls. (24-26) Vertically aligned arrays of carbon nanotubes (CNTs) can also act as membranes with functional cylindrical nanopores. (27-29) When the pore entrances are functionalized with carboxylic acid groups, these membranes show ion exclusion. (29, 30) All these approaches, however, require multistep and complicated synthesis procedures. They also result in very low porosities (<1%, compared with 70–90% bulk porosity for typical membranes (31)) that lead to membrane fluxes that are too low for most filtration applications. Because of these concerns, the materials prepared using these methods are used in microelectronics, (32) energy storage devices, (33) drug delivery, (34) and sensors (35) rather than as filtration membranes.
Self-assembly is a promising tool for generating membranes with functional nanostructures using scalable, easier to implement methods. (36-41) For example, the self-assembly of a polymer within the pores of a TE membrane through ionic interactions has been reported to narrow the pores down to 6–9 nm, (42) ideal for protein separations but still too large for separating small molecules. The porosity of these membranes is, however, still very low, and tailoring the pore size and the functionality is very difficult and limited by the polymer structure. Another example is a template-free approach in which a mixture of gold nanoparticles, polyamidoamine dendrimers (PAMAM-Den), and CS2 is coated on a glass substrate and formed thin film composite (TFC) membranes with dendrimer–gold nanoparticle (Den–AuNP) selective layers. The cross-linked dendrimer domains provide permeation pathways between the gold particles, and unreacted groups can be used for postfunctionalization. (43, 44) These membranes show some diffusion selectivity for small molecules but are more effective for larger molecules (i.e., proteins). The smallest pore size (interparticle spacing) is still on the order of 10 nm depending on the dendrimer generation, too large for separating small molecules.
The self-assembly of well-designed copolymer-based precursors can lead to formation of pores that can be chemically modified for desired selectivity through scalable manufacturing processes. Self-assembly of amphiphilic block copolymers (BCPs) can yield well-defined structures such as cylinders, spheres, gyroids, and lamellae. (45) These structures, especially cylindrical and gyroid morphologies, can be used to form membrane pores. Upon functionalization, they can potentially exhibit chemical feature-based selectivity, (45-48) but it is difficult to obtain domain sizes, and hence pores, smaller than ∼10 nm using BCP self-assembly. This makes BCP membranes especially suitable for ultrafiltration applications and protein separation and purification. (37) Random and comb-shaped copolymers can form smaller and bicontinuous domains down to 1 nm (49-53) and have shown size-selective screening of small molecules. With further functionalization, these copolymers can exhibit selectivity that goes beyond size screening. For example, a random terpolymer of acrylonitrile, oligo(ethylene glycol)methacrylate and glycidyl methacrylate, microphase separates to form polyacrylonitrile- and oligo(ethylene glycol)-rich domains. The latter acts as effective channels for water permeation, with epoxide moieties that allow for further postfunctionalization to form positively or negatively charged moieties. (54)
As an alternative to microphase separation, the assembly of spherical nanoassemblies such as micelles or colloidal nanoparticles into packed arrays can create porous systems that act as membrane selective layers. For instance, BCP micelles have been deposited onto a silicon wafer by spin coating to form a porous film of packed micelles that can perform size-based separation. (55, 56) The compressibility of these micelles causes them to deform upon the application of pressure, causing changes in pore size. (56) Alternatively, colloidal silica nanoparticles can be assembled into packed arrays that can be functionalized with polymers and modulate transport. (57-61) These membranes can also be presumably used as membrane selective layers, though the brittleness and thickness of these layers may be of concern in pressure-driven processes. However, the large size of both BCP micelles and silica particles (45–200 nm) accessible in these studies leads to pore sizes between 7.5 and 100 nm, too large to address small molecule separations. Furthermore, these approaches have not been explored for imparting chemical structure-based selectivity in filtration applications.
Almost all of the methods mentioned above require postmodification steps that can increase the risk of undesired side reactions or damage to the membrane structure. The added manufacturing steps may also limit scalability. It is highly desirable to develop a single-step, scalable approach to generate membrane selective layers with a high density of <3 nm nanopores lined with tailored, well-defined functional groups, to yield membranes with high permeability and good selectivity between solutes of similar size but different chemical features (e.g., charge). There is also a knowledge gap in better understanding the mechanisms of transport and selectivity in such membranes.
In this work, we demonstrate the formation of membranes that feature a network of carboxylate-functionalized nanochannels in their selective layer by depositing random copolymer micelles in alcohol onto a porous support using a single-step coating process (Scheme 1). These micelles are formed by the self-assembly of a random amphiphilic copolymer, poly(trifluoroethyl methacrylate-random-methacrylic acid) P(TFEMA-r-MAA), (62) and are stable in water. The resultant membranes feature a selective layer of a packed array of micelles with carboxylate functional surfaces. The interstices between these micelles, calculated to be approximately 1–3 nm at their narrowest point, serve as charged nanochannels through which water and solutes can pass. The negatively charged carboxylate groups lead to high separation selectivities between organic solutes of similar size but different charge, as demonstrated by diffusion and filtration experiments. These membranes effectively retain negatively charged solutes while allowing the passage of positively charged and neutral solutes of similar size and exhibit water fluxes comparable to that of commercial membranes of similar pore size. Their permeation selectivity is enhanced further in competitive diffusion experiments as the neutral solutes prevent the entrance of anionic solutes into the nanopores. In addition to promising applications in charge-based separations in the industry, these membranes represent an innovative approach to creating membranes with carboxyl functional nanopores that can be further modified to enable a broad range of selectivities.

Scheme 1

Scheme 1. Formation Mechanism of the Membrane Selective Layer Featuring Charged Nanochannelsa

Scheme a(a) Random copolymer with fluorinated and carboxylated repeat units; (b) formation of micelles in methanol; (c) coated micelles onto a porous support, where they form a packed array of spherical micelles with carboxylic acid functional surfaces. The interstices between the micelles act as effective nanopores through which permeation occurs. Ionized carboxylate groups impart charge-based selectivity through electrostatic interactions.

