Impact of Hydration and Sulfonation on the Morphology and Ionic

Article Cite This: Macromolecules XXXX, XXX, XXX−XXX

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Impact of Hydration and Sulfonation on the Morphology and Ionic Conductivity of Sulfonated Poly(phenylene) Proton Exchange Membranes

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Eric G. Sorte,† Benjamin A. Paren,∥ Christina G. Rodriguez,⊥ Cy Fujimoto,‡ Cassandria Poirier,† Lauren J. Abbott,§ Nathaniel A. Lynd,⊥ Karen I. Winey,∥ Amalie L. Frischknecht,*,§ and Todd M. Alam*,† †

Department of Organic Materials Science, ‡Nanoscale Sciences Department, and §Center for Integrated Nanotechnologies, Sandia National Laboratories, Albuquerque, New Mexico 87185, United States ∥ Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States ⊥ McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States S Supporting Information *

ABSTRACT: Multiple computational and experimental techniques are used to understand the nanoscale morphology and water/proton transport properties in a series of sulfonated Diels−Alder poly(phenylene) (SDAPP) membranes over a wide range of temperature, hydration, and sulfonation conditions. New synthetic methods allow us to sulfonate the SDAPP membranes to much higher ion exchange capacity levels than has been previously possible. Nanoscale phase separation between the hydrophobic polymer backbone and the hydrophilic water/sulfonic acid groups was observed for all membranes studied. We find good agreement between structure factors calculated from atomistic molecular dynamics (MD) simulations and those measured by X-ray scattering. With increasing hydration, the scattering ionomer peak in SDAPP is found to decrease in intensity. This intensity decrease is shown to be due to a reduction of scattering contrast between the water and polymer and is not indicative of any loss of nanoscale phase separation. Both MD simulations and density functional theory (DFT) calculations show that as hydration levels are increased, the nanostructure morphology in SDAPP evolves from isolated ionic domains to fully percolated water networks containing progressively weaker hydrogen bond strengths. The conductivity of the membranes is measured by electrical impedance spectroscopy and the equivalent proton conductivity calculated from pulsed-field-gradient (PFG) NMR diffusometry measurements of the hydration waters. Comparison of the measured and calculated conductivity reveals that in SDAPP the proton conduction mechanism evolves from being dominated by vehicular transport at low hydration and sulfonation levels to including a significant contribution from the Grötthuss mechanism (also known as structural diffusion) at higher hydration and sulfonation levels. The observed increase in conductivity reflects the impact that changing hydration and sulfonation have on the morphology and hydrogen bond network and ultimately on the membrane performance.

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materials.8−12 Hydrocarbon-based PEMs of various compositions have been pursued as alternatives to Nafion and similar PFSA polymers.12 Ideal characteristics of PEMs include high proton conductivity, low fuel and oxidant permeability,

INTRODUCTION Perfluorosulfonic acid (PFSA) polymers, such as Nafion, with flexible, primarily aliphatic side chains are commonly used as proton exchange membranes (PEMs) in fuel cells,1,2 flow batteries,3,4 and electrolyzer5,6 applications.7 However, PFSA polymers’ high cost, environmental processing concerns, low glass transition temperatures, and incompatibility with alkaline environments have motivated the search for alternative © XXXX American Chemical Society

Received: September 18, 2018 Revised: December 20, 2018

A

DOI: 10.1021/acs.macromol.8b02013 Macromolecules XXXX, XXX, XXX−XXX

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ments alone, particularly for systems with complex nanoscale structures.18−21 By combining experimental impedance spectroscopy, NMR diffusion measurements, and MD simulation, additional insight into the proton conduction mechanism and transport can be obtained. Since the original synthesis and characterization of SDAPP,13 several studies have investigated aspects of morphology and conduction in this class of polymers. He et al. performed initial X-ray scattering measurements but failed to observe an ionomer peak characteristic of nanophase hydrophilic domain formation in their studies.22 Structure sizes were instead interpreted from low angle neutron scattering data, which due to contributions from residual catalyst, bubbles, or any other type of density variation are notoriously difficult to interpret. Moreover, no variation in structure was reported as a function of acid concentration. Some of the same authors later published NMR characterization and diffusion measurements, but the reported 1 H NMR chemical shifts are inconsistent with the sulfonic acid speciation known to exist within the hydrated SDAPP membranes.23 An estimate of the hydrophilic domain size based on NMR spin diffusion experiments was initially reported by Cherry and co-workers but was limited to a single sulfonation and hydration level.24 Quasi-elastic neutron scattering measurements of hydrated SDAPP membranes have also been described, showing that the polymer backbone is immobile (the polymer is below its glass transition temperature), while the hydration water is mobile in these membranes.25 In this article we apply multiple characterization and computational techniques to establish the structure− property relationships between the morphology and the proton conduction mechanism in SDAPP as a function of sulfonation and hydration levels. Recently, we have revisited aspects of the local structure and morphology in a series of SDAPP membranes. Fully atomistic MD simulations on SDAPP polymers with varying amounts of sulfonation and hydration have been performed.26 The MD simulations show clear nanoscale phase separation between the polymer backbone and the hydrated hydrophilic domains. We found that at low hydration and sulfonation levels the hydrophilic domains tended to consist of isolated clusters with elongated shapes. As the degree of sulfonation and water content were increased, the hydrophilic clusters became more spherical but also more connected until a fully percolated, hydrated hydrophilic domain was formed. We also investigated the local hydration structure and hydration energies using DFT calculations for SDAPP model clusters and for select hydrophilic domains extracted from the MD simulations.27 The DFT calculations revealed that spontaneous proton dissociation occurs at low levels of hydration to form sulfonic acid-associated H3O+ contact ion pairs (CIPs), which evolve into solvated CIPs at higher hydration levels as the hydrophilic domains become more percolated. These DFT studies also show that the hydration level required for spontaneous dissociation is a function of the extent of sulfonic acid clustering. These same studies demonstrate that the hydration energies are also impacted by the degree of acid clustering within the hydrophilic domains. Finally, we recently developed a methodology for directly comparing 1H NMR spin diffusion experiments to the MD simulations and verified that the MDpredicted SDAPP structures are consistent with the NMR results at low hydration levels.28 In this paper, we focus on a series of SDAPPs synthesized with a new postsulfonation procedure that achieves higher

chemical and mechanical stability, and low cost. We have been exploring a promising class of aromatic hydrocarbon polymers, namely sulfonated Diels−Alder poly(phenylene) (SDAPP, Scheme 1), as possible PEMs.13 SDAPP membranes are Scheme 1. Repeat Unit Structure of a Highly Sulfonated SDAPP Polymer (S = 4)

thermally and chemically robust,13−16 with conductivities rivaling those of Nafion at high sulfonation levels. However, a detailed understanding of the changes in nanomorphology that control proton conduction in SDAPP with varying hydration has been lacking. The morphology of ion-conducting polymer membranes is known to strongly influence their conductivity and other material properties.7,17 In sulfonated PEMs, the hydrophobic polymer backbone naturally segregates from the hydrophilic sulfonic acid groups. Adsorption of water leads to nanoscale phase separation between the polymer backbone and the hydrated sulfonic acid groups, which form hydrophilic domains crucial for proton transport. Synthesis conditions, chemical composition, polymer architecture, and hydration levels can all lead to different internal nanostructures, and researchers over the past few decades have proposed a wide range of structural models and ion transport mechanisms to describe the proton conduction process in PEMs.7,17 The detailed morphology in Nafion remains a matter of some debate; for example, see Kusoglu and Weber and references found therein.7 There is consensus that sufficiently hydrated Nafion consists of nanoscale hydrophilic domains coexisting with semicrystalline domains, and these interpenetrating domains form a disordered, complex morphology.7,17 In PEMs the characteristic size of the hydrophilic domains is typically determined from the broad, low-angle scattering ionomer peak seen in small-angle X-ray scattering. Hydrocarbon-based PEMs are commonly amorphous and show an ionomer peak indicative of nanoscale phase separation, although it is often less intense than that observed in PFSA membranes such as Nafion. This reduced scattering intensity has been interpreted to mean that the phase separation in these polymers between the polymer backbone and the hydrophilic domains is weaker. The morphology of SDAPP membranes is expected to differ from Nafion because of the rigid aromatic backbone and lack of side chain flexibility, thus motivating a careful characterization of these materials. A full understanding of the morphology, and its impact on conductivity, for ionconducting polymers requires the use of multiple characterization methods integrated with simulations. In particular, molecular dynamics (MD) simulations coupled with experimental measurements of the characteristic length scales can reveal more information about the morphology than experiB


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with a heating and cooling rate of 10 °C/min. Thermal gravimetric analysis (TGA) shown in Figure S2 was performed on a Q500 series analyzer (TA Instruments). Approximately 3 mg of membrane was loaded in an aluminum pan in an argon-filled glovebox and crimped with an aluminum hermetic lid. The sample was heated to a maximum of 850 °C with a heating rate of 20 °C/min. Water Uptake. Weight gain as a function of hydration was measured using ∼50 mg of membrane previously dried under vacuum in the presence of P2O5 (Wdry). The membranes were then equilibrated at different relative humidities (RH) in sealed chambers containing the appropriate saturated salt solution,30 ranging from 11% to 98% RH to provide WRH. Weight gain was calculated using

levels of sulfonation, specifically 1.3−3.6 sulfonic acid groups per polymer repeat unit (S), corresponding to ion exchange capacities (IECs) between 1.5 and 3.4 mequiv/g. This degree of sulfonation is larger than is commonly possible in other PEMs (e.g., Nafion) due to the low solubility of the aromatic backbone in water, so that the SDAPP does not dissolve even at high sulfonation. We integrate structural information obtained from MD simulations and X-ray scattering experiments to establish a complete description of the nanoscale morphologies in these SDAPPs. Importantly, we show that the loss of the X-ray scattering ionomer peak with increasing hydration is due to a reduction of scattering contrast and not due to any lessening of nanoscale phase separation between the hydrophilic and hydrophobic domains. Moreover, using a combination of impedance spectroscopy and pulse-fieldgradient (PFG) NMR diffusometry measurements along with the determined morphology, we show that in SDAPP membranes the proton conduction mechanism shifts from being dominated by vehicular transport at low hydration to including a significant contribution from the Grö tthuss structural diffusion mechanism at higher hydration. This comprehensive and multidisciplinary study identifies new directions for molecular design to achieve novel properties in proton conducting membranes.

