Gas separation of 6FDA–6FpDA membranes

Gas separation of 6FDA–6FpDA membranes

Journal of Membrane Science 293 (2007) 22–28 Gas separation of 6FDA–6FpDA membranes Effect of the solvent on polymer surfaces and permselectivity ´ R...

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Journal of Membrane Science 293 (2007) 22–28

Gas separation of 6FDA–6FpDA membranes Effect of the solvent on polymer surfaces and permselectivity ´ Roberto Recio a , Laura Palacio a , Pedro Pr´adanos a , Antonio Hern´andez a,∗ , Angel E. Lozano b , ´ Angel Marcos b , Jos´e G. de la Campa b , Javier de Abajo b b

a Dpto. F´ısica Aplicada, Universidad de Valladolid, Facultad de Ciencias, Real de Burgos s/n, 47071 Valladolid, Spain Dpto. Qu´ımica Macromolecular, Instituto de Ciencia y Tecnolog´ıa de Pol´ımeros, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain

Received 26 July 2006; received in revised form 16 January 2007; accepted 20 January 2007 Available online 24 January 2007

Abstract The aim of this work has been to analyze how different solvents used in the manufacture of gas separation membranes, based on 6FDA–6FpDA, influence permeability and selectivity. It has been shown that a low boiling point and/or a repulsive interaction between the solvent and the polymer increase both selectivity and permeability for O2 /N2 and, specially, for CO2 /CH4 gas pairs. These results have been explained in terms of fractional free volume and intersegmental mobility. In particular it has been shown that good solubility of the polymer results in a high glass transition temperature and planar surface as characterised by the fractal dimension of the resulting membranes, obtained from AFM analysis. © 2007 Elsevier B.V. All rights reserved. Keywords: Fluorinated polyimides; Gas separation; Fractional free volume; Fractal dimension; Solubility parameter

1. Introduction Polymeric membranes can compete with other more traditional processes of gas separation as cryogenic distillation or pressure swing adsorption, mainly due to their simplicity, continuous working ability, low energy consumption and capital costs [1]. A high selectivity leads to a high purity of products and allows a reduction in the number of operation steps. A high permeability involves a high process velocity and a lower membrane area. Nevertheless, high selectivity is normally obtained with low permeability and vice versa [2]. Of course, it should be convenient to reach simultaneously high permeabilities and selectivities or at least to increase one of these parameters without decreasing the other. The main physicochemical characteristics that rule gas permeability of polymers are: • The mobility of the polymer chains that can be correlated with the glass transition temperature, Tg . ∗

Corresponding author. Tel.: +34 983 423134; fax: +34 983 423136. E-mail address: [email protected] (A. Hern´andez).

0376-7388/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2007.01.022

• The intersegmental spacing and the corresponding polymer free volume. • The interaction between the polymer and the penetrant gas that is correlated with the gas solubility [3]. It seems clear that there is a direct correlation between gas diffusivity in the polymer and its free volume [4]. Because of that, both selectivity and permeability characteristics can be interpreted in terms of a series of parameters that are substantially determined by the free volume of the polymer [5]. It has been shown that the introduction of bulky groups in the chains of glassy polymers makes their structure stiffer and hinders an efficient packing of chains [6,7]. This should lead to an increase in free volume. An example of such a kind of polymer is 6FDA–6FpDA [8]. Fluorinated polyimides are particularly interesting for gas separation because they have good mechanical, thermal and transport properties [9]. They have also an acceptable resistance to plasticization [10]. In most cases, it has been assumed that the solvent used in the casting does not influence the resulting structure of the membrane once it has been evacuated. Nevertheless, some studies have been done on this dependency [11,12], without conclusive explanation of the differences in permeation found.

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Table 1 Average thickness for the membranes manufactured x, μ ± ␴ (␮m) DCM THF DMAc DMF Ac

Fig. 1. Structure of 6FDA–6FpDA.

59.8 45.1 50.5 29.0 68.6

± ± ± ± ±

16.1 5.7 19.2 7.7 19.3

μ is the average thickness for many samples made with the same solvent while σ is the corresponding standard deviation.