Results and Discussion

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Copolymer Synthesis and Characterization

Two batches of P(TFEMA-r-MAA) copolymers with different compositions were synthesized using free radical polymerization. This method is simple and scalable, which is important for future commercial impact of related technologies. The resultant copolymer compositions were calculated using the characteristic peaks of each monomer from 1H NMR spectra (Figure S1, Supporting Information). The compositions of membrane selective layers prepared by these copolymers, obtained by attenuated total internal reflectance Fourier transform infrared (ATR-FTIR) spectroscopy (Figure S3, Supporting Information), closely matches the composition of the copolymers used for their preparation. This indicates the copolymer chemistry and composition are preserved during the selective layer formation process. GPC analysis in tetrahydrofuran (THF) showed the successful synthesis of high molecular weight copolymers with polydispersities in agreement with typical values for the free radical polymerization method (Table 1). We suspect, however, that these measurements were at least somewhat affected by the formation of micelles in THF (62) and the limited solubility of CP50 in this solvent, leading to the measurement of very different molecular weights for the CP40 and CP50, even though, based on the similar synthesis conditions, similar molar masses were expected. Water uptake measurements indicate that copolymers with higher MAA content show higher water uptake, as expected from the hydrophilicity of this monomer.
Table 1. Compositions, Molecular Weights, Water Uptake Values of Synthesized Copolymers, and Key Properties of Prepared Membranes
propertiesCP40CP50
MAA wt % in reaction mixture5070
MAA wt % in copolymer4555
copolymer weight-average molar mass (kg mol–1)106439a
copolymer dispersity1.751.72
copolymer water uptake %26 ± 351 ± 7
estimated membrane pore size (nm)b1–31–4
pore density (×1014 pores m–2)b2.34.1
membrane permeance, Lp (L m–2 h–1 bar–1)4.2 ± 1.07.3 ± 1.3
selective layer permeability, Pm (L μm m–2 h–1 bar–1)1.7 ± 0.43.7 ± 0.7
contact angle82 ± 369 ± 4
a

Likely underestimated due to limited solubility of CP50 in THF.

b

Calculated through image analysis of surface FESEM images in the dry state (Figure S8).

In both cases, the resultant copolymer compositions, obtained at about 40% conversion, were slightly higher in TFEMA content compared to that of the reaction mixture composition. These results are in agreement with additional studies (62) that indicate the monomer sequence is close to random, with few, if any, PTFEMA blocks. While the resultant copolymers cannot be described as completely random, their segmental order is likely close. It should be noted that while these copolymers are truly statistical copolymers with the given caveats, we use the term “random copolymer” throughout this document for the sake of simplicity, to clearly distinguish from block copolymers commonly investigated in current literature, and to use consistent terminology with past publications in the field where this effect was not often considered.

Copolymer Micelle Formation in Methanol

The MAA repeat units in the P(TFEMA-r-MAA) contain carboxylate functional groups and are highly incompatible with the TFEMA repeat units. PMAA homopolymer is a weak poly acid and highly soluble in methanol, with which it interacts strongly through hydrogen bonding. In contrast, PTFEMA homopolymer is a fluorinated, very hydrophobic polymer that is insoluble in methanol. We have recently documented that this leads the random copolymer of these two monomers, P(TFEMA-r-MAA), to assemble into spherical micelles and vesicles upon being dissolved in methanol. (62) This was confirmed by transmission electron microscopy (TEM) imaging (Figure 1).

Figure 1

Figure 1. TEM images of the P(TFEMA-r-MAA) micelle assemblies cast from a solution in methanol by immersion into water after (a) no evaporation time, (b) 10 s evaporation, and (c) 20 s evaporation. The insets in (a) and (b) show higher-magnification images (scale bar: 100 nm) of the smaller ∼20 nm micelles, in isolation or in clusters. Large vesicles and small isolated micelle clusters form packed assemblies upon solvent evaporation.

Unlike micelles formed by BCPs, these micelles do not show a thick corona. The two types of repeat units in random copolymers are dispersed in close vicinity of each other along the polymer chain, as opposed to distinct blocks found in block copolymers. Because the segments are very short, a key structural feature of random copolymers, a much thinner corona is formed. This prevents the formation of clear boundaries between a core and a shell/corona in the resultant micelles. (63) The micelle surface is rich in MAA groups, as evidenced by the staining of the outer surface of the micelle by Cu(OAc)2 indicated by the dark outlines on the micelles. TFEMA-rich sections of the polymer chain form the micelle core. PTFEMA homopolymer has a high Tg (80 °C). (64) This improves micelle stability by limiting polymer mobility within the core.
TEM imaging (Figure 1a) also showed a wide range of micelle sizes, including some very large micelles (>200 nm), possibly vesicles, and some much smaller micelles (∼15–20 nm) captured in the same frame or at varying magnifications (inset in Figure 1a). This was consistent with dynamic light scattering (DLS) data (Figure S2, Supporting Information). Both copolymers showed a bimodal size distribution, consisting of a large number of small <20 nm micelles mixed with large micelles/vesicles with size of about 100 nm. The larger size of the bigger aggregates in the TEM image can be attributed to the flattening of micelles on TEM grid while drying or fusion of smaller particles induced by solvent evaporation and desolvation of micelle corona. (65, 66) CP50 micelles had a smaller average effective diameter of about 7.8 ± 0.3 nm, compared with 17.0 ± 0.9 nm for CP40. This can be attributed to the lower TFEMA content leading to shorter TFEMA segments and thus smaller micelle cores. The bimodal distribution likely implies the formation of large compound micelles (LCM) and vesicles (66-69) in solution upon the fusion of smaller micelles, frequently observed in both random and block copolymers.

Formation of Packed Micelle Arrays

In this work, we utilized the assembly of the micelles described above to form membrane selective layers that feature nanometer-scale channels with carboxylate functional walls, arising from the interstices between micelles packed together. To form such membrane selective layers, this micellar solution is coated onto a porous support (a commercial membrane with large pore size). Methanol is allowed to evaporate briefly to increase the local micelle concentration, forming a tightly packed micelle array triggered by capillary forces between the micelles. (70, 71) During evaporation, particles on the topmost layer arrange themselves into the most favorable ordered structure. The coated membrane is then immersed into water. P(TFEMA-r-MAA) copolymers with ≤55 wt % MAA are insoluble in water, so this step causes the micelles to precipitate out quickly, with their morphology preserved due to their rigid and hydrophobic TFEMA-rich core.
The water immersion step is crucial because the packed micelle structure is not an equilibrium morphology. In general, micelles and vesicles formed in solution (here, in methanol) are very dynamic. Micelles formed by random copolymers are even more dynamic due to their thinner corona. (66) Their morphology changes upon solvent evaporation and during the formation of the selective layer. With a long enough evaporation time, the capillary pressure can reach a critical value above which particles are stressed above their limit of deformation. Micelles merge, and a continuous, dense polymer layer forms (Figures S4 and S5, Supporting Information). Other researchers have also observed that, upon solvent evaporation, random copolymer micelles often merge. (72) This means that controlling and stabilizing the micellar morphology far from equilibrium is important in this approach to bottom-up nanostructure fabrication.
To characterize the effect of drying time on how micelles assemble into packed arrays, we performed TEM on thin film samples prepared on TEM grids using a process that simulated the membrane formation process (Figure 1). We dipped TEM grids into 0.3 wt % CP40 copolymer micelle solutions in methanol to form a thin film. After evaporation in air for the selected time period, the grids were dipped into water to fix the structure. When the polymer film was immediately submerged in DI water with no evaporation time, isolated ∼20 nm micelles and some large micelles or vesicles (∼200 nm) were observed (Figure 1a). It is likely that smaller micelles were also present in solution that either merged to form these large structures or dispersed into the water due to lack of cohesion. Obviously, this structure is not suitable to serve as a membrane selective layer. When the solvent is allowed to evaporate for 10 s before immersion into water, clusters of smaller micelles were observed in the deposited film in addition to a small number of large vesicles (Figure 1b). When the film was dried for 20 s and then dipped in DI water, a closely packed array of micelles and vesicles of varying sizes spanning a large area was observed (Figure 1c). The dark stained regions, gaps between these micelles, can now act as effective nanochannels that would enable permeation through the membrane selective layer. Longer evaporation times led to merged micelles and continuous thin films (Figure S4, Supporting Information).