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wt (%) = 100 ×

WRH − Wdry Wdry

(1)

The IEC (mequiv/g) of the samples was determined by titration of the acidified films. Membranes (approximately 5 cm × 2 cm × 50 μm) were immersed in 50 mL of 1 M Na2SO4 for 24 h. The solutions were then titrated to pH 7 with 0.01 M NaOH. The IEC of the membrane was then computed by IEC =

v base[NaOH] × 103 mdry

(2)

where vbase is the volume of base required to reach the end point, [NaOH] is the base concentration, and mdry is the mass of dry polymer. All IEC values reported are the average of three titrations. For SDAPP the degree of sulfonation S can then be determined from the measured IEC (in mequiv/g) as

MATERIALS AND METHODS

Synthesis. The preparation of the Diels−Alder poly(phenylene) (DAPP) polymer and subsequent sulfonation via chlorosulfonic acid to produce SDAPP (structure of repeat unit shown in Scheme 1) were previously described.13 There, it was noted that insoluble gels were isolated at high ion exchange capacities (IECs) over 2.2 mequiv/g. The gels obtained were presumably due to sulfonyl cross-linking, which has been reported for reactions employing chlorosulfonic acid.13,29 To explore higher sulfonation levels and avoid sulfonyl cross-linking in the polymer, chlorotrimethylsilyl sulfonate was used as the sulfonating agent in this study, as the silyl group prevents extensive coupling compared to the sulfonyl chloride moiety. In a typical reaction, 1 g of DAPP was dissolved in 100 mL of dichloromethane and chilled in an ice bath. To this solution, 0.5 g of chlorotrimethylsilyl sulfonate in 5 mL of dichloromethane was added dropwise over 10 min. The yellow DAPP polymer solution immediately turned dark brown upon addition of the sulfonating agent. The reaction was stirred in an ice bath for 1 h, then removed from the bath, and left to stir at room temperature for 2 h, after which a brown solid precipitate was isolated by filtration. The obtained solid was then soaked in 100 mL of 1 M NaOH solution to form the sodium sulfonate salt. The resulting SDAPP polymer was then rinsed with deionized (DI) water (Barnstead NANOpure, 18 MΩ) multiple times until a neutral pH rinse was obtained, followed by drying under vacuum at 60 °C for 12 h. The SDAPP polymer membrane films were prepared by dissolving the sodium salt of the sulfonated polymer in dimethylacetamide (DMAc) as a 10 wt % polymer solution, filtered through a 2 μm glass microfiber syringe filter onto a glass plate, and placed in a vacuum oven at 60 °C for 15 h. After baking, the SDAPP film was removed from the plate and immersed in DI water (18 MΩ) to remove any additional solvent. The acid form of the polymer was obtained by immersing the film in 2.0 M H2SO4 at 100 °C for 1 h and then washing in DI water to remove residual acid. SDAPP films were stored in DI water until used. Approximate film thicknesses of 20−60 μm were used for all experiments. Thermal Characterization. Differential scanning calorimetry (DSC) was performed using a Q200 series analyzer (TA Instruments) with the results shown in Figure S1 (Supporting Information). Between 5 and 10 mg of membrane was loaded in an aluminum pan in an argon-filled glovebox and crimped with an aluminum hermetic lid. The sample was heated from −50 °C to a maximum of 600 °C

S=

IEC × 760 1000 − IEC × 81 + IEC

(3)

where 760 and 81 are the molecular weights of the SDAPP repeat unit and sulfonic acid group, respectively. The number of waters per sulfonic acid group (λ) for SDAPP can be obtained using eqs 1 and 3 to give λ=

wt %(760 − S) + 81S 100 × 18.01 × S

(4)

Gas Permeability. The pure gas permeabilities of H2, CH4, N2, and O2 were obtained using a custom-built system based on a constant volume/variable-pressure method.31 All SDAPP membranes were dried under vacuum overnight followed by an overnight degassing. The upstream pressure was maintained at predetermined set values of 3.0, 6.4, 9.8, 13.0, and 16.6 atm, while the increase in the downstream pressures across the membrane were recorded as a function of time. The gas permeabilities (P) were determined from the steady-state rate of pressure increase in the downstream volume using31−33 ÄÅ ÉÑ ÅÅi dp y ij dp1 yz ÑÑÑÑ Vdl ÅÅjj 1 zz j z P= = ÅÅj z −j z ÑÑ p2 ART ÅÅÅÅjjk dt zz{ss jjk dt zz{leak ÑÑÑÑ (5) Ç Ö where Vd is the downstream volume, l is the film thickness, p2 is the upstream pressure, A is the area of the film accessible to gas transport, R is the gas constant, T is the temperature, (dp1/dt)ss is the steadystate pressure increment in the downstream, and (dp1/dt)leak is the leak rate of the system. The ideal selectivity was determined by taking the ratio of P for two gases using34 αA/B =

PA PB

(6)

The impact of humidity on the H2 and O2 pressures was also determined using a constant pressure/variable volume apparatus equipped with a hygrometer to determine the effect of humidity on their permeabilities ranging from 0 to 75% relative humidity. Helium gas was used to sweep the downstream side of the membrane and carry the permeate to a gas chromatograph (GC). The partial pressure C


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using 80 kHz 13C pulses, and 66 kHz 1H SPINAL64 decoupling. For the 1H−13C cross-polarization (CP) MAS experiments, contact times were optimized for S/N at 1.5 ms, using 512 scans and a 4 s recycle delay. A single pulse Bloch decay with 1H decoupling was used for the direct acquisition experiments with a 10 s recycle delay. The 1H MAS NMR spectra were obtained on Bruker Avance III 600 spectrometer using a 2.5 mm probe spinning at 30 kHz, with a rotor-synchronized Hahn echo. 13C and 1H NMR chemical shifts were referenced to the secondary standard adamantane (δ(13C) = +38.0 ppm and δ(1H) = +0.8 ppm) with respect to TMS (δ = 0 ppm). The DMFIT software was used for all NMR spectral deconvolutions.43 The 1H pulsed field gradient (PFG) NMR diffusometry experiments were performed on a Bruker Avance-III 600 instrument using a DIFF30 (30 A, maximum strength of 1300 G/cm) z-gradient 5 mm water-cooled diffusion NMR probe at a 1H observed frequency of 600.1 MHz. The bipolar stimulated echo pulse sequence using trapezoidal shape pulses was used, with the translational self-diffusion coefficients (DT) evaluated from the variation in signal intensity with gradient strength S(g) using the Stejkal and Tanner44 relation as implemented in the TOPSPIN software package.

of the penetrant (i.e., O2 or H2) on the downstream side was very close to 0 ( 2).26 These structural changes are further explored with the Xray scattering experiments described later. Once these percolation thresholds are achieved, enhanced transport of water and protons is expected to occur leading to improved conductivity and water diffusion rates, as detailed below. Gas Permeability. A critical issue for PEMs operating at elevated pressures is cross-permeation of gases, where oxygen and hydrogen produced at separate electrodes penetrate the membrane and mix at the counter electrode. This phenomenon degrades fuel cell performance and causes risk of device failure. One mechanism of gas transportation is as a dissolved species in water. Both hydrogen and oxygen are soluble in water,54−59 and thus the water transport through the membranes may also transport gases. The O2 and H2 permeability data for several of the SDAPP membranes are presented in Figures 2a and 2b. For comparison, the permeability for other polymers including unsulfonated DAPP (S = 0, blue triangles), Nafion 117 (green diamonds),10 and the polyphenylene PEM proposed and studied by Miyake and co-workers (SPP-QP, pink stars) are also included.10 Permeation of both O2 and H2 in the DAPP membrane is similar to Nafion. Above 20% RH, the SDAPP membranes provide a superior barrier to both O2 and H2 fuel cell gases compared to Nafion, with the higher SDAPP sulfonation levels demonstrating increased resistance to gas transport. At the highest sulfonation level of S = 3.6, the SDAPP membrane performs comparably to the SPP-QP membrane (IEC = 2.4 mequiv/g, pink stars),10 supporting the argument of using polyphenylene-based membranes while also highlighting the ability to control gas permeation via synthetic variation of the degree of sulfonation. Gas permeability is the product of gas diffusivity (which depends on penetrant gas size, free volume in the polymer matrix, polymer morphology, polarity, and operating temperF


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conditions (thin lines). For a range of humidity conditions, good agreement is found between the experiments and MD simulations at both high and low q. At q > 8 nm−1, the simulations and experiments both contain two peaks at similar λ, and the intensity difference between the two peaks fades as λ increases. The behavior of the ionomer peak is also similar between experiments and simulations as λ increases. The experimental and simulation S(q) data were fit to 3−4 Lorentzian functions to identify the peak positions. The correlation length d* of the ionomer peak was calculated from d* = 2π/q*, where q* is the ionomer peak center. This correlation distance was only identified for values of λ < 10 because at higher water content the ionomer peak becomes difficult to identify in both the experimental and simulation results. The resulting correlation distances are shown in Figure 5a. The correlation lengths from MD simulations agree relatively well with those from scattering and follow the same trends. Historically, d* has been interpreted to represent the average distance between hydrophilic domains. In both the experiments and MD simulations, there is a minor linear increase in d* with λ. This variation is expected due to the swelling of the hydrophilic domains with added water. The experiments and simulations both show larger values of d* for lower sulfonation levels; in principle, this indicates larger distances between hydrophilic domains at lower S. In the literature, the decrease in intensity and loss of the ionomer peak in hydrocarbon PEMs (as seen in Figure 4) has been interpreted to result from a decrease in phase separation between the hydrophilic and hydrophobic domains.68−71 However, examination of real space structural snapshots from the MD simulations as well as cluster analysis shows no apparent loss of phase separation. To further probe nanostructure in the SDAPP membranes, the individual partial structure factors from the MD simulations were calculated. We decompose the full structure factor eq 12 into six partial scattering terms:

Figure 3. Snapshots from MD simulations of SDAPP for S = 1 with λ = 5 (left) and λ = 10 (right) where only the hydrophilic clusters are shown for clarity.

and separated clusters that were only connected by thin bridges into separate clusters. We calculated the radius of gyration and the shape anisotropy of the percolated clusters and found that overall the dense regions of the percolated clusters became more spherical with increasing total water content. Here we further quantify the morphology by calculating the structure factors S(q) from the MD simulations and comparing with experimental SAXS results. X-ray scattering measurements were conducted on the SDAPP S = 2.3 and S = 3.6 membranes at room temperature as a function of RH, with the results reported in terms of λ. The data for S = 2.3 are shown in Figure 4a, while the scattering from the S = 3.6 sample is

Stotal(q) = Spoly + Ssulf + Swater + Swater−poly + Ssulf−poly + Swater−sulf

(14)

Here the poly group consists of the polymer backbone atoms, the sulf group consists of all the SO3− atoms, and the water group includes atoms from both water and hydronium ions. These six partial structure factors, along with the total Stotal(q), are shown in Figure 6a for S = 2 and λ = 10, a system in which the ionomer peak is not readily discernible in either the X-ray scattering or the MD simulations. Partial structure factors for the other simulated systems are qualitatively similar. Strikingly, we see that Spoly and Swater both show a strong peak at low q, roughly where we would expect the presence of the ionomer peak. These peaks are canceled in Stotal by the large negative correlations between the water and polymer atoms, Swater−poly, and the somewhat less negative correlation between the sulfonic acid groups and the polymer atoms, Ssulf−poly. Thus, importantly, the loss of the X-ray scattering ionomer peak is due to a cancellation of correlations, not due to a loss of nanoscale phase separation in the system. Put differently, the ionomer peak gradually vanishes with increasing water content due to a loss of scattering contrast between the water and the polymer backbone. The electron density of all the SDAPP materials is slightly higher in the dry state (within 4%) than that of water but closely approaches the electron density of water as λ increases. The similarity in electron density greatly weakens

Figure 4. (a) X-ray scattering data for a SDAPP membrane (S = 2.3) performed at room temperature under different RH environments, corresponding to λ = 0−16.6, as indicated to the right of each curve. (b) Select experimental data from (a) compared to SDAPP MD S = 2 simulations for λ = 3, 5, 10, and 20. (Data are shifted vertically for clarity.)

similar (see Figure S5). The low wavevector ionomer peak, near q ∼ 2.5 nm−1, decreases in intensity and shifts to lower q (increasing correlation length) with increasing water content for both sulfonation levels. Above λ ∼ 10 the ionomer peak increases again at a lower q in S = 3.6 (see Figure S5). Figure 4b shows some of the experimental traces (points appearing as heavy lines) from Figure 4a together with S(q) calculated from MD simulations of similar IEC and closely matched hydration G


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Figure 5. (a) Correlation length d* for SDAPP membranes calculated from the ionomer peak location in S(q), from both experimental SAXS (exp) and MD simulations (MD). (b) Correlation length d*water from the location of the ionomer peak in the water MD structure factor Swater in eq 14.