In this work, differences in selectivity and permeability have been detected on 6FDA–6FpDA membranes, depending on the solvent used in their manufacture, and have been analyzed in some detail. Moreover, the morphology of the membrane, both on the surface and in the bulk, along with permeability and selectivity, could be correlated with the solvent characteristics. This has been done here through the fractional free volume and glass transition temperature but also by an analysis of fractal dimension as detected by studying roughness by atomic force microscopy (AFM).

the “time lag” method, at 30 ◦ C and 1 bar. The amount of gas that crosses the membrane at time t was calculated from the permeate pressure readings in the low-pressure side. The inherent leak rate in the downstream side, determined after evacuating the system, was measured for each experimental run. The permeability constant was obtained directly from the flow rate into the downstream volume upon reaching the steady state [14]. These experimental permeabilities are shown in Table 2.

2. Experimental

2.3. Wide angle X-ray diffractometry

2.1. Membrane materials

Wide-angle X-ray diffraction (WAXD) patterns of the films were obtained in a Philips PW 1130 diffractometer (Cu K␣ radiation), at a scan rate of 2◦ min−1 over the 5–40◦ 2θ range. The corresponding d-spacing values, which provide a measure of intersegmental distances between polymer backbones, were calculated from the diffraction peak maximum through the Bragg equation:

Several membranes were prepared from the 6FDA–6FpDA polyimide (Fig. 1). This polyimide was synthesized using the classical two-steps method from 6FpDA diamine and 6FDA dianhydride [8,13]. Dichloromethane (DCM), tetrahydrofuran (THF), N,Ndimethylacetamide (DMAc), N,N-dimethylformamide (DMF) and acetone (Ac), were used to prepare 6FDA–6FpDA solutions with a 7.5% (w/v) polymer concentration. These solutions were cast on glass plates, and solvent was removed at 25 ◦ C for DCM, Ac and THF, and at 70 ◦ C for DMAc and DMF. After peeling off the membranes from the glass, they were heated at 180 ◦ C under vacuum of 10−2 mbar for 2 days. The resulting thickness has been measured on several samples for the membranes manufactured with all the solvents used and are shown in Table 1. Then the membranes were placed in the holder and subjected to a high vacuum (by the two pumps in series; a rotary and a turbo-molecular one) overnight until arriving to 10−9 mbar and then tested as gas separation membranes. 2.2. Permeability Gas permeability measurements for O2 , N2 , CO2 and CH4 have been performed with a barometric gas permeator based on

d=

λ 2 sin θ

(1)

where λ is the wavelength of the radiation and 2θ is the angle of maximum intensity in the amorphous halo exhibited by the polymer. 2.4. Atomic force microscopy Atomic Force Microscopy, AFM, is a technique allowing to get a tri-dimensional image of a surface by taking profit of the force between a sharp tip and the surface itself. A cantilever, where the tip is placed, deflects proportionally to the interaction force. If the surface is scanned this allows getting a tri-dimensional map. Depending on the operation mode the deflection (contact and non-contact modes) or the changes in the natural oscillation frequency of the cantilever (intermittent contact or tapping mode) are imaged. The last method has high sensibility without damaging the samples [15].

Table 2 Permeabilities and selectivities for the 6FDA–6FpDA manufactured with different solvents Solvent

P-O2 (Barrer)

P-N2 (Barrer)

P-CO2 (Barrer)

P-CH4 (Barrer)

α (O2 /N2 )

α (CO2 /CH4 )

DCM THF DMAc DMF Ac

17.79 15.76 14.61 14.80 15.54

3.68 3.24 3.03 2.98 3.24

81.4 76.5 68.4 66.8 72.1

1.71 1.67 1.61 1.59 1.62

4.84 4.87 4.82 4.96 4.79

47.7 45.8 42.6 42.0 44.6

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Here, AFM, was performed in the TappingMode® at room temperature with a Nanoscope IIIA from Digital Instruments® , on pieces of the same films used for the permeability tests. A silicon etched tip with a curvature radius below 5 nm mounted on a single cantilever of a length of 125 ␮m, with a vibration resonance frequency of 350 kHz, was used to carry out the AFM experiments. The AFM images have all XYZ information. Consequently it is an easy task to evaluate roughness that can be quantitatively defined though the mean roughness (Ra ) or the average roughness (Rq ). The root square mean, Rq , is found in common literature and will also be used here. NanoScope (v5.12 rev. B) software was used for recording and analyzing the AFM topographic images. Average roughness (Rq ) was determined for different explored areas using the definition expressed by the following equation:   n 1 Rq =  (Zi − Zm )2 (2) n

Fig. 2. Selectivity vs. permeability with Robeson trade off curve for O2 /N2 for the different solvents used.

i=0

where Zm is the mean value of the tip height in each point of the image (Zi ) over a reference baseline (Z) [16]. 2.5. Thermal characterization Differential scanning calorimetry (DSC) was performed in a Perkin-Elmer DSC-7 instrument. All runs were taken in perforated pans under N2 purge at a scanning rate of 10 ◦ C/min. The glass transitions temperatures (Tg ) have been obtained as the midpoint of the change in the heat capacity, Cp /2, as calculated by the software. Thermogravimetric analysis, TGA, was done on a TA Q-500 analyzer under nitrogen atmosphere, using 5 mg samples. The TA HiRes dynamic method was used, so that by this software the heating rate is adjusted in response to changes in the ratio of weight loss, which resulted in improved resolution.