Membrane Formation and Morphology

These experiments showed that closely packed micelle arrays can be formed and stabilized by spreading the micelle-containing solution as a thin film, evaporating the solvent briefly, and then immersing the film into water to freeze the packed array before the micelles merge. As the next step, we aimed to apply this method to make micelle arrays on porous supports, to serve as membrane selective layers. During the use of these membranes, the carboxylate groups on the micelles become negatively charged in water due to their low pKa (between 3 and 5.5 for PMAA homopolymer (73)). This enables the membrane to exhibit charge-based selectivity through Coulombic interactions between these pore walls and solutes. Furthermore, the carboxylic acid groups provide a great platform for further functionalization of the membrane. (74)
Membranes were fabricated from both copolymer compositions by depositing the copolymer micelles onto a commercial support membrane by a coating process designed to enable the micelles to pack together on top of the membrane but prevent their merging into a nonporous film. For this purpose, a solution of 5 wt % copolymer in methanol was spread onto a porous UF membrane (polyacrylonitrile, PAN400, Nanostone) using a doctor blade to form a thin layer. The solvent was allowed to evaporate for 20 s to direct the self-assembly of the copolymer into the desired nanostructured selective layer. Shorter evaporation times typically led to poor rejection, indicating incomplete coverage of the surface with the micelle arrays. Extended evaporation times led to the merger of micelles to form a uniform, dense coating layer (Figures S4 and S5, Supporting Information). It is likely that when optimal evaporation times are used, the resultant layer features the partial fusion of micelles at points of contact, perhaps through copolymer chains that bridge two micelles. Subsequently, the film was submerged into a water bath, which quickly precipitated the micelles, whose morphology is preserved due to the hydrophobicity and high Tg of the PTFEMA core. The self-assembled random copolymer micelles are kinetically trapped in a packed array of spheres. Hydrogen bonding between MAA groups on the micelle surfaces also likely reinforces the integrity of this layer. The interconnected interstices between them provide permeation pathways, lined with carboxylic acid groups (Scheme 1).
The polymer concentration in the coating solution affects the final performance of the membrane. High polymer concentrations in the coating solution (>10 wt %) with the same evaporation times resulted in low membrane permeability (0.15 L m–2 h–1 bar–1). While this is at least partially due to the deposition of a larger quantity of micelles on the membrane surface, it may also arise from the micelles merging into a nonporous film more quickly. The porous membrane support also had a significant impact on coating morphology and membrane performance (Figure S6, Supporting Information). These results demonstrate that while the proposed approach is simple to execute overall, manufacturing parameters must be selected carefully to enable the formation of a stable layer of packed micelles, arrested on the membrane surface.
The resultant membrane selective layer with packed micelles can be observed by high-resolution scanning electron microscopy (SEM) imaging of membrane cross sections and surfaces. SEM images for the support membrane and membranes made from both copolymers are shown in Figure 2. The surface morphology of the support membrane (Figure 2a) is distinctly different than that of the CP40- and CP50-coated membranes (Figure 2b,c), confirming the presence of a continuous selective layer. The surfaces of both CP40- and CP50-coated membranes feature closely packed small spherical micelles. Cross-sectional images of both copolymer-coated membranes (Figure 2e,f) exhibit a ∼400 nm thick selective layer well adhered onto the support membrane, shown in Figure 2d,g. At higher magnification (Figure 2h,i), a nicely packed array of spheres on top of the support can be seen for both copolymers. In the case of the membrane prepared with the CP40 copolymer (Figure 2h), the micelle size distributions obtained from the cross section and surface images are consistent with both DLS and TEM (Figures S7 and S8, Supporting Information). However, the SEM image of the CP50-coated membrane (Figure 2i) shows larger micelles (20–25 nm) in comparison to DLS measurements (7 nm). This can be attributed to bigger clusters forming during solvent evaporation in the case of CP50 due to its lower hydrophobic repeat unit content, providing it with less rigidity and stability during the membrane formation process.

Figure 2

Figure 2. SEM micrographs of (a) PAN400 support membrane surface morphology, (b) CP40 membrane surface morphology, (c) CP50 membrane surface morphology, (d,g) PAN400 cross section, (e,h) CP40 cross section, and (f,i) CP50 cross section. Both CP40- and CP50-coated membranes exhibit packed arrays of micelles, interstices between which act as permeation pathways.

The micelles maintain their discrete structure throughout the layer in both copolymer-coated membranes. The intermicellar spaces provide the path for the transport of solute through the selective layer. In some regions, especially in the topmost layer, the micelles arrange themselves into semiregular arrays and provide a continuous path throughout the selective layer, similar to what has been reported for block copolymer micelle assembly. (75) The solute pathway is more tortuous in the layers below. The tight packing of the micelles in the top layer was also documented by atomic force microscopy (AFM) (Figure 3a). This image was analyzed to determine if the packed micelles showed significant ordering. Two-dimensional fast Fourier transform (2D-FFT) pattern of the AFM height image was radially integrated for a more quantitative evaluation using ImageJ software (Figure 3b). This plot shows peak positions (1:√3:1.9) that suggest a high density of uniform micelles with a hexagonal close-packed (hcp) structure. The packing, however, is imperfect, with other irregular structures (pentagons, polygons) dispersed among the hcp array (Figure 3a). As a general rule, micelles of monodisperse size prefer to arrange in hexagonal patterns that lead to the densest possible packing. (76) The wide size distribution of the micelles observed in this case likely leads to the defects and heptagonal and pentagonal structures. (77) The position of the q* peak can further be used to calculate the lattice parameter of the hcp structure to be a = 14 nm (Figure S10, Supporting Information). Note that a corresponds to the distance between micelles’ centers and thus is larger than the micelle size. Thus, this value is overall consistent with the micelle size obtained by microscopy imaging and DLS experiments. The minor disparities between exact values can be attributed to the tip broadening effect in AFM, resolution of the tip, and potential fusion of the micelles on the surface during selective layer formation.

Figure 3

Figure 3. (a) AFM height image of CP40 membrane (10 μm × 10 μm with z-range of 200 nm), showing spherical micelles packed in a hexagonal close packed (hcp) array with few irregular polygons; (b) 2D FFT pattern corresponding to AFM height image; dashed markings correspond to (q/q*)2 = 1, 3, and 3.7, showing almost 2D hcp structure.