Figure 6. (a) Partial structure factors from SDAPP MD simulation for S = 2 and λ = 10. (b) Water partial structure factors (Swater) for S = 2 and λ = 3 (blue), λ = 5 (green), λ = 10 (red), and λ = 20 (black).

the contrast in S(q) between the SDAPP backbone and the water molecules. In Nafion and similar PFSA polymers, there is a clear ionomer peak that increases in intensity and moves to lower q with increasing water content and that has been used to determine hydrophilic domain spacing.7 We note that there is a larger contrast in X-ray scattering between fluorinated groups and water than there is between hydrocarbons and water. Indeed, if we replace the atomic scattering coefficients of the hydrogens bonded to the SDAPP backbone with fluorine scattering values (i.e., we use values of f i for F instead of for the aromatic H in eq 13) and recalculate Stotal(q) from the simulations, we obtain a large ionomer peak in all systems (see Figure S6). We speculate that a similar loss of scattering contrast could occur in other hydrocarbon PEMs with increasing water content, leading to the potentially incorrect conclusion that these polymers exhibit a loss of nanoscale phase segregation with increasing water uptake. A more accurate measure of the spacing between hydrophilic domains in our MD-simulated SDAPP systems can be obtained from the location of the peak in the water partial structure factor, Swater(q). This water structure factor is shown for S = 2 at various λ in Figure 6b (see Figures S7 and S8 for S = 1 and S = 4). The peak grows in intensity and shifts to lower q with increasing λ in all cases. The spacing d*water obtained

from the water structure factor peak is plotted in Figure 5b. As is generally seen in PEMs, the spacing increases roughly linearly with increasing λ. As a reality check on these distances, we calculated the average minimum distance dmin between the centers-of-mass of the clusters in the MD simulations, using the cluster analysis described in our previous work. This interdomain distance is only meaningful for systems with isolated, rather than percolated, clusters. For systems with isolated clusters, we found good agreement between dmin and d*water. For example, for S = 1, λ = 3, we find dmin = 2.2 ± 0.9 nm and d*water = 2.2 nm, and for S = 2, λ = 3, we find dmin = 2.1 ± 0.9 nm and d*water = 2.0 nm. This further verifies that the location of the peak in the water structure factor corresponds to the spacing between the hydrophilic domains. We previously compared the morphology obtained from the MD simulations with NMR spin diffusion measurements.28 In that work, the spin diffusion recovery curves measured for the S = 2.3 sample at λ = 2 and the S = 1.9 sample at λ = 5 were in excellent agreement with calculated NMR spin diffusion curves using the MD-predicted structures.28 This is further evidence supporting the MD representation of the SDAPP morphology on length scales of a few nanometers. On the other hand, attempting to describe the MD simulated structures and the NMR spin diffusion results using simple 3D dispersed domain models shows significant discrepancies in domain size H


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Figure 7. MD predicted (a) volume to surface area (V/S) ratios as a function of water per sulfonic acid and (b) surface to volume (S/V) ratios as a function of hydrophilic phase volume fraction for SDAPP. Results from Nafion (open green symbols) and S/V estimated from d*water (open symbols).

sulfonation levels this is consistent with the formation of more “bulk-like” water environments within the SDAPP membranes at high water content, as suggested by the more spherical shape found in our prior work using the density-based clustering.26 The S/V ratio as a function of ϕhydrophilic also shows a reversal of trends with increasing sulfonation. These trends can be discussed assuming the simple dispersed phase relationship S/ V = 2ϕ dispε/d disp, where ϕ disp = ϕ hydrophilic, ε is the dimensionality of the dispersion, and ddisp is the domain size of the dispersed phase.73 If the dimensionality and domain size remained constant (or decreased) with increasing hydrophilic domain volume fraction (water concentration), S/V would increase linearly. This is what is approximately observed in Figure 7b for S = 1 (black solid circles), suggesting only a slight increase in the domain size of the dispersed phase. If, on the other hand, the domain size simply increased with constant volume fraction, S/V would decrease. At constant ϕhydrophilic, for ϕhydrophilic between 0.2 and 0.6, the MD simulations predict that S/V increases with S. Based on this dispersed phase model, this increase is not due to an increase in hydrophilic domain size with increasing S, but instead there must be some additional inherent structure to produce the increased S/V values for the S = 4 domains. Also note that the correlation distance d*water is smaller for larger S (Figure 5b). The final decrease in S/V at high hydrophilic volume fraction can be understood in terms of increasing domain size. This simple dispersed phase relationship can be used to estimate the S/V based on the characteristic dimensions or correlation length d*water (Figure 5). These are shown as open symbols in Figure 7b where we have assumed ε = 2. These d*water-predicted S/V are much lower than the S/V values calculated directly from the MD simulations (solid symbols) but reveal the same ordering as a function of S. This also supports the argument that a simple dispersed model representation of the MD-predicted hydrophilic domain structures is not adequate and clearly underestimates the S/ V structure present. This is compared to the S/V measured in Nafion from the analysis of the Porod regime assuming a layered morphology.1,74 The SDAPP S/V estimated from the d*water are similar to those in Nafion and hint at the possible

estimations, clearly due to the complex heterogeneous hydrophilic domain structures that occur. These issues with analysis of the experimental NMR spin diffusion results will be described in more detail in a forthcoming paper (Sorte and Alam, unpublished). The characteristic distances we have extracted for SDAPP are similar to Nafion and for other hydrocarbon PEMs. For example, d* from the ionomer peak in Nafion 212 varies from 3.0 to 6.0 nm with increasing λ.51 Previous MD simulations on Nafion have obtained domain sizes and characteristic distances in agreement with X-ray scattering. In particular, Okazaki and co-workers performed atomistic simulations of two PFSA ionomers and calculated both the total structure factor and the water and sulfur partial structure factors.72 They also found good agreement in d* from the ionomer peak with experimental scattering results and found that in these PFSA ionomers the location of the peak in the water structure factor was in most cases identical to d* from the total S(q). There are a few X-ray scattering results for hydrocarbon PEMs in the literature. In several cases, experimenters stained the PEMs with lead acetate or studied a neutralized form of the ionomer (e.g., with Na+) to increase the contrast in X-ray scattering and thus obtain clear ionomer peaks. These studies found characteristic distances ranging from 2.0 to 8.0 nm, depending on the polymer architecture.68−70 Again, MD simulations of these polymers obtained similar characteristic distances as was found in the X-ray scattering. We note that in these cases an artificial contrast was introduced in the calculation of S(q) from the simulations, presumably to enhance the resolution of the ionomer peak.68,71 As a final characterization of the predicted morphology in the MD simulations, we plot the ratio V/S of the total system volume (V) to the surface area (SA) of the hydrophilic domains as a function of λ (Figure 7a). Equivalently, the S/V ratio as a function of hydrophilic volume fraction ϕhydrophilic (which is related to the total water content S*λ) is shown in Figure 7b. The MD simulations predict that for low degrees of sulfonation (S = 1) there is a decreasing V/S with increasing hydration. For the larger S, the volume per surface area initially decreases but then increases for higher λ. At these high I


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Figure 8. (a) Simulated 1H NMR chemical shifts calculated from DFT models. The upper broken line represents the predicted chemical shift for protons in a Zundel cation configuration (pictured in the inset) while the lower dotted line shows the expected shifts for water, both as a function of the correlation parameter q1. The solid line is a fit of all the simulation data (blue + and red ×) to eq 16. (b) Experimental 1H NMR water chemical shifts obtained on SDAPP membranes of all IEC levels as a function of hydration. The solid line is a guide for the eye. As more water is introduced, the proton resonance shifts to lower frequency, indicating decreasing hydrogen bond strengths.

equally between the two oxygens. More positive or negative values of q1 correspond to weaker hydrogen bonds where the H is associated more strongly with one of the oxygens. Correlations between the 1H chemical shift δ and q1 of the form

loss of structural details from analysis of scattering data assuming simplistic models. In the SDAPP membranes the combination of X-ray scattering and MD simulations demonstrates that there is clear nanoscale phase separation between the hydrophobic polymer backbone and the hydrophilic domains for all cases examined. The disappearance of the ionomer peak is a consequence of a reduction in scattering contrast, not a loss of phase separation. The spacing between the hydrophilic domains increases with increasing λ and decreases with increasing S. The hydrophilic domains are disordered and branched but become more spherical with increasing λ and S. Thus, the water is in more bulk-like regions for SDAPPs with higher hydration levels. Local Hydrogen Bond Network. In a hydrated PEM the role of water is central to the ionic conductivity, with the nature of hydrogen bond interactions impacting the proton conduction mechanisms.1,75−77 To further explore the role of water hydrogen bonding in the SDAPP membranes, the experimental 1H NMR chemical shifts as a function of water content (λ) were evaluated to provide a measure of the average hydrogen bond strength. Correlations between 1H NMR chemical shifts and hydrogen bond lengths have been forwarded by several groups,78−81 including for hydrogen bond networks in water and for proton defects in water environments. Limbach and co-workers82 have shown a relationship between the NMR chemical shift and the hydrogen bond coordinates (q1, q2) defined by 1 (r1 − r2) 2 q2 = r1 + r2

δ(1H) = a + b exp[−cq12]