Fig. 3. Selectivity vs. permeability with Robeson trade off curve for CO2 /CH4 for the different solvents used.

where the diffusivity is also obtained from the time lag method, from the time-lag parameter as: t0 =

3. Results and discussion

(x)2 6D

(4)

The so obtained solubilities are shown in Fig. 4. There it can be seen that solubility does not depend on the solvent used to

3.1. Permeability The obtained permeabilities and selectivities for the gas pairs O2 /N2 and CO2 /CH4 are shown in Figs. 2 and 3, for all the solvents. In all cases the corresponding Robeson [2], trade-off bound is shown along with the corresponding zone of commercial interest [17]. For O2 /N2 it is clear that the increases in permeability bring about a reduction in selectivity in such a way that the distance from the points to the Robeson line remains constant. This is not the case for CO2 /CH4 (see Fig. 3) as far as; in this case, some points present simultaneously higher permeability and selectivity and consequently show better gas separation properties. It is important to take into account that solubility can be evaluated as: S=

P D

(3)

Fig. 4. Evaluated solubility as a function of the difference between the boiling and the cast temperature, T.

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with different solvents are randomly distributed around an average value of 1.462 g/cm3 – very close to the value given in literature for 6FDA–6FpDA; 1.466 g/cm3 – with deviations below the 0.005 g/cm3 error inherent to the technique. This prevents a direct use of Eq. (5) to evaluate FFV. Since, all of the 6FDA–6FpDA membranes studied exhibit substantially equal solubility coefficients, permeability can be directly related to free volume using the following equation: Pg = −Ag e−Bg /FFV

Fig. 5. TGA traces for the different membranes studied after vacuum and temperature conditioning.

manufacture the membrane. Moreover, then it is clear that all detected changes in permeability are due to diffusive transport. Joly et al. [18], attributed the changes in permeability, when different solvents are used, to the presence of residual solvent after evaporation. Nevertheless, they assure that there are virtually no solvent residues after 90 min of treatment at 200 ◦ C. Herein, we have used a thermal treatment of 180 ◦ C for more than 3000 min (approx. 2 days). In our case, the maximal dispersion of the traces corresponds to a 0.2% in mass at 200 ◦ C as shown in Fig. 5, which is lower that the weight loss assumed as negligible by Joly et al. [18]. Moreover there is no correlation of the weight loss with the boiling point that should exist if solvent residues were significantly present. In fact, the thermo-gravimetric traces coincide within the error range for all the membranes after the thermal and vacuum conditioning pre-treatment, what supports the irrelevance, in our case, of any solvent residue. 3.2. Free volume There are two main methods to obtain the fractional free volume FFV: either polymer density and group contribution theory, or positron annihilation lifetime spectroscopy (PALS) [19]. Only PALS actually measures FFV while the other method is in fact an estimation based on: FFV =

V − V0 V

(6)

With Ag and Bg being constants that depend on the gas. Lin et al. [5], have given values for these constants obtained from gas permeability measurements. For CO2 they propose ACO2 = (360 ± 70) × 103 Barrers and BCO2 = 0.95 ± 0.02 and for CH4 ACH4 = (27 ± 5) × 103 Barrers and BCH4 = 0.99 ± 0.01. Using these values of Ag and Bg and the measured permeabilities for CO2 and CH4 in Eq. (6), it is possible to calculate FFV of the different membranes as a function of the conditions of preparation. These values are in very good accordance with those obtained by Wang et al. [21], from molecular dynamics simulations, FFVS = 0.110. In Fig. 6, the calculated FFV values are plotted as a function of the differences of the boiling and the membrane cast temperature, T. It is clear that when a membrane is cast at a temperature far below the boiling point of the solvent, needs a longer time to eliminate it allowing the polymer chains to relax and to attain a state of lower fractional free volume. This trend is clearly shown in Fig. 6. On the other hand, given that the penetrant kinetic diameter [22], of CO2 is lower than that of CH4 it is clear that CO2 should be able to occupy a higher fraction of free volume as it is also seen in Fig. 6. It is worth to note that if the FFV values shown in Fig. 6 are assumed, the corresponding change in the membrane density should be not higher than 0.004 g/cm3 . This confirms that the changes in FFV due to the different solvents used would be undetectable. This is even more evident if we take into account that the changes in FFV affecting permeabilities should happen mainly in a certain limited zone below the evaporation surface.