It is worth noting that TEM samples prepared under conditions designed to mimic the membrane fabrication process exhibit tightly packed micelles (Figure 1c), but unlike the membrane selective layers, they exhibit no order. The difference may arise from the fact that TEM was acquired using samples prepared from a very dilute solution, which may change the forces that may be at play in creating the ordered structure in the multilayered structure on the membrane from more concentrated solutions. The presence of the porous support may also remove the solvent through capillary forces, further changing how micelles interact with each other and pack.
Based on the packing geometry and the average micelle size determined from SEM micrographs of both surface and cross-section morphologies (Figure S9, Supporting Information), we estimated the average membrane pore size (57, 58) to be around 3 nm for the CP40 membrane and slightly larger (4 nm) for the CP50 membrane (Table 1). It should be noted that this estimation relies exclusively on the geometry of the packed layer and does not account for the alignment or polydispersity of the micelles. It also utilizes the micelle size from SEM micrographs, which were obtained in the dry state. The effective pore size in water is likely to be smaller due to the hydration of the copolymer.
This multilayered assembly of micelles creating an interconnected network of nanochannels offers significant advantages. The structure confines flow into nanometer-scale channels lined with a high density of functional groups. The hcp structure, one of two densest packing structures for spheres, provides the narrowest pore size and hence a high density of functional groups lining the pores. This leads to more solute–pore wall interactions during permeation. Unlike cylindrical nanochannels, this structure does not need to be aligned perpendicular to the membrane surface. While the high tortuosity may lead to slightly lower permeance, (31) it also increases solute–wall contacts during permeation. This can lead to enhanced separation selectivity. (78) The presence of multiple permeation paths also minimizes the negative effects of potential pore clogging during operation. Therefore, these interconnected nanochannels provide superior permeation properties and selectivity. Finally, since the rigid and hydrophobic micelle core remains impervious to water and provides a rigid structure, the self-assembled nanostructure is resistant to swelling. This permits high and more stable permeability and selectivity in comparison with selective layers where the functional groups are spread throughout the layer.

Membrane Performance

The permeation properties and selectivity of membranes prepared as above were studied using two types of experiments: diffusion and filtration. Diffusion tests are simple. Permeation under these conditions is well understood and modeled, and selectivity results can be linked to parameters such as solute diffusivity and solute–membrane affinity. Furthermore, most literature in the field of chemical selectivity in membranes reports diffusion test results. (26, 44, 79-81) However, membranes rarely operate under conditions used in these experiments. In realistic applications, pressure-driven flow through the membrane is used. Convective flow through the membrane during such operation may influence how the membrane behaves. Under pressure, some polymers may change their conformation or solubility, leading to changes in rejection. (53) Transport limitations and boundary layer features can be significantly different in the two modes of operation, affecting performance. Thus, pressure-driven filtration experiments were also performed to characterize the performance of our membranes.

Effect of Copolymer Composition on Membrane Permeability

The permeance (Lp) of membranes prepared from both copolymers were measured by pressure-driven filtration experiments and are listed in Table 1. CP50 membranes showed higher permeance due to higher MAA content and thus higher hydrophilicity, confirmed by their lower contact angle. Both CP40- and CP50-coated membranes maintained high permeances (4.2–7.3 L m–2 h–1 bar–1) comparable to that of commercially available nanofiltration membranes (2.1–13.4 L m–2 h–1 bar–1) and some tight UF membranes with molecular weight cutoff (MWCO) values between 1000 and 3000 Da (1.1–5.7 L m–2 h–1 bar–1) based on industrial specification sheets. (82) We further calculated the selective layer permeability (Pm), defined as membrane permeance normalized by selective layer thickness, using the resistances in a series model (see Supporting Information). Selective layer permeabilities were between 1.7 and 3.7 L μm m–2 h–1 bar–1, higher than that of commercial TFC nanofiltration membranes (0.2–1.4 L μm m–2 h–1 bar–1), (82) calculated assuming a selective layer thickness of 0.1 μm. (83) While the selectivity properties of commercial NF and UF membranes are by definition distinct from the proposed membranes, this serves as a broad comparison regarding their potential industrial use.
The membrane permeance did not change with pH when tested between pH 3 and 9 (Figure S11, Supporting Information). This is in contrast to the pH-responsive behavior shown in block copolymer membranes, (39, 46) in which the pores can reversibly close or open and act as a pH-sensitive gate when the hydrophilic block contains weak acids or bases such as acrylic acid (84, 85) or pyridine. (75, 86) The difference arises due to the fact that PMAA segments in the PTFEMA-r-MAA random copolymer are very short and cannot undergo the conformational transformations feasible for longer blocks found in BCPs.

Diffusion Experiments: Charge-Based Selectivity between Organic Solutes

Diffusion experiments with small organic molecules can provide insight into the relative effects of different transport mechanisms involved during permeation. In the proposed membranes, electrostatic interactions between the solutes and the negatively charged carboxylate groups on the pore walls are expected to play the most dominant role on solute permeation. Thus, solute diffusion rate is expected to strongly depend on solute charge, leading to charge-based separation capabilities. In addition to the electrostatic interactions, steric effects can also contribute to permeation selectivity given the very small 1–3 nm pores involved. Hydrophobic interactions and the adsorption of the solutes into the membrane pores can also play a role.
For these experiments, we selected a set of organic small molecules with varying electrostatic charges: Basic Blue 3 (BB3, cationic), Acid Blue 45 (AB45, anionic), and riboflavin (RIB, neutral). All three solutes were selected to have similar calculated sizes (8.3–8.6 Å, calculated using Molecular Modeling Pro (50, 52)) (Figure S12, Supporting Information). The pH of the solutions used in diffusion and filtration experiments varied between 5.4 and 7.5 (Figure S12, Supporting Information). The pKa of carboxylic acid groups in the PMAA homopolymer is reported to be between 3 and 5.5, (73) below the pH of all used solutions. Therefore, the membrane is negatively charged in all reported experiments. This is further supported by the fact that anionic solute rejection remains unchanged with pH between pH 4 and 8 (see Supporting Information). All three solutes had similar permeation rates through the porous support membrane (Figure S13a, Supporting Information), further confirming they have similar diffusivities. Hence we expect that, in this system, differences in ion permeation rates will be dominated by electrostatic interactions within the nanopores. We measured the total solute transferred through the membrane (ntransferred) and normalized it by the driving force for diffusion, the feed concentration (ΔC), to obtain the normalized moles of solute transferred, N, defined as
To quantify these differences, we calculated selectivity coefficients (α), defined as the ratio of the permeation rates of two species whose charges are noted in the subscript (Table 2).
Table 2. Solute Transfer Rates and Separation Coefficients (α) for PAN400, CP40, and CP50 Membranes in Single-Solute and Competitive Diffusion Experiments
 solute transfer rate (×10–9 m s–1)   
 single solutemixtureseparation factor for single-solute 
membrane codeBB3 (+)AB45 (−)RIB (0)AB45 (−)RIB (0)(+) and (−), α+/–(0) and (−), α0/–separation factor, α0/– in mixture
PAN4003382763592452641.21.31.1
CP4021 ± 30.75 ± 0.05197 ± 9a238 ± 828.1263>300b
CP50107 ± 721.5 ± 1.5203 ± 4a265 ± 65.09.4>400b
a

No detectable amount of AB45 was transferred.

b

The α value is calculated by considering the detection limit at the end of the experiment.