(16)

have been reported for carboxylic acids, water, and protonated Zundel cations, H5O2+.82 Here we use DFT methods to calculate the 1H NMR chemical shifts in a range of possible molecular environments for hydrated sulfonic acid groups in SDAPP. In particular, we calculated the chemical shifts for the optimized hydrated diphenylsulfonic acid (DIP-SA) clusters presented in our previous work.27 For different DIP-SA· n(H2O) clusters (where the number of water molecules varies from n = 1−6) the 1H NMR chemical shift for each proton is shown in Figure 8a, where the blue symbols (+) are for protons in water−water hydrogen bonds, while the red symbols (×) are for protons in sulfonic−water hydrogen bonds. Because there are only minor differences predicted for these two types of hydrogen-bonded environments, they were combined and fit to eq 16 to give the solid correlation line, with a = 2.181, b = 20.32, and c = 8.10. Also shown in Figure 8a are the correlations for the H5O2+ Zundel cation (dashed line) and for large (H2O)n clusters inside a fullerene (C180) cavity (dotted line).82 For increasingly negative q1 values (weaker hydrogen bonds) the chemical shifts of the DIP-SA· n(H2O) (n = 1−6) clusters are more similar to the (H2O)n cluster behavior but begin to approach the behavior of the more strongly hydrogen-bonded Zundel cation H5O2+ as q1 increases (becomes less negative). Because water is highly mobile on the NMR time scale (only a single resonance is observed experimentally at room temperature) in the SDAPP hydrophilic domains, there is a dynamic averaging between different hydrogen bond environments. Experimentally the 1H NMR chemical shift therefore provides an average hydrogen bond strength. Figure 8b shows the measured 1H MAS NMR chemical shifts for all the hydrated SDAPP polymers studied (S = 1.3−3.6), with the

q1 =

(15)

where r1 is the covalent OH distance and r2 is the hydrogen bond HO distance as shown in Figure 8. For a linear hydrogen bond, q1 represents the displacement of the hydrogen from the center (asymmetry) and q2 corresponds to the O···O distance. In general, values of q1 near zero are indicative of strong symmetric hydrogen bonds, where the hydrogen is shared J


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Figure 9. (a) Hydrophilic clusters extracted from SDAPP MD simulations26 used to calculate (b) the 1H NMR chemical shifts using eq 16, along with the average chemical shift noted. The small cluster (left) was obtained from the S = 1, λ = 3 MD simulation, while the larger cluster (right) originated from the S = 4, λ = 10 MD simulation.

hydrophilic domain was obtained from the S = 1, λ = 3 (S*λ = 3) MD simulation and contained 8 sulfonic acid-terminated phenyl side chains, 17 H2O, and 8 H3O+ groups with the cluster having an average radius of gyration of R̅ g = 7.6 Å. The larger hydrophilic domain was extracted from the S = 4, λ = 10 (S*λ = 40) MD simulation and contained 11 sulfonic acidterminated phenyl side chains, 42 H2O, and 11 H3O+ groups with R̅ g = 7.7 Å. The distributions of the 1H NMR chemical shifts for these two clusters are shown in Figure 9b. Because the water and acid proton environments are in rapid exchange with each other on the NMR time scale, the experimentally determined shifts would be an average of these different environments. The resulting average chemical shift is shown in Figure 9b. The reduction in the chemical shift (and correspondingly the hydrogen bond strength) is consistent with the experimental trend shown in Figure 8b. These results support the picture of not only the domain size in SDAPP increasing with hydration but also the decrease of the average hydrogen bond strength. These calculations are for only two select hydrophilic clusters; in reality, the chemical shift averaging should include all the clusters present in the MD simulation unit cell as well as a time average over the entire MD simulation. These results reveal a transition from strongly hydrogen bonded water to more mobile free water molecules (approaching a bulk water environment) with increasing λ. This change should have consequences for water diffusion and conductivity, which we will confirm below. Additionally, the transition to a more bulk-like environment with increasing λ is

NMR spectra being shown in Figure S9. The increased chemical shift with decreasing λ reveals a strengthening of the average hydrogen bond strength with respect to the hydrogen bonding strength present in pure water (where δ = +4.8 ppm). Using the correlation between δ and q1 from Figure 8a gives a change in the hydrogen bond strength from q1 = −0.35 at λ ∼ 1 to q1 = −0.45 at λ > 8. With increasing λ the contribution from the H3O+ speciation (one H+ exists per sulfonic acid) is expected to diminish due to increasing relative concentration of H2O−H2O hydrogen bonding, and at very large λ the chemical shift should finally approach that of pure water (δ = +4.8 ppm). While empirical valence bond (EVB) simulations in hydrated Nafion showed minimal change in the water hydrogen-bonding network structure with increasing hydration,75,83 these NMR results clearly reveal a change in the overall hydrogen bond strength with increasing hydration in SDAPP. The MD predicted morphologies also support this concept of changing hydrogen bond strength. We can use the developed empirical correlation (Figure 8a and eq 16) to calculate the 1H NMR chemical shifts for different hydrophilic clusters extracted from the MD simulations. The size of the MD clusters precludes a direct DFT NMR chemical shift calculation due to our computational limitations, but eq 16 is based entirely on O−H bond distances and is readily evaluated. As an example of the evolution of the hydrogen bond strength with increasing hydration levels, two hydrophilic clusters (Figure 9a) were extracted from the MD simulation and the 1H NMR chemical shifts estimated. The small K


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Figure 10. (a) Proton conductivity for SDAPP as measured by impedance spectroscopy as a function of IEC at low temperature/low RH (■) and elevated temperature/high RH (●). (b) SDAPP conductivity for different IECs as measured by impedance measurements as a function of relative humidity at 80 °C. For comparison, Nafion conductivity is shown in (a) and (b) as open symbols.

the second solvation shell of the sulfonate groups but that this does not hinder their motion.75,84 Instead, the solvated excess protons easily move between adjacent sulfonate groups due to a flat free energy surface between them. We expect a similar mechanism may occur in SDAPP. The sulfur−sulfur radial distribution function in SDAPP has a large initial peak at low hydration, but the peak merges with the second solvation shell peak at high hydration (see Figure 2 in ref 26), indicating a good overlap between the solvation shells of adjacent sulfonate groups. Furthermore, the MD simulations in SDAPP show the hydronium is highly likely to be in the second solvation shell of one or two sulfonates at high hydration (see Figure S15b). This would then allow the solvated hydronium (proton) to easily move among adjacent sulfonate groups in the hydrophilic domains at high hydration. The decrease in surface area with increasing λ for S = 4 (Figure 7B) would promote this effect due to the sulfonate groups being closer together along the hydrophilic domains.84 Proton Conductivity and Diffusion. Proton conductivity data for the SDAPP membranes were obtained from complex impedance measurements (σImp) as a function of both temperature (at fixed hydration levels) and hydration level (at fixed temperatures) and are presented in Figure 10. Through-plane conductivity for SDAPP at low temperature and low humidity (black squares) and at elevated temperature and high humidity (red circles) as a function of IEC are shown in Figure 10a, where the open symbols show the conductivity of Nafion 117 (IEC = 0.91) and Nafion 212 (IEC = 0.48 mequiv/g) under similar conditions. Note that the Nafion membranes contain significantly fewer sulfonic acids per gram of polymer (lower IECs) than the SDAPP membranes and therefore have a lower H+ concentration available for transport. In contrast to Nafion, in SDAPP the degree of sulfonation is one of the variables that can be widely modified because the rigid hydrophobic polyphenylene backbone prevents highly sulfonated membranes from becoming water-soluble (see Table 1). Figure 10b shows the conductivity of SDAPP at elevated temperature (80 °C) as a function of relative humidity over a range of sulfonation levels. Open symbols represent the conductivity of Nafion 212 under the same conditions. Figure 10 reveals that the conductivity of SDAPP is a strong function of sulfonation level, the temperature, and the water content. Optimal conditions to maximize SDAPP proton

consistent with the morphological changes found in the MD simulations. At a more local level, the MD simulations also provide information about the coordination environment of the hydronium. We previously calculated the distribution of coordination numbers for the hydronium with both the sulfonate groups and with water/hydronium ions, using cutoffs based on the first peak in the relevant radial distribution function. As shown in Figure 3 of ref 26, at low hydration and sulfonation, the hydronium is most likely to be coordinated to 2 sulfonic acids and 1 water. As the sulfonation and hydration levels increase, the hydronium becomes more likely to be dissociated from the sulfonic acid groups and instead only coordinated with water (or other hydroniums). For example, for S = 4, the hydronium spends 25% of the time away from the first solvation shell of any sulfur atom at λ = 10 (S*λ = 40) and 44% of the time away at λ = 20 (S*λ = 80) as shown in Figure S14. Thus, the hydronium forms fewer CIPs at high sulfonation and hydration. This hydrogen bond strength variation highlights the interplay between structural reorganization of the hydrating water and high proton transfer rates. Strong hydrogen bonds favor proton transfer between oxygens, while the structural reorganization around a hydrated hydronium is hindered by strong hydrogen-bonding networks.1,75,76 The increased proton conduction in bulk water occurs due to the numerous hydrogen-bonding interactions between multiple waters and protons in the extended network that can produce a reduction in the hydrogen bond strength. This cooperative effect thus allows for structural reorganization of the hydrogen-bonding network.76 For this process the activation energy for the overall proton transport process is dominated by the hydrogen bond breaking and formation.1,76 The interaction energies between the sulfonate anion and the hydronium cation are also modulated by the local hydrogen bond network and impact the movement of the CIP from the anion to a solvated state which ultimately contributes to the proton transport efficiency.75,83 These NMR results argue that the decreasing hydrogen bond strength with increasing hydration levels will allow an enhanced contribution from the Grötthuss mechanism to the overall conductivity as demonstrated below. There may also be a contribution from a “sulfonate passing mechanism” at high hydration. Reactive MD simulations of PFSAs have found that the solvated protons are often found in L


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Figure 11. (a) Proton conductivity of SDAPP at high (S = 3.6, IEC = 3.4) and intermediate (S = 2.3, IEC = 2.4) sulfonation at high and low temperature. (b) Same membranes as in (a) scaled to the molar conductivity to remove H+ concentration effects.

compares the conductivities (Figure 11a) and the molar conductivities which are concentration independent (Figure 11b) for SDAPP at two different sulfonation levels and temperatures. As expected, increasing the degree of sulfonation (IEC) from S = 2.3 to 3.6 improves the proton conductivity due to the increased carrier concentration, especially at higher hydration levels. More surprisingly, the molar conductivity (Figure 11b) also shows a difference between different sulfonation levels, even when CH+ has been normalized out. This strong dependence on hydration for high S levels remains even when scaled to the total number of waters S*λ (or equivalently water volume fraction) and thus is not simply because of the increase in water content (see Figure S12). In addition, these differences in conductivity as a function of S are observed over the full temperature range studied. In contrast, the proton conductivity of acidic aqueous solutions decreases with increasing acid concentration.87 This has been shown to result from a decrease in the contribution from the Grötthuss mechanism (structural diffusion) resulting from changes in the hydrogen bond network.1 The observation of conductivity increasing with higher S in the SDAPP membranes argues that there must be changes in the local nanostructure of the hydrophilic domains and/or changes in the water environment that significantly impact the proton transport. As discussed above, one possible change is the association of the hydrated proton (hydronium) to multiple sulfonic acid groups in their second solvation shell at S = 4 as compared with S = 2 (Figure S15b), allowing increased conductivity by proton shuttling among neighboring sulfonic acids. It is expected that the behavior of H+ in confined nanophase-separated hydrophilic domains will be distinct from their behavior in bulk water. Simulations of Nafion by Voth and co-workers have suggested that the picture of vehicular transport dominating to account for poor conductivity at low hydration levels is oversimplistic.75,83,84,88 Their simulations suggest that overall conductivity depends on the ability of proton transfer to contribute constructively (for the proton to move away from its original position) as opposed to nonconstructively (local motion that does not involve longrange transport of the proton). At low hydration levels, the dissociated proton is effectively trapped in a CIP and cannot readily contribute to long-range proton transport. In SDAPP, the formation of a CIP is supported by our recent DFT simulations27 where it was found that at λ ∼ 3 the sulfonic acid proton spontaneously dissociates. The exact λ of hydration for

conductivity would be to produce membranes with high sulfonation levels (≥3 mequiv/g) and to operate at high humidity and elevated temperatures. Under these conditions, ionic conductivities exceeding 160 mS/cm are observed and are comparable to or better than those of Nafion, which vary from 10 to 100 mS/cm as relative humidity varies from 20 to 95% RH at equivalent weights of 1100 (IEC = 0.91 mequiv/g). At low RH% and low temperature SDAPP has higher proton conductivity than Nafion for membranes with S > 2 (IEC > 2.2 mequiv/g). Conductivity is ultimately related to the concentration of H+ and the transport rate through the membrane and is commonly described by the Nernst−Einstein relationship for electrolyte solutions as σ=