Figure 4a shows the permeation of these three solutes through the CP40-coated membrane. The neutral solute permeated through the membrane 263 times faster than the negatively charged solute of similar size due to the exclusion of negatively charged solutes from the pores as a result of repulsive forces. The α0/– value of 263 is an order of magnitude higher than the highest value reported in the literature for functional nanopore membranes formed by bottom-up methods. (44) The positively charged solute started permeating through the membrane after a delay, associated with the adsorption of these solute ions onto the membrane pores due to Coulombic interactions. After sites are saturated, however, the positively charged solute starts to diffuse at a faster rate than the anionic molecules, leading to α+/– value of 28. The lower separation factor for the cationic molecule in comparison to that of the neutral one is likely due to several factors that slow down the permeation of cationic groups through the membrane. First, maintaining electroneutrality during the passage of cationic solutes across the membrane also requires the passage of counterions, which are repelled by the negatively charged membrane. This slows down the passage of cationic solutes. We also observed significant adsorption of cationic solutes onto the membrane, leading to delayed penetration of the solute into the permeate (Table S1, Supporting Information). This results in significant pore narrowing, given the similarity between the size of the pores and the solutes used in this study. Indeed, when diffusion rate of a neutral solute was measured again after exposing the membrane to the cationic solute, a slower diffusion rate was recorded, indicating that some of the pore blockage due to adsorption is not easily reversible. Extensive washing is required to obtain the original diffusion rate. Thus, experiments with cationic solutes were only run after all other experiments were complete.

Figure 4

Figure 4. Permeation of organic molecules through (a,c) CP40- and (b,d) CP50-coated membranes in (a,b) single-solute and (c,d) competitive diffusion experiments for a mixture of negative and neutral solutes. All experiments demonstrate charge-based selectivity between similarly sized organic solutes. Selectivity between neutral RIB and anionic AB45 is enhanced in competitive diffusion experiments, as the permeation rate of AB45 through both CP40- and CP50-coated membranes is shifted below the detection limit. N is defined as the total number of moles of solute transferred divided by feed concentration.

Membrane selective layers prepared from CP40 and CP50 have different effective pore sizes and charge densities. The higher MAA content of CP50 can lead to higher charge density on the micelles. This is confirmed by static adsorption tests for the positively charged solute, showing a BB3 binding capacity for CP50 higher than that of CP40 (Table S1, Supporting Information). On the other hand, these membranes have slightly larger effective pore size and higher pure water permeability. The combination of these effects may influence membrane selectivity in different ways. Significantly higher permeation rates were observed for cationic and anionic solutes, whereas that of the riboflavin was comparable with the CP40-coated membrane (Table 2). Selectivities between solutes were lower, with α+/– around 5 and α0/– around 9 (Figure 4b). This implies that the increase in the pore size enabled easier passage of the anionic solutes despite the increase in the charge density along the walls. The relatively slower diffusion rate of the positively charged dye likely arises from the partial clogging of pores caused by more prominent adsorption of this solute, curtailing its flux more significantly than observed in the CP40-coated membrane.

Competitive Permeation in Two-Solute Mixtures for Charge-Based Separation

The presence of multiple solutes can affect permeation selectivity during operation. For example, one solute may plasticize the membrane selective layer and decrease the rejection of all others. (87) Alternatively, the adsorption of solutes into the pores can lead to constant variation of the rejection of both species. In contrast, in biological pores, permeation selectivity is enhanced in multicomponent systems as the solute with favorable interactions prevents other species from entering the pores. (78) To better understand the selectivity mechanism of these membranes, we conducted diffusion experiments for a mixture of two solutes with very similar size but differing charge, anionic AB45 and neutral RIB, through both CP40- and CP50-coated membranes (Figure 4c,d).
The support membrane showed no selectivity between the two similarly sized solutes (Figure S13b, Supporting Information). This is expected behavior for most porous materials. Interestingly, permeation selectivity through the CP40-coated membrane was significantly higher in competitive permeation experiments (Figure 4c). The normalized permeation rate of neutral riboflavin was slightly enhanced in comparison with that of single-solute diffusion experiments (Table 2). Even more strikingly, the passage of anionic solute was even more strongly inhibited. Similar behavior was observed for the CP50-coated membrane. The transport of the anionic solute was inhibited, whereas the permeation rate of the neutral molecule was enhanced (Figure 4d). No detectable amount of AB45 was transferred through either membrane even after 24 h. This meant that permeation selectivity could not be accurately measured; estimates in Table 2 indicate the minimum value based on the detection limits of our experiments.
This significantly enhanced selectivity, previously only recorded in membranes with functional nanopores prepared using complicated top-down methods, (88) is believed to arise from the two solutes competing for entrance into the very narrow nanochannels. (78) When the “preferred” (in this case, neutral) solute enters the pore, it blocks the channel and prevents the entrance of the “unpreferred” (i.e., anionic) solute. Thus, it is not only more difficult for the anionic solute to enter the channel but also less probable for it to translocate through the channel due to competition for space with neutral molecules. This results in much stronger inhibition of the permeation of the unfavorable solute compared with when it is present alone. The ability of only one solute to fit into the pore diameter has also been reported to lead to the enhancement of the transport of the “preferred” solute. Although the anionic solute molecules are mostly retained, they may still accumulate near pore entrances, hampering the back-diffusion of the neutral solute molecules, thereby increasing their forward flux. (78) These results indicate that the presence of the very narrow channels in these membranes significantly alters some of the key transport mechanisms that dominate selectivity.

Rejection of Organic Solutes in Filtration Experiments

To get a better insight into the performance of these membranes under realistic conditions, we studied the membrane separation in pressure-driven filtration. Initially, we filtered a series of solutions each containing one organic solute. We surveyed cationic, anionic, and neutral solutes with various sizes and chemical structures (Figure S12, Supporting Information).
The rejections of these solutes by the CP40-coated membrane are shown in Figure 5a, classified based on solute electrostatic charge. Similar results were also obtained for CP50 (Figure S14, Supporting Information). The rejections of anionic solutes were significantly higher than those of neutral and cationic solutes of comparable size. Positively charged solutes are also retained to a greater extent than the neutral ones. This is consistent with the diffusion experiments given the fact that cationic solutes are rejected both by their size and due to electrostatic interactions. The passage of positively charged solutes through the membrane requires the passage of counterions bound to it to preserve electroneutrality. The passage of these counterions is strongly inhibited by the negatively charged membrane. In contrast, neutral solutes do not experience similar electrostatic interactions, and their passage is solely controlled by steric hindrance. This leads to higher rejection of positively charged molecules in comparison to the neutral ones. Furthermore, significant adsorption of cationic solutes observed on the membrane results in delayed penetration of the solute into the permeate. Rejection increases with increasing solute size, indicating some size sieving effects are also at play. However, the significant differences in rejections of solutes of similar size but different charge indicates that electrostatic interactions dominate the selectivity of these membranes, at least for small molecule solutes. This demonstrates that the proposed membranes are capable of charge-based separation of organic molecules of similar size.

Figure 5

Figure 5. (a) Rejections of organic molecules with different charges by the CP40-coated membranes. Negatively charged solutes (from left to right: MO, AB45, CAL, BBR) are rejected by >85%, whereas low rejections are observed for neutral (from left to right: RIB, RTH, B12) and cationic solutes (from left to right: BB3, Rho6G) of similar size. (b) Effect of ionic strength on dye rejection of the CP40 membrane, consistent with selectivity driven by electrostatic interactions. (c) Rejection of four different salts by the CP40-coated membrane at different feed concentrations. Bars denote experimental data, and filled symbols show values calculated by fitting the Donnan model using a single parameter, Cmx, obtained 3.65 mM.

Separation of Two-Solute Mixtures Based on Solute Charge

To study the separation behavior of these membranes under more realistic conditions, we filtered the same mixture as in the diffusion experiment (anionic AB45 and neutral RIB), through the CP40-coated membrane. The membrane retained the anionic solute by 96% while allowing the passage of the neutral dye to a large extent, with a rejection of only 23% (Figure S15a, Supporting Information). Even better separation was achieved between solutes of larger size. The negatively charged solute Brilliant Blue R was retained by 98%, whereas neutral vitamin B12 was rejected by only 25% (Figure S15b, Supporting Information). Similar results, exhibiting good separation capability between negatively charged and neutral solutes, were also obtained for CP50-coated membranes (Figure S15c,d, Supporting Information). Similar to diffusion experiments, the rejection values for the anionic dyes in two-solute experiments with the CP40-coated membrane were slightly higher than those measured in single-solute experiments. For example, the rejection of negatively charged Acid Blue 45 increased from 89 to 96%. All rejection values were comparable with those measured in single-solute tests for the CP50-coated membrane (Figure S14, Supporting Information), possibly due to the larger nanochannels.

Effect of Ionic Strength on Organic Solute Rejection

In all experiments described above, we assumed that the separation mechanism is primarily dominated by electrostatics. Charged groups lead to the formation of an electrical double layer (EDL) where co-ions are excluded and counterions are enriched inside the nanopores. (89) Ionic selectivity for a charged membrane depends strongly on channel size and the thickness of EDL, typically quantified by the Debye length (λD) according to Gouy–Chapman theory (see Supporting Information). (89)
If the EDL extends through the channel, the passage of co-ions would be strongly inhibited due to electrostatic repulsion. However, if the EDL thickness is smaller than the pore radius, co-ions can pass through the region far enough from the pore walls without being repelled. The Debye length, and hence the effect of Coulombic repulsions, diminishes as the ionic strength of the feed increases. The effective pore size through which anions can pass unimpeded is increased, resulting in lower rejection. Therefore, if separation is dominated by electrostatic interactions, higher feed ionic strength should lead to lower rejection of charged solutes.
To test this hypothesis, solutions of several solutes were prepared in 10 and 100 mM NaCl solutions (Figure 5b). The Debye lengths for 10 and 100 mM NaCl solutions are calculated to be 3.0 and 0.96 nm, respectively. All negatively charged solutes were rejected more effectively in lower ionic strength solutions than at higher ionic strengths. The rejection of neutral solutes was low at all three ionic strengths and within the error margin of each other, as expected. These results support our hypothesis that the key separation mechanism is in fact electrostatic repulsion, and the effects of solute size and hydrodynamic effects are much less pronounced.
It should be noted that in the 100 mM NaCl solution, the EDL thickness is lower than the calculated pore radius of ∼1.5 nm. Nonetheless, anionic dyes are still rejected to a high degree. The obtained rejections could be due to the fact that membrane pore size in wet condition is in fact much smaller than the estimated pore size in dry state due to hydration of MAA segments. Alternatively, high tortuosity of the nanopore network, leading to a longer path length, may also contribute to high rejection. The long tortuous path length could likely force the solute to interact with a larger functionalized surface area during permeation even when the EDL does not completely fill the pores. (59, 78)

Salt Rejection

To better understand the electrostatic interactions that dominate the selectivity of these membranes, we tested the rejection of salts by the CP40 membrane and compared the results to those obtained by the Donnan equilibrium model. We measured the rejection of four salts with different anionic and cationic valencies, Na2SO4, NaCl, CaSO4, and CaCl2, at different concentrations (1, 5, 10 mM). The CP40 membrane showed 87% rejection for Na2SO4 at 1 mM salt concentration (Figure 5c), comparable to rejection values reported for some commercial nanofiltration (NF) membranes, (90) even though this membrane is not designed or optimized for typical applications of NF such as water softening or salt removal. Other salts are rejected to a lower degree. Salts with higher anionic charge (i.e., SO42– as opposed to Cl) and lower cationic charge (i.e., Na+ as opposed to Ca2+) are rejected better, as predicted for a negatively charged membrane. As ionic strength increases, the rejections of all salts decrease as electrostatic interactions are shielded.
The Donnan exclusion model describes electrochemical equilibria involved when a charged layer, such as a membrane selective layer, is in contact with an electrolyte solution. To determine if the selectivity of the proposed membrane can be modeled by this theory, we fit the salt rejection data to this equation using only the membrane charge density, Cmx, as the fitting parameter (see Supporting Information). The values acquired from the model (Figure 5c) mirror the experimental data perfectly and strongly support the claim that electrostatic interaction is the major separation mechanism in our membrane.
Donnan exclusion model was specifically developed for selective layers with a homogeneous charge distribution, not porous media with charged surfaces. Thus, it is interesting that this model describes salt rejections in this membrane with a nanostructured selective layer. The calculated value of Cmx was 3.65 mM, a much lower value than the actual density of carboxylic groups in the selective layer if all COOH functional groups were assumed to be homogeneously distributed through the selective layer and ionized (see Supporting Information). This mismatch likely arises partially from the trapping of some of the carboxylic groups inside the micelles and from the incomplete dissociation of weakly acidic carboxylic acid groups in water. Furthermore, due to the nanostructure, the carboxyl groups are concentrated on the edges of the channels as opposed to evenly dispersed throughout, leading to lower charge densities in the middle sections of the pores. Overall, while this model describes salt rejection well, better models need to be developed to describe the selectivity of these membranes for organic molecules whose sizes would be more comparable with the nanopores.