F 2(C+q+D+ + C −q−D−) RT

⇒σ=

F 2C H+D H+ RT

(17)

where F is Faraday’s constant, R is the gas constant, T is the temperature, C± and q± are the carrier concentrations and charges, and D+ and D− are the diffusion rates of the cation and anion species. In PEMs (including SDAPP) the sulfonate groups (SO3−) are covalently linked to the polymer and are essentially immobile (D− ≈ 0). In this limit the concentration (CH+) and diffusivity (DH+) of the H+ controls the conductivity (eq 17). The concentration of the H+ depends on S and on the degree of the acidic proton dissociation (see the Supporting Information). The pKa for a triflic acid is −12,85 while for a benzenesulfonic acid the value is ∼−6.5.86 Changes in the degree of dissociation will be a function of both temperature and the local morphology where clustering of the sulfonate groups has been shown to impact the minimum hydration level where spontaneous deprotonation of the sulfonic acid occurs.27 The motions of the local polymer chains can also influence σ. For example, dynamics in PFSA polymers allows the side chain to explore more of the hydrophilic domains, resulting in improved efficiency of protons being passed between different sulfonic acid groups, while shorter side chains can prevent the sulfonic acid groups and associated protons from fully exploring the hydrophilic regions.83,84 For the SDAPP membranes side-chain dynamics are expected to be minimal due to the rigidity of the polyphenylene structure and the high Tg of the polymer. It is also instructive to remove the H+ concentration (CH+) dependence from the conductivity (eq 17). Figure 11 M


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Nafion where the water proton D varies linearly from 6 × 10−11 to 5.8 × 10−10 m2/s between λ = 2−14.90 In rigid aromatic systems with short side chains, such as sulfonated poly(ether ketone)s, diffusion constants also vary by a factor of 10 or more over the hydration range.91 In SDAPP, D increases with IEC (i.e., S) and is approximately linear over the range studied. The variation with IEC is more pronounced at higher hydration levels. The overall increase in D with increasing hydration suggests that the water protons on average spend less time associated with the sulfonic acid, with a higher fraction in more bulk-like water environments where the Coulombic attraction to the sulfonic acid is weaker or the domain topology is less restrictive such that the diffusion is less hindered. Equivalently, the increasing D may also be impacted by the reduction in the hydrogen bond strength of water/ proton species in the hydrophilic domains. This trend is further supported by Figures S10 and S11, which show D as a function of λ and reciprocal temperature, and is consistent with results from other PEMs. Proton conductivity is a sum of contributions from surface, Grötthuss, and vehicular transport mechanisms:7

dissociation was found to be a function of the number of sulfonic acids clustered together, with the critical λ reduced with an increasing number of acids in the cluster. For λ ≥ 6 hydrated H3O+ or solvated CIP environments are energetically favored, as opposed to the H3O+−sulfonate anion CIP, leading to a more bulk-like water environment for the acidic proton.27 Continuous hydrogen bond networks have also been argued to be important for shuttling of protons between different sulfonate groups on poly(phenyl sulfone) ionomers.75,83,84,89 Water Diffusion. To further elucidate the proton transport mechanisms in SDAPP, we used PFG NMR diffusometry to measure the diffusion rate D of water (vehicular transport) in SDAPP membranes as a function of IEC and RH at room temperature (Figure 12). The water diffusion rate increased by

σ=

F 2 Surf Surf Grott Veh + C + + C + ) (D H+ C H+ + D HGrott + D HVeh H H RT

(18)

where Ci and Di are concentrations and diffusion rates of protons for these different mechanisms. The surface diffusion refers to the direct transport of H+ between different surface sites along the hydrophilic domain surface (e.g., sulfonic acid groups), while the Grö tthuss mechanism describes the dynamic motion of H+ defects through hydrogen-bonded networks of the hydrated hydrophilic phase. This mechanism is responsible for the higher than expected conductivity observed in pure water. Agmon92 originally described how the series of bond breaking and forming events results in the transfer of protons through a hydrogen-bonded network via reorientation of water molecules on the picosecond time scale, which is only possible in relatively free water molecules. The description of this process has subsequently been changed to instead involve a coherent hydrogen bond formation/breaking process leading to H+ displacement.1,75,76,83 The vehicular mechanism describes the bulk transport or diffusion (en masse) of the H3O+ within the hydrophilic domain. Proton conductivity

Figure 12. Water self-diffusion rates in SDAPP membranes (298 K) at different hydration levels as a function of IEC.

an order of magnitude, from 1 × 10−11 to 5 × 10−10 m2/s, between 33% RH and 98% RH conditions. This is similar to

Figure 13. (a) Proton conductivity as measured by PFG-NMR diffusometry (solid shapes) and impedance measurements (open shapes) for a range of membranes at high RH (≥90%). Solid lines are linear fits to solid symbols, while the broken lines are linear fits to open symbols. (b) Constant temperature correlation of the conductivity obtained by impedance (σImp) and by NMR (σNMR). N


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conductivity amplification factor has been observed to be as high as 2.5 in hydrated Nafion but is generally near 2 for highly sulfonated and highly hydrated samples, decreasing to 1 (or slightly less) for low water contents.93 The trends found here for SDAPP are similar to those seen in numerous Nafion studies, where higher values of σImp versus σNMR reveal that the Grötthuss mechanism has become dominant.1,90,94−99 There is no clear distinction in nanoscale morphology between the MD-simulated S = 2 and S = 4 systems at high water content that would explain the increasing σImp/σNMR above S = 2.5, with both systems exhibiting percolated hydrophilic domains. The S = 4 structures show a slightly higher S/V ratio at low λ but are similar at higher λ (see Figure 5). Also, tortuosity effects on the percolation pathways would be reflected in σNMR, but since D increases with IEC (Figure 12), this does not explain the increasing σImp/σNMR. However, we previously showed that in the MD simulations the hydronium exists in a wider range of coordination states with the sulfonic acids and water for S = 4 than for S = 2, even at the same total water content (S × λ) (see Figure 3 in ref 26), allowing an increased proton mobility. We note also that as water is added to SDAPP at a given S, the conductivity mechanism and temperature dependence also change to produce an enhanced conductivity (Figure 13 and Figure S13). The increase in conductivity with IEC and hydration in SDAPP can thus be understood as arising from the percolation of the hydrophilic domains and also from the evolution to a less strongly bound hydrogen bond network as water is added to the membrane and the hydrophilic domains become more bulk-like. Conductivity Activation Energy. Reactive MD simulations have indicated that different mechanisms contribute to ionic diffusion in membranes under different conditions.84,100 While definitive ionic diffusion mechanisms in polymer membranes continue to be strongly debated,7 measurements of activation energies of conductivity by different methods provide additional insight into the mechanisms at play in SDAPP. Assuming an Arrhenius relationship for each individual mechanism that contributes to the overall proton conductivity σ (as measured by electrical impedance), the temperature dependence can be related to the proton diffusion DH+ and the activation energy Ea for each mechanism. It is important to note that temperature dependence may be nonArrehnius if there are different conduction mechanisms with similar relative contributions, since they describe different transport processes and may have very dissimilar activation energies. The Ea for σNMR will only be equal to the activation energies determined by the PFG NMR experiments, Ea(NMR), when the vehicular transport mechanism is dominant. The temperature dependence of the conductivity is given by (see the Supporting Information for additional details)

within PEM membranes has been argued to include contributions primarily from vehicular diffusion of the water/ hydronium and from proton motion via the Grötthuss mechanism (structural diffusion).7,75,83,84,92 The relative contributions of these different conductivity mechanisms will vary with pressure, temperature, and hydration level and ultimately with local morphology. Insight can be gained into the proton conductivity mechanisms occurring in SDAPP under different conditions by comparing the electrical impedance conductivity values (σImp) from Figure 10 to conductivity estimated from water diffusion coefficients as measured by PFG NMR diffusometry (Figure 12). We define the NMR conductivity, equivalent to the contribution from the vehicular transport mechanism, as σNMR =

F 2C H−DH2O RT

(19)

where DH2O is the self-diffusion rate of water and is argued to be equivalent to the diffusion rate of H3O+. It has been suggested by Agmon92 that DH3O+ < DH2O based on increased hydrogen bonding in the first hydration shell, but this would further decrease the predicted conductivity. For SDAPP, the 1 H NMR does not resolve between those waters/protons associated at the hydrophilic domain surface and those waters elsewhere in the hydrophilic domain due to rapid chemical exchange, such that D from PFG NMR is a weighted average of water at both the surface and internal domain environments. Electrical impedance measurements measure the total proton conductivity (σImp) from one electrode to the other and thus will include contributions from both the vehicular diffusion mechanism and the Grötthuss mechanism. By comparison of σImp to σNMR, the difference can be attributed to the Grötthuss mechanism. Kreuer and co-workers have also shown that the contributions from the Grötthuss and vehicular transport mechanisms in hydrated Nafion can be identified.1,7,91,93 The impedance and NMR-based conductivity measurements for SDAPP are compared in Figure 13 at high hydration levels and in Figure S13 for low hydration conditions. These figures show several illuminating aspects which bear discussion. First, at low IEC (S ≤ 2.5, Figure 13a) the magnitudes of the σImp and σNMR are very similar (compare the open and solid symbols of the same shape). This suggests that under these hydration and temperature conditions and for low S, the dominant conductivity mechanism is vehicular diffusion. Additionally, the temperature dependence of σImp and σNMR are similar and reflective of the diffusion rate activation energies (see additional discussion below). Numerous studies have found similar behavior in Nafion: at low and intermediate degrees of sulfonation or hydration, the proton motion is dominated by the vehicular transport mechanism.1,90,94−98 For SDAPP membranes with increasing IEC values (S ≥ 2.5) differences between σImp and σNMR become apparent. The σImp becomes larger than σNMR and shows different temperature behavior. This suggests that the Grötthuss mechanism is now making a significant contribution to the conductivity (eq 18). We note that the temperature variation of σNMR remains consistent between high and low IEC, showing that the vehicular diffusion process has not changed; it is simply not making as large of a contribution to the overall σ. Figure 13b shows the correlations between σImp and σNMR at a given temperature. For the lower IEC membranes, σImp/σNMR is ∼1, but this ratio approaches 2 with increasing IEC. This

σ(T ) =

F 2C H+ Grott [D0 exp(−EaGrott /RT ) + D0Veh exp(−EaVeh /RT )] RT

(20)

The conductivity activation energies can be evaluated by plotting ln(σ × T) vs 1/T in Figure 13 and are presented in Table 2. These activation energies are similar to those reported for other membrane systems. A wide range of activation energies for fully hydrated Nafion membranes have been reported in the literature, from a low of 1 kJ/mol101 to 10−29 kJ/mol.102,103 More rigid systems reduce water mobility and thus tend to have higher activation energies; sulfonated O


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by the vehicular transport mechanism. At both high S and high λ, the surface to volume ratio begins to turn over, consistent with an increasing domain size or bulk-like water environment and decreasing hydrogen bond strengths, leading to improved conductivity. These morphological changes allow the Grötthuss mechanism to contribute more to the proton conductivity under these conditions.