Conclusion

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We have demonstrated an innovative approach to manufacturing membranes whose selective layers are formed of packed nanometer scale spherical polymer particles with carboxylate functional groups and showed they can be used for separating small molecule solutes based on their electrostatic charge. We have found that micelles formed by random copolymers of fluorinated TFEMA and carboxyl functional MAA in methanol can be deposited onto porous supports in a densely packed array if the support and the manufacturing methods are selected carefully. The interstices between these micelles act as carboxyl functional nanopores, 1–3 nm in diameter at their narrowest point, through which water and other solutes can pass. Due to electrostatic interactions between solutes and deprotonated carboxylate groups, these membranes can separate organic molecules based on charge, allowing the passage of neutral and positively charged solutes while retaining negatively charged solutes of similar size. Compared with other approaches described in the literature, these membranes exhibited significantly higher permeation selectivity (up to 263, between neutral and anionic solutes), had high water flux, and were manufactured using more scalable, easier methods (Table 3). Furthermore, this selectivity is enhanced in competitive diffusion experiments performed with a mixture of neutral and anionic solutes. The passage of anionic solutes is completely blocked within the 24 h time frame of this experiment, while the permeation rate of the neutral solute is enhanced. Due to the very small effective pore size of the membrane, the entry of favored neutral solutes into the nanochannels prevents the entry of the unfavored anionic solute molecules. Charge-based selectivity is also observed in filtration experiments as anionic solutes are highly retained, neutral solutes are easily permeated, and cationic solutes heavily adsorb on the membrane. The rejection of charged organic compounds decreases with increasing ionic strength, whereas that of neutral solutes remains the same, consistent with a separation mechanism dominated by electrostatic interactions. Salt retention properties of these membranes can be described by the Donnan exclusion model, though further studies are needed to better understand the implications of the presence of the nanoscale structures described. These membranes are promising for applications where charged and uncharged small molecule solutes are separated, such as the manufacture of pharmaceuticals or purification of naturally occurring compounds. Furthermore, the interesting nanostructured selective layer morphology obtained by this method can serve as a platform for the preparation of a wide range of membranes whose selective layers feature networks of functionalized nanochannels, promising for an even wider array of interesting separations.
Table 3. Comparison of the Work Described Here with Other Membranes for Charge-Based Separation of Small Organic Molecules Reported in Literature
methodsmallest pore size (nm)range of available functional groupsease of manufacture and scalabilityporosity/ permeabilityhighest reported selectivity for a charge-based separation of small molecules
gold nanotube membranes (88)0.9very highvery lowvery low13.3
polymer self-assembly inside the PCTE (42)4.5very limitedvery highvery low3.5
NP–Den assembly (44)7highmediummedium11
micelle self-assembly (this work)1–3very highvery highvery high263

Methods

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See Supporting Information for expanded experimental methods.

Polymer Synthesis and Characterization

P(TFEMA-r-MAA) was synthesized using free radical polymerization. A total of 40 g of MAA and TFEMA and AIBN (0.02 g) was dissolved in 100 mL of DMSO. The flask was sealed and purged with nitrogen for 30 min and then heated under stirring at 55 °C for about 4 h. Two grams of MEHQ was added to terminate the reaction. Copolymers were recovered by precipitation in a 1:3 (v/v) ethanol/hexane mixture, redissolved in ethanol, and washed three times in hexane. The product was air-dried overnight and dried in a vacuum oven at 50 °C for 24 h. The yield was approximately 40%.
The synthesized copolymers were characterized using 1H nuclear magnetic resonance (1H NMR) spectroscopy in DMSO-d6 using a Bruker Avance III 500 spectrometer. Molecular weight distribution was acquired using a Shimadzu gel permeation chromatography (GPC) system equipped with a TOSOH TSK gel GMHh-M mixed-bed column and guard column, equipped with both UV and refractive index detectors. THF was used as the mobile phase at 0.75 mL min–1 elution rate and calibrated with low polydispersity poly(styrene) standards (TOSOH, PSt Quick Kit).
To measure water uptake, dry samples were weighed (Wdry) and then equilibrated in deionized water at room temperature. Excess water was removed gently by dabbing with a filter paper, and the sample was weighed (Wwet). Water uptake was calculated using(1)

Characterization of Micelles

The copolymer was dissolved in methanol at a 0.5 wt % concentration and passed through a 0.45 μm syringe filter with Teflon membrane before analysis. DLS was performed using Nano Brook 90Plus PALS particle sizer (Brookhaven Instruments, Holtsville, NY) equipped with a He–Ne laser operated at 659 nm and with a 1 mm entrance aperture at 25 °C and 90° angle.
The nanoscale morphologies of micelles and films were studied by transmission electron imaging (FEI Technai Spirit) operated at 80.0 kV. Samples were prepared by submerging a copper grid with carbon film into a 0.3 wt % copolymer solution in methanol, evaporating the solution for 0–20 s, and floating the grid on a droplet of DI water. Samples were stained using 0.5 wt % aqueous solution of Cu(OAc)2.

Membrane Fabrication and Characterization

Copolymer solutions for membrane preparation were prepared by dissolving 5 wt % of the copolymer in methanol by stirring at 40 °C for 24 h. The solutions were filtered through a 1 μm glass fiber syringe filter (Whatman) and kept in an oven at 50 °C to eliminate bubbles. The bubble and dust-free solutions were spread onto a PAN400 ultrafiltration membrane taped on a glass plate with an adjustable doctor blade (Gardco, Pompano Beach, FL) set to a gap size of 20 μm, which was then immersed into a water bath after 20 s of solvent evaporation at room temperature.
The microstructure of the membrane was characterized by Supra 55 FESEM at 4 kV and 10 mm working distance. Dried membranes were frozen in liquid nitrogen and cut with a razor blade for cross-sectional imaging. Samples were sputter-coated (Cressington 108 manual, Ted Pella Inc., CA) with Au/Pd (60/40) in an argon atmosphere.
Atomic force microscopy measurements were performed with a Dimension 3100 (Veeco, Plainview, NY) on tapping mode. AFM cantilevers were purchased from Bruker with a f0 = 50–100 kHz and k = 1–5 N m–1. Samples were dried and taped on a glass slide. A 10 μm × 10 μm area was scanned. The fast Fourier transform analysis was obtained using Gwyddion software. Membrane hydrophilicity was measured with a Ramé-Hart contact angle goniometer (Succasunna, NJ) on dried membranes cut and taped onto glass plates.

Characterization of Membrane Performance

Diffusion experiments were performed using a side-by-side glass diffusion cell (Permegear) with a cell volume of 7.0 mL and an effective permeation area of 1.8 cm2. A circular membrane swatch 1 in. in diameter was mounted between the two halves of the diffusion cell: feed and sink. A 0.1 mM solution of the desired solute was placed in the feed half-cell, whereas the sink compartment was filled with DI water. Both solutions were continuously stirred to minimize concentration polarization. One milliliter of the solution in the sink was periodically sampled and replaced with DI water. Solute concentration was measured by UV–visible spectroscopy (Thermo Scientific Genesys10S Spectrometer, Waltham, MA).
Filtration experiments were carried out using a 10 mL Amicon 8010 dead-end stirred cell (Millipore) with a filtration area of 4.1 cm2, stirred at 500 rpm, at a transmembrane pressure of 40 psi. Fluxes were measured by following the mass of permeate and collected in a container on a scale (Ohaus Scout Pro) connected to a computer. The membrane permeance (Lp), defined as the flux (J) normalized by applied transmembrane pressure (ΔP), was calculated according to(2)
Membrane selectivity was determined by filtering a series of organic solutes (cationic, anionic, and neutral) at the concentration of 0.1 mM. The first milliliter of filtrate was discarded, and the subsequent 1 mL was collected and used for measuring rejection.(3)where R is the solute rejection and CF and CP are the concentration of feed (0.1 mM) and permeate, respectively. The concentration of organic solutes was measured by UV–visible spectroscopy. Two-solute separation experiments were performed using a similar procedure, but the total solute concentration in the feed was kept at 0.1 mM. Salt retention experiments were carried out using the same system. The first milliliter was discarded, and the subsequent 2 mL was collected. The conductivity of the solution was measured using a conductivity meter (Cole-Parmer, Vernon Hills, IL). Rejections were calculated using eq 3, given that in this concentration range, conductivity is linearly related with salt concentration.
Membranes were soaked in DI water at least overnight between diffusion or filtration experiments to remove any organic solute or salt residues. DI water was filtered through the membranes before subsequent filtration experiments.

Supporting Information

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The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b07596.

  • Expanded experimental methods, DLS micelle size distributions for CP40 and CP50 membranes, FTIR spectra of CP40 and CP50 membranes, TEM micelle size distribution, effect of drying time on selective layer morphology, support membrane surface morphology, PVDF membrane morphology, SEM micelle size distribution, membrane pore size calculation, lattice parameters calculation, effect of pH on membrane permeance and rejection properties, structure and solubility parameter of organic dye molecules, diffusion of dyes through support membrane, single solute and separation of dyes in filtration experiments for the CP50-coated membrane, static adsorption experiments, and calculation of membrane surface charge density (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Ilin Sadeghi - Chemical and Biological Engineering Department, Tufts University, Medford, Massachusetts 02155, United States
    • Jacob Kronenberg - Chemical and Biological Engineering Department, Tufts University, Medford, Massachusetts 02155, United States
  • Notes
    The authors declare no competing financial interest.

Acknowledgment

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We gratefully acknowledge financial support from Tufts University, the Tufts Collaborates program, and the National Science Foundation (NSF) under Grant No. CBET-1553661. FESEM imaging was performed at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the National Science Foundation under NSF Award No. ECS-0335765. CNS is part of Harvard University. TEM was performed utilizing the W.M. Keck foundation Biological Imaging Facility at the Whitehead Institute. We thank N. Watson at the Whitehead Institute for help with TEM data acquisition, Prof. Q. Xu for access to DLS, and Prof. S. Thomas III for access to GPC.

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  • Abstract

    Scheme 1

    Scheme 1. Formation Mechanism of the Membrane Selective Layer Featuring Charged Nanochannelsa

    Scheme a(a) Random copolymer with fluorinated and carboxylated repeat units; (b) formation of micelles in methanol; (c) coated micelles onto a porous support, where they form a packed array of spherical micelles with carboxylic acid functional surfaces. The interstices between the micelles act as effective nanopores through which permeation occurs. Ionized carboxylate groups impart charge-based selectivity through electrostatic interactions.

    Figure 1

    Figure 1. TEM images of the P(TFEMA-r-MAA) micelle assemblies cast from a solution in methanol by immersion into water after (a) no evaporation time, (b) 10 s evaporation, and (c) 20 s evaporation. The insets in (a) and (b) show higher-magnification images (scale bar: 100 nm) of the smaller ∼20 nm micelles, in isolation or in clusters. Large vesicles and small isolated micelle clusters form packed assemblies upon solvent evaporation.

    Figure 2

    Figure 2. SEM micrographs of (a) PAN400 support membrane surface morphology, (b) CP40 membrane surface morphology, (c) CP50 membrane surface morphology, (d,g) PAN400 cross section, (e,h) CP40 cross section, and (f,i) CP50 cross section. Both CP40- and CP50-coated membranes exhibit packed arrays of micelles, interstices between which act as permeation pathways.

    Figure 3

    Figure 3. (a) AFM height image of CP40 membrane (10 μm × 10 μm with z-range of 200 nm), showing spherical micelles packed in a hexagonal close packed (hcp) array with few irregular polygons; (b) 2D FFT pattern corresponding to AFM height image; dashed markings correspond to (q/q*)2 = 1, 3, and 3.7, showing almost 2D hcp structure.

    Figure 4

    Figure 4. Permeation of organic molecules through (a,c) CP40- and (b,d) CP50-coated membranes in (a,b) single-solute and (c,d) competitive diffusion experiments for a mixture of negative and neutral solutes. All experiments demonstrate charge-based selectivity between similarly sized organic solutes. Selectivity between neutral RIB and anionic AB45 is enhanced in competitive diffusion experiments, as the permeation rate of AB45 through both CP40- and CP50-coated membranes is shifted below the detection limit. N is defined as the total number of moles of solute transferred divided by feed concentration.

    Figure 5

    Figure 5. (a) Rejections of organic molecules with different charges by the CP40-coated membranes. Negatively charged solutes (from left to right: MO, AB45, CAL, BBR) are rejected by >85%, whereas low rejections are observed for neutral (from left to right: RIB, RTH, B12) and cationic solutes (from left to right: BB3, Rho6G) of similar size. (b) Effect of ionic strength on dye rejection of the CP40 membrane, consistent with selectivity driven by electrostatic interactions. (c) Rejection of four different salts by the CP40-coated membrane at different feed concentrations. Bars denote experimental data, and filled symbols show values calculated by fitting the Donnan model using a single parameter, Cmx, obtained 3.65 mM.

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    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b07596.

    • Expanded experimental methods, DLS micelle size distributions for CP40 and CP50 membranes, FTIR spectra of CP40 and CP50 membranes, TEM micelle size distribution, effect of drying time on selective layer morphology, support membrane surface morphology, PVDF membrane morphology, SEM micelle size distribution, membrane pore size calculation, lattice parameters calculation, effect of pH on membrane permeance and rejection properties, structure and solubility parameter of organic dye molecules, diffusion of dyes through support membrane, single solute and separation of dyes in filtration experiments for the CP50-coated membrane, static adsorption experiments, and calculation of membrane surface charge density (PDF)


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