Table 2. Activation Energies (in kJ/mol) As Measured by NMR Diffusion and Impedance Conductivity RH (%) NMR S S S S

= = = =

1.9 2.3 2.8 3.6 Imp

S S S S S

= = = = =

1.3 1.9 2.3 2.8 3.6

33

65

31.3 30.4 29.0 31.8

25.8 26.4 24.7 24.7

75 22.2 22.9 22.6 21.1 RH (%)

98 20.4 19.1 20.1 19.0

20

50

90

18.1 17.3 16.0 13.1 15.3

18.9 19.0 19.7 12.0 14.3

20.6 21.0 21.0 10.4 9.2

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CONCLUSIONS We have used multiple computational and experimental techniques to characterize the nanoscale morphology and water/proton transport properties in a series of SDAPP polymers over a wide range of temperature, hydration, and sulfonation conditions. Structure factors calculated from MD simulations were found to be in good agreement with those measured by X-ray scattering. We demonstrated that the experimentally observed loss of the ionomer peak with increasing hydration is due to a reduction of scattering contrast between the water and polymer and is not indicative of decreasing nanoscale phase separation in SDAPP. On the contrary, the MD simulations predict an increasingly strong phase segregation at higher hydration levels, as quantified by the water partial structure factor. Both MD simulations and DFT calculations show that as hydration is increased, the nanoscale morphology in SDAPP evolves from isolated ionic domains to fully percolated water networks with progressively weaker hydrogen bond strengths, but with larger domains of hydrogen-bonded water/proton species. The increasing hydrophilic domain sizes and correlation distances as a function of water content are also consistent with the water uptake and gas permeability measurements. The trends in the measured conductivity are explained in terms of the nanoscale structure and transport properties of the hydrogen-bonded water network present in the polymer membranes. The comparison of impedance spectroscopy and PFG NMR diffusometry measures of conductivity indicate a change in conduction mechanism as the SDAPP structure evolves with increasing hydration and IEC. This changes from a primarily vehicular diffusion mechanism to a hybrid mechanism with increasing contributions from the Grötthuss conductivity mechanism, as has been observed in Nafion and other PEMs. The increased contribution from the Grötthuss conductivity mechanism at high sulfonation is correlated more with changes in the hydrogen bond network strength than with any qualitative changes in the nanoscale morphology. New synthesis methods have allowed us to sulfonate the SDAPP membranes to much higher levels than has been previously possible, opening the door to more practically functional membranes with conductivities exceeding those of Nafion under optimal conditions and with superior gas barrier properties.

aromatic PEEK has been reported to have activation energies ranging from 30 to 90 kJ/mol depending on hydration.104,105 Under both humid and dry conditions, the activation energies of SDAPP are higher than those of Nafion, showing that proton transport requires more energy in the more rigid polyaromatic polymers. At high RH the low IEC membranes’ σImp and σNMR activation energies are similar (Figure 13), while for high IEC the activation energies of σImp are lower and most likely reflect the increasing contribution from the Grötthuss mechanism (expected to be in the range of 14−40 kJ/mol).106 The activation energies for σNMR all increase with decreasing levels of hydration. This has been observed in different membrane systems and reflects the loss of percolation and the increase in interaction between the water and the SDAPP polymer. Previous examples in Nafion have shown similar Ea behaviors for σImp and σNMR with changing hydration levels. This does not appear to be the case for SDAPP at low hydration levels, where activation energies of σNMR are higher than σImp for all IECs. Differences in the measured Ea would be expected as the Grötthuss and vehicular mechanisms describe very different processes. Equation 20 predicts that non-Arrhenius behavior, or a change in the apparent Ea, can occur if the relative fractions of the two conduction mechanisms change significantly over the temperature range studied and if the activation energies for the individual mechanisms are different. This may explain why the slope of the σImp temperature dependence becomes larger at lower temperature for the S = 2.8 and 3.6 membranes. The temperature dependence of σImp(T) is only equal to σNMR(T) if the vehicular mechanism is the only dominant process. The activation energies for σImp increase slightly as hydration increases for low IEC membranes but decrease with increasing humidity for high IEC SDAPP membranes. These differences are not presently fully understood but most likely reflect competing effects of structure changes, percolation, and the contributions from different conductivity mechanisms that are difficult to resolve. These conductivity and diffusion results now provide a consistent picture involving the hydrogen bond network and hydrophilic domain morphology. At low λ and S, the hydrophilic domains are isolated and have strongly hydrogen-bonded protons associated with the sulfonic acid groups, resulting in low conductivity. At low S and high λ, we have percolated water domains with hydrogen-bonded networks of limited size, resulting in relatively low conductivity dominated

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ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.macromol.8b02013. Figures S1−S15 and discussion on the temperature dependence of proton conductivity (PDF) P


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(8) Hickner, M. A.; Ghassemi, H.; Kim, Y. S.; Einsla, B. R.; McGrath, J. E. Alternative Polymer Systems for Proton Exchange Membranes (PEMs). Chem. Rev. 2004, 104 (10), 4587−4612. (9) Maier, G.; Meier-Haack, J. Sulfonated Aromatic Polymers for Fuel Cell Membranes. In Fuel Cells II; Springer: 2008; pp 1−62. (10) Miyake, J.; Taki, R.; Mochizuki, T.; Shimizu, R.; Akiyama, R.; Uchida, M.; Miyatake, K. Design of Flexible Polyphenylene ProtonConducting Membrane for Next-Generation Fuel Cells. Sci. Adv. 2017, 3 (10), No. eaao0476. (11) Rikukawa, M.; Sanui, K. Proton-Conducting Polymer Electrolyte Membranes Based on Hydrocarbon Polymers. Prog. Polym. Sci. 2000, 25 (10), 1463−1502. (12) Shin, D. W.; Guiver, M. D.; Lee, Y. M. Hydrocarbon-Based Polymer Electrolyte Membranes: Importance of Morphology on Ion Transport and Membrane Stability. Chem. Rev. 2017, 117 (6), 4759− 4805. (13) Fujimoto, C. H.; Hickner, M. A.; Cornelius, C. J.; Loy, D. A. Ionomeric Poly(phenylene) Prepared by Diels-Alder Polymerization: Synthesis and Physical Properties of a Novel Polyelectrolyte. Macromolecules 2005, 38 (12), 5010−5016. (14) Hickner, M. A.; Fujimoto, C. H.; Cornelius, C. J. Transport in Sulfonated Poly(phenylene)s: Proton Conductivity, Permeability, and the State of Water. Polymer 2006, 47 (11), 4238−4244. (15) Small, L. J.; Pratt, H. D.; Fujimoto, C. H.; Anderson, T. M. Diels Alder Polyphenylene Anion Exchange Membrane for Nonaqueous Redox Flow Batteries. J. Electrochem. Soc. 2016, 163 (1), A5106−A5111. (16) Tang, Z.; Lawton, J. S.; Sun, C.-N.; Chen, J.; Bright, M. I.; Jones, A. M.; Papandrew, A. B.; Fujimoto, C. H.; Zawodzinski, T. A. Characterization of Sulfonated Diels-Alder Poly (Phenylene) Membranes for Electrolyte Separators in Vanadium Redox Flow Batteries. J. Electrochem. Soc. 2014, 161 (12), A1860−A1868. (17) Mauritz, K. A.; Moore, R. B. State of Understanding of Nafion. Chem. Rev. 2004, 104 (10), 4535−4586. (18) Buitrago, C. F.; Bolintineanu, D. S.; Seitz, M. E.; Opper, K. L.; Wagener, K. B.; Stevens, M. J.; Frischknecht, A. L.; Winey, K. I. Direct Comparisons of X-ray Scattering and Atomistic Molecular Dynamics Simulations for Precise Acid Copolymers and Ionomers. Macromolecules 2015, 48 (4), 1210−1220. (19) Hall, L. M.; Seitz, M. E.; Winey, K. I.; Opper, K. L.; Wagener, K. B.; Stevens, M. J.; Frischknecht, A. L. Ionic Aggregate Structure in Ionomer Melts: Effect of Molecular Architecture on Aggregates and the Ionomer Peak. J. Am. Chem. Soc. 2012, 134 (1), 574−587. (20) Trigg, E. B.; Gaines, T. W.; Maréchal, M.; Moed, D. E.; Rannou, P.; Wagener, K. B.; Stevens, M. J.; Winey, K. I. SelfAssembled Highly Ordered Acid Layers in Precisely Sulfonated Polyethylene Produce Efficient Proton Transport. Nat. Mater. 2018, 17, 725−731. (21) Trigg, E. B.; Stevens, M. J.; Winey, K. I. Chain Folding Produces a Multilayered Morphology in a Precise Polymer: Simulations and Experiments. J. Am. Chem. Soc. 2017, 139 (10), 3747−3755. (22) He, L.; Fujimoto, C. H.; Cornelius, C. J.; Perahia, D. From Solutions to Membranes: Structure Studies of Sulfonated Polyphenylene Ionomers. Macromolecules 2009, 42 (18), 7084−7090. (23) He, L.; Cornelius, C. J.; Perahia, D. Water Dynamics within a Highly Rigid Sulfonated Polyphenylene. Eur. Polym. J. 2014, 56, 168− 173. (24) Cherry, B. R.; Fujimoto, C. H.; Cornelius, C. J.; Alam, T. M. Investigation of Domain Size in Polymer Membranes Using Double Quantum Filtered Spin Diffusion MAS NMR. Macromolecules 2005, 38, 1201−1206. (25) Osti, N.; Etampawala, T.; Shrestha, U.; Aryal, D.; Tyagi, M.; Diallo, S.; Mamontov, E.; Cornelius, C.; Perahia, D. Water Dynamics in Rigid Ionomer Networks. J. Chem. Phys. 2016, 145 (22), 224901. (26) Abbott, L. J.; Frischknecht, A. L. Nanoscale Structure and Morphology of Sulfonated Polyphenylenes Via Atomistic Simulations. Macromolecules 2017, 50 (3), 1184−1192.

AUTHOR INFORMATION

Corresponding Authors

*(T.M.A.) E-mail [email protected]. *(A.L.F.) E-mail [email protected]. ORCID

Christina G. Rodriguez: 0000-0001-8681-4002 Lauren J. Abbott: 0000-0003-3523-9380 Nathaniel A. Lynd: 0000-0003-3010-5068 Karen I. Winey: 0000-0001-5856-3410 Amalie L. Frischknecht: 0000-0003-2112-2587 Todd M. Alam: 0000-0002-1047-1231 Present Address

L.J.A.: AMA Inc., NASA Ames Research Center, Moffett Field, CA 94035. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank Patricia Sawyer for providing the DSC and TGA measurements. This research was funded by the Sandia Laboratory Directed Research and Development (LDRD) program, including student support through the Academic Alliance LDRD program (C.G.R.). This work was performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under Contract DE-NA-0003525. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The X-ray scattering facility at the University of Pennsylvania is supported by NSF-MRSEC (1720530), while B.P. and K.I.W. also acknowledge support from NSF PIRE (1545884).

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REFERENCES

(1) Kreuer, K.-D.; Paddison, S. J.; Spohr, E.; Schuster, M. Transport in Proton Conductors for Fuel-Cell Applications: Simulations, Elementary Reactions, and Phenomenology. Chem. Rev. 2004, 104 (10), 4637−4678. (2) Peighambardoust, S. J.; Rowshanzamir, S.; Amjadi, M. Review of the Proton Exchange Membranes for Fuel Cell Applications. Int. J. Hydrogen Energy 2010, 35 (17), 9349−9384. (3) Huskinson, B.; Marshak, M. P.; Suh, C.; Er, S.; Gerhardt, M. R.; Galvin, C. J.; Chen, X.; Aspuru-Guzik, A.; Gordon, R. G.; Aziz, M. J. A Metal-Free Organic−Inorganic Aqueous Flow Battery. Nature 2014, 505 (7482), 195. (4) Li, B.; Gu, M.; Nie, Z.; Shao, Y.; Luo, Q.; Wei, X.; Li, X.; Xiao, J.; Wang, C.; Sprenkle, V.; Wang, W. Bismuth Nanoparticle Decorating Graphite Felt as a High-Performance Electrode for an All-Vanadium Redox Flow Battery. Nano Lett. 2013, 13 (3), 1330−1335. (5) Siracusano, S.; Baglio, V.; Navarra, M.; Panero, S.; Antonucci, V.; Arico, A. Investigation of Composite Nafion/Sulfated Zirconia Membrane for Solid Polymer Electrolyte Electrolyzer Applications. Int. J. Electrochem. Sci. 2012, 7 (2), 1532−1542. (6) Ma, L.; Sui, S.; Zhai, Y. Investigations on High Performance Proton Exchange Membrane Water Electrolyzer. Int. J. Hydrogen Energy 2009, 34 (2), 678−684. (7) Kusoglu, A.; Weber, A. Z. New Insights into Perfluorinated Sulfonic-Acid Ionomers. Chem. Rev. 2017, 117 (3), 987−1104. Q


Article

Macromolecules (27) Alam, T. M. Computational Study of Microhydration in Sulfonated Diels−Alder Poly(phenylene) Polymers. J. Phys. Chem. A 2018, 122 (15), 3927−3938. (28) Sorte, E. G.; Abbott, L. J.; Frischknecht, A. L.; Wilson, M. A.; Alam, T. M. Hydrophilic Domain Structure in Polymer Exchange Membranes: Simulations of NMR Spin Diffusion Experiments to Address Ability for Model Discrimination. J. Polym. Sci., Part B: Polym. Phys. 2018, 56, 62−78. (29) Bayramoglu, G.; Senkal, F. B.; Celik, G.; Arica, M. Y. Preparation and Characterization of Sulfonyl-Hydrazine Attached Poly(styrene-divinylbenzene) Beads for Separation of Albumin. Colloids Surf., A 2007, 294 (1−3), 56−63. (30) Rockland, L. B. Saturated Salt Solutions for Static Control of Relative Humidity between 5° and 40° C. Anal. Chem. 1960, 32 (10), 1375−1376. (31) Wiederhorn, S.; Fields, R.; Low, S.; Bahng, G.-W.; Wehrstedt, A.; Hahn, J.; Tomota, Y.; Miyata, T.; Lin, H.; Freeman, B.; Aihara, S.; Hagihara, Y.; Tagawa, T. Mechanical Properties. In Springer Handb. Mat. Measur. Met; Czichos, H., Saito, T., Smith, L., Eds.; Springer: Berlin, 2006; pp 283−397. (32) Lin, H.; Freeman, B. D. Gas Solubility, Diffusivity and Permeability in Poly(ethylene oxide). J. Membr. Sci. 2004, 239 (1), 105−117. (33) Raharjo, R. D.; Lin, H.; Sanders, D. F.; Freeman, B. D.; Kalakkunnath, S.; Kalika, D. S. Relation between Network Structure and Gas Transport in Crosslinked Poly(propylene glycol diacrylate). J. Membr. Sci. 2006, 283 (1), 253−265. (34) Wiegand, J. R.; Smith, Z. P.; Liu, Q.; Patterson, C. T.; Freeman, B. D.; Guo, R. Synthesis and Characterization of Triptycene-Based Polyimides with Tunable High Fractional Free Volume for Gas Separation Membranes. J. Mater. Chem. A 2014, 2 (33), 13309− 13320. (35) Merkel, T. C.; Gupta, R. P.; Turk, B. S.; Freeman, B. D. MixedGas Permeation of Syngas Components in Poly(Dimethylsiloxane) and Poly(1-Trimethylsilyl-1-Propyne) at Elevated Temperatures. J. Membr. Sci. 2001, 191 (1), 85−94. (36) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams-Young, D.; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; Zakrzewski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Keith, T.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian 09, Revision E.01; Gaussian, Inc.: Wallingford, CT, 2016. (37) Krishnan, R.; Binkley, J. S.; Seeger, R.; Pople, J. A. Self Consistent Molecular Orbital Methods. XX. A Basis Set for Correlated Wave Functions. J. Chem. Phys. 1980, 72 (1), 650−654. (38) McLean, A.; Chandler, G. Contracted Gaussian Basis Sets for Molecular Calculations. I. Second Row Atoms, Z = 11−18. J. Chem. Phys. 1980, 72 (10), 5639−5648. (39) Miertuš, S.; Scrocco, E.; Tomasi, J. Electrostatic Interaction of a Solute with a Continuum. A Direct Utilizaion of Ab Initio Molecular Potentials for the Prevision of Solvent Effects. Chem. Phys. 1981, 55 (1), 117−129. (40) Miertus, S.; Tomasi, J. Approximate Evaluations of the Electrostatic Free Energy and Internal Energy Changes in Solution Processes. Chem. Phys. 1982, 65 (2), 239−245. (41) Pascual ahuir, J.-L.; Silla, E.; Tunon, I. Gepol: An Improved Description of Molecular Surfaces. III. A New Algorithm for the Computation of a Solvent Excluding Surface. J. Comput. Chem. 1994, 15 (10), 1127−1138.

(42) Cooper, K. Progress toward Accurate through-Plane Membrane Resistance and Conductivity Measurement. ECS Trans. 2009, 25 (1), 995−1007. (43) Massiot, D.; Fayon, F.; Capron, M.; King, I.; Le Calvé, S.; Alonso, B.; Durand, J.-O.; Bujoli, B.; Gan, Z.; Hoatson, G. Modelling One- and Two-Dimensional Solid-State NMR Spectra. Magn. Reson. Chem. 2002, 40 (1), 70−76. (44) Callaghan, P. T. Principles of Nuclear Magnetic Resonance Microscopy; Oxford University Press on Demand: 1993. (45) Heiney, P. Datasqueeze Software. Comun. Powder Diff. Newsl 2005, 32, 9−11. (46) Waasmaier, D.; Kirfel, A. New Analytical Scattering Factor Functions for Free Atoms and Ions. Acta Crystallogr., Sect. A: Found. Crystallogr. 1995, 51 (3), 416−431. (47) Plimpton, S. Fast Parallel Algorithms for Short-Range Molecular Dynamics. J. Comput. Phys. 1995, 117 (1), 1−19. (48) Gong, C.; Pinatti, L.; Lavigne, G.; Shaw, M. T.; Scola, D. A. Thermal Stability of End-Capped and Linear Sulfonated Polyimides, Sulfonated Polystyrene, and Nafion 117. J. Appl. Polym. Sci. 2018, 135 (3), 45694. (49) Singare, P. U.; Lokhande, R. S.; Madyal, R. S. Thermal Degradation Studies of Polystyrene Sulfonic and Polyacrylic Carboxylic Cationites. Russ. J. Gen. Chem. 2010, 80 (3), 527−532. (50) Jung, H.-Y.; Kim, J. W. Role of the Glass Transition Temperature of Nafion 117 Membrane in the Preparation of the Membrane Electrode Assembly in a Direct Methanol Fuel Cell (DMFC). Int. J. Hydrogen Energy 2012, 37 (17), 12580−12585. (51) Kusoglu, A.; Dursch, T. J.; Weber, A. Z. Nanostructure/ Swelling Relationships of Bulk and Thin Film PFSA Ionomers. Adv. Funct. Mater. 2016, 26 (27), 4961−4975. (52) Kusoglu, A.; Savagatrup, S.; Clark, K. T.; Weber, A. Z. Role of Mechanical Factors in Controlling the Structure−Function Relationship of PFSA Ionomers. Macromolecules 2012, 45 (18), 7467−7476. (53) Shi, S.; Dursch, T. J.; Blake, C.; Mukundan, R.; Borup, R. L.; Weber, A. Z.; Kusoglu, A. Impact of Hygrothermal Aging on Structure/Function Relationship of Perfluorosulfonic Acid Membrane. J. Polym. Sci., Part B: Polym. Phys. 2016, 54 (5), 570−581. (54) Battino, R.; Clever, H. L. The Solubility of Gases in Liquids. Chem. Rev. 1966, 66 (4), 395−463. (55) Fogg, P. G.; Gerrard, W. Solubility of Gases in Liquids; John Wiley: 1990. (56) Ito, H.; Maeda, T.; Nakano, A.; Takenaka, H. Properties of Nafion Membranes under PEM Water Electrolysis Conditions. Int. J. Hydrogen Energy 2011, 36 (17), 10527−10540. (57) Linke, W. F. Solubilities, Inorganic and Metal Organic Compounds: A Compilation of Solubility Data from the Periodical Literature; Van Nostrand: 1965; Vol. 2. (58) Stephen, H.; Stephen, T. Solubility of Inorganic and Organic Compounds; Pergamon Press: Oxford, 1963; Vol. 1, Part 1. (59) Wiebe, R.; Gaddy, V. The Solubility of Hydrogen in Water at 0, 50, 75 and 100° from 25 to 1000 atm. J. Am. Chem. Soc. 1934, 56 (1), 76−79. (60) Yoshida, N.; Ishisaki, T.; Watakabe, A.; Yoshitake, M. Characterization of Flemion® Membranes for PEFC. Electrochim. Acta 1998, 43 (24), 3749−3754. (61) Mohamed, H. F.; Ito, K.; Kobayashi, Y.; Takimoto, N.; Takeoka, Y.; Ohira, A. Free Volume and Permeabilities of O2 and H2 in Nafion Membranes for Polymer Electrolyte Fuel Cells. Polymer 2008, 49 (13−14), 3091−3097. (62) Kocha, S. S.; Deliang Yang, J.; Yi, J. S. Characterization of Gas Crossover and Its Implications in PEM Fuel Cells. AIChE J. 2006, 52 (5), 1916−1925. (63) Takata, H.; Nishikawa, M.; Arimura, Y.; Egawa, T.; Fukada, S.; Yoshitake, M. Study on Water Uptake of Proton Exchange Membrane by Using Tritiated Water Sorption Method. Int. J. Hydrogen Energy 2005, 30 (9), 1017−1025. (64) Broka, K.; Ekdunge, P. Oxygen and Hydrogen Permeation Properties and Water Uptake of Nafion® 117 Membrane and Recast Film for PEM Fuel Cell. J. Appl. Electrochem. 1997, 27 (2), 117−123. R


Article

Macromolecules (65) Novitski, D.; Holdcroft, S. Determination of O2 Mass Transport at the Pt | PFSA Ionomer Interface under Reduced Relative Humidity. ACS Appl. Mater. Interfaces 2015, 7 (49), 27314− 27323. (66) Schalenbach, M.; Hoefner, T.; Paciok, P.; Carmo, M.; Lueke, W.; Stolten, D. Gas Permeation through Nafion. Part 1: Measurements. J. Phys. Chem. C 2015, 119 (45), 25145−25155. (67) Naudy, S.; Collette, F.; Thominette, F.; Gebel, G.; Espuche, E. Influence of Hygrothermal Aging on the Gas and Water Transport Properties of Nafion® Membranes. J. Membr. Sci. 2014, 451, 293− 304. (68) Chang, Y.; Brunello, G. F.; Fuller, J.; Disabb-Miller, M. L.; Hawley, M. E.; Kim, Y. S.; Hickner, M. A.; Jang, S. S.; Bae, C. Polymer Electrolyte Membranes Based on Poly(arylene ether sulfone) with Pendant Perfluorosulfonic Acid. Polym. Chem. 2013, 4 (2), 272−281. (69) Lafitte, B.; Jannasch, P. Proton Conducting Aromatic Polymers Carrying Hypersulfonated Side Chains for Fuel Cell Applications. Adv. Funct. Mater. 2007, 17 (15), 2823−2834. (70) Weiber, E. A.; Takamuku, S.; Jannasch, P. Highly Proton Conducting Electrolyte Membranes Based on Poly(arylene sulfone)s with Tetrasulfonated Segments. Macromolecules 2013, 46 (9), 3476− 3485. (71) Chang, Y.; Mohanty, A. D.; Smedley, S. B.; Abu-Hakmeh, K.; Lee, Y. H.; Morgan, J. E.; Hickner, M. A.; Jang, S. S.; Ryu, C. Y.; Bae, C. Effect of Superacidic Side Chain Structures on High Conductivity Aromatic Polymer Fuel Cell Membranes. Macromolecules 2015, 48 (19), 7117−7126. (72) Kuo, A.-T.; Shinoda, W.; Okazaki, S. Molecular Dynamics Study of the Morphology of Hydrated Perfluorosulfonic Acid Polymer Membranes. J. Phys. Chem. C 2016, 120 (45), 25832−25842. (73) Clauss, J.; Schmidt Rohr, K.; Spiess, H. W. Determination of Domain Sizes in Heterogeneous Polymers by Solid State NMR. Acta Polym. 1993, 44 (1), 1−17. (74) Kreuer, K. D.; Portale, G. A Critical Revision of the Nano Morphology of Proton Conducting Ionomers and Polyelectrolytes for Fuel Cell Applications. Adv. Funct. Mater. 2013, 23 (43), 5390−5397. (75) Feng, S.; Voth, G. A. Proton Solvation and Transport in Hydrated Nafion. J. Phys. Chem. B 2011, 115 (19), 5903−5912. (76) Knight, C.; Voth, G. A. The Curious Case of the Hydrated Proton. Acc. Chem. Res. 2012, 45 (1), 101−109. (77) Kreuer, K. D. Proton Conduction in Fuel Cells. HydrogenTransfer React. 2006, 709−736. (78) Harris, T.; Zhao, Q.; Mildvan, A. NMR Studies of Strong Hydrogen Bonds in Enzymes and in a Model Compound. J. Mol. Struct. 2000, 552 (1−3), 97−109. (79) Jeffrey, G.; Yeon, Y. The Correlation between Hydrogen-Bond Lengths and Proton Chemical Shifts in Crystals. Acta Crystallogr., Sect. B: Struct. Sci. 1986, 42 (4), 410−413. (80) Sternberg, U.; Brunner, E. The Influence of Short-Range Geometry on the Chemical Shift of Protons in Hydrogen Bonds. J. Magn. Reson., Ser. A 1994, 108 (2), 142−150. (81) Tolstoy, P. M.; Schah-Mohammedi, P.; Smirnov, S. N.; Golubev, N. S.; Denisov, G. S.; Limbach, H.-H. Characterization of Fluxional Hydrogen-Bonded Complexes of Acetic Acid and Acetate by NMR: Geometries and Isotope and Solvent Effects. J. Am. Chem. Soc. 2004, 126 (17), 5621−5634. (82) Limbach, H. H.; Tolstoy, P. M.; Pérez Hernández, N.; Guo, J.; Shenderovich, I. G.; Denisov, G. S. OHO Hydrogen Bond Geometries and NMR Chemical Shifts: From Equilibrium Structures to Geometric H/D Isotope Effects, with Applications for Water, Protonated Water, and Compressed Ice. Isr. J. Chem. 2009, 49 (2), 199−216. (83) Petersen, M. K.; Voth, G. A. Characterization of the Solvation and Transport of the Hydrated Proton in the Perfluorosulfonic Acid Membrane Nafion. J. Phys. Chem. B 2006, 110 (37), 18594−18600. (84) Savage, J.; Tse, Y.-L. S.; Voth, G. A. Proton Transport Mechanism of Perfluorosulfonic Acid Membranes. J. Phys. Chem. C 2014, 118 (31), 17436−17445.

(85) Raamat, E.; Kaupmees, K.; Ovsjannikov, G.; Trummal, A.; Kütt, A.; Saame, J.; Koppel, I.; Kaljurand, I.; Lipping, L.; Rodima, T.; et al. Acidities of Strong Neutral Brønsted Acids in Different Media. J. Phys. Org. Chem. 2013, 26 (2), 162−170. (86) Furukawa, N.; Fujihara, H. Acidity, Hydrogen Bonding and Metal Complexation of Sulfonic Acids and Derivatives. Chem. Sulphonic Acids, Esters Their Deriv. 1991, 261−281. (87) Dippel, T.; Kreuer, K. Proton Transport Mechanism in Concentrated Aqueous Solutions and Solid Hydrates of Acids. Solid State Ionics 1991, 46 (1−2), 3−9. (88) Choe, Y.-K.; Tsuchida, E.; Ikeshoji, T.; Ohira, A.; Kidena, K. An Ab Initio Modeling Study on a Modeled Hydrated Polymer Electrolyte Membrane, Sulfonated Polyethersulfone (SPES). J. Phys. Chem. B 2010, 114 (7), 2411−2421. (89) Wang, C.; Paddison, S. J. Hydration and Proton Transfer in Highly Sulfonated Poly(phenylene sulfone) Ionomers: An Ab Initio Study. J. Phys. Chem. A 2013, 117 (3), 650−660. (90) Zawodzinski, T. A., Jr.; Neeman, M.; Sillerud, L. O.; Gottesfeld, S. Determination of Water Diffusion Coefficients in Perfluorosulfonate Ionomeric Membranes. J. Phys. Chem. 1991, 95 (15), 6040− 6044. (91) Kreuer, K. D. On the Development of Proton Conducting Materials for Technological Applications. Solid State Ionics 1997, 97 (1), 1−15. (92) Agmon, N. The Grotthuss Mechanism. Chem. Phys. Lett. 1995, 244 (5−6), 456−462. (93) Kreuer, K.-D.; Dippel, T.; Meyer, W.; Maier, J. Nafion® Membranes: Molecular Diffusion, Proton Conductivity and Proton Conduction Mechanism. MRS Online Proc. Libr. 1992, DOI: 10.1557/ PROC-293-273. (94) Kreuer, K. On the Development of Proton Conducting Polymer Membranes for Hydrogen and Methanol Fuel Cells. J. Membr. Sci. 2001, 185 (1), 29−39. (95) Park, J. K.; Li, J.; Divoux, G. M.; Madsen, L. A.; Moore, R. B. Oriented Morphology and Anisotropic Transport in Uniaxially Stretched Perfluorosulfonate Ionomer Membranes. Macromolecules 2011, 44 (14), 5701−5710. (96) Edmondson, C.; Fontanella, J. Free Volume and Percolation in S-SEBS and Fluorocarbon Proton Conducting Membranes. Solid State Ionics 2002, 152-153, 355−361. (97) Ochi, S.; Kamishima, O.; Mizusaki, J.; Kawamura, J. Investigation of Proton Diffusion in Nafion® 117 Membrane by Electrical Conductivity and NMR. Solid State Ionics 2009, 180 (6−8), 580−584. (98) Kidena, K.; Ohkubo, T.; Takimoto, N.; Ohira, A. PFG-NMR Approach to Determining the Water Transport Mechanism in Polymer Electrolyte Membranes Conditioned at Different Temperatures. Eur. Polym. J. 2010, 46 (3), 450−455. (99) Zawodzinski, T. A., Jr.; Springer, T. E.; Uribe, F.; Gottesfeld, S. Characterization of Polymer Electrolytes for Fuel Cell Applications. Solid State Ionics 1993, 60 (1−3), 199−211. (100) Chen, C.; Tse, Y.-L. S.; Lindberg, G. E.; Knight, C.; Voth, G. A. Hydroxide Solvation and Transport in Anion Exchange Membranes. J. Am. Chem. Soc. 2016, 138 (3), 991−1000. (101) Sone, Y.; Ekdunge, P.; Simonsson, D. Proton Conductivity of Nafion 117 as Measured by a Four Electrode AC Impedance Method. J. Electrochem. Soc. 1996, 143 (4), 1254−1259. (102) Halim, J.; Büchi, F.; Haas, O.; Stamm, M.; Scherer, G. Characterization of Perfluorosulfonic Acid Membranes by Conductivity Measurements and Small-Angle X-ray Scattering. Electrochim. Acta 1994, 39 (8−9), 1303−1307. (103) Uosaki, K.; Okazaki, K.; Kita, H. Conductivity of Nation Membranes at Low Temperatures. J. Electroanal. Chem. Interfacial Electrochem. 1990, 287 (1), 163−169. (104) Di Vona, M.; Marani, D.; D’Epifanio, A.; Licoccia, S.; Beurroies, I.; Denoyel, R.; Knauth, P. Hybrid Materials for Polymer Electrolyte Membrane Fuel Cells: Water Uptake, Mechanical and Transport Properties. J. Membr. Sci. 2007, 304 (1−2), 76−81. S


Article

Macromolecules (105) Grayson, M. A.; Wolf, C. J. The Solubility and Diffusion of Water in Poly(aryl ether ether ketone) (PEEK). J. Polym. Sci., Part B: Polym. Phys. 1987, 25 (1), 31−41. (106) Colomban, P. Proton Conductors: Solids, Membranes and GelsMaterials and Devices; Cambridge University Press: 1992; Vol. 2.

T


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