(5)

where V is the specific volume of the amorphous polymer at the temperature of interest and V0 is the specific volume at 0 K, which is estimated as 1.3 times the Van der Waals volume that can be evaluated by using the Bondi’s group contribution method [20]. For 6FDA–6FpDA this method gives a value of FFVB = 0.190 [21]. The average density of the 6FDA–6FpDA membranes was also determined by using the method of flotation in a water solution of calcium nitrate at 25 ± 0.1 ◦ C whose density is afterwards measured by pycnometry. The corresponding error range resulted to be 0.005 g/cm3 without a consideration of systematic error due to bubbles and water adsorption. The so obtained values for the density of membranes manufactured

Fig. 6. Fractional free volume vs. T. The values evaluated from both CO2 and CH4 gases are shown.

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Fig. 7. Distance below (negative) or above (positive) the Robeson curve vs. T. Both O2 /N2 and CO2 /CH4 gas pairs are shown.

Given that the FFV obtained from CO2 permeabilities approach better FFVS and that the tendencies are very similar for data evaluated from permeabilities of other gases, here on FFV will be given as evaluated from measured permeabilities for CO2 . Of course this is an arbitrary election because both the FFV refer to different concepts of free volume; being FFVS an estimation of the geometrically defined total volume left by the polymer chains while the FFV obtained from permeability results refer to the volume actually accessible for each penetrant. In order to study in a more quantitative way how a change in the solvent can increase permeability and selectivity, we can define the distance from the point in a selectivity versus permeability plot to the Robeson trade-off line, ΔR (ΔR < 0 if the point is below the Robeson bound and ΔR > 0 if the point is above it). This distance can be plotted versus T as shown in Fig. 7. In this plot, it can be seen that permeability versus selectivity relation is improved when the boiling temperature decreases; i.e. when it is closer to the membrane preparation temperature. This, attending to Fig. 6, can be explained in terms of the speed of evacuation of the solvent that should increase for lower boiling temperatures thus leaving higher free volume fractions due to the incomplete relaxation of the polymer structure.

In our case we deal with fractal interfaces, consequently their fractal dimension will be between 2 and 3. The resulting fractal dimension will be close to 2 if the interface was perfectly alike to an Euclidean surface; close to 3 if it the interface filled a volume. The roughness versus scanned area pattern is characteristic of a given material and preparation, and defines the fractal dimension, dfr , which is evaluated as: dfr = 3 − α, where α is the so-called roughness exponent that can be calculated as the slope of roughness versus scan size in a double log plot [23]. This fractal dimension experimentally represents well how roughness increases with scan size with accurate fittings to experimental data [24]. Some preliminary results on the fractal dimension of these membranes without further correlation have already been published by us [25]. The quality of a solvent–polymer system can be correlated with their Hildebrand solubility parameters in such a way that when these parameters are similar |δs − δp | ≤ 2.5 (cal/cm3 )1/2 the solubility is acceptable. The above criterion comes from the approximate Flory–Huggins that can be improved to incorporate new terms. In this way, the Prigogine–Flory–Patterson theory introduces an entropic contribution due to free volume effects in order to obtain more realistic results [26], without substantial changes in the criterion stated. In Fig. 8, the fractal dimension is plotted versus δs for the solvents used as obtained in literature [27]. A parabolic plot should be obtained in this kind of plots [28], with a minimum in fractal dimension (flat membrane surface). Here, this minimum appears at 10.2 (cal/cm3 )1/2 when 6FDA–6FpDA dissolves better. The minimum in fractal dimension is mainly due to the polar contribution of the solubility Hildebrand parameter, as can be proved by the reproducibility of the minimum when the polar solubility parameter of Hansen is used, while no correlation between fractal dimension and the dispersive or hydrogen bond Hansen parameters can be found [29]. 3.5. Glass transition temperature An idea of the mobility of the polymer chain is given by the glass transition temperature. In Fig. 9, the Tg of the different

3.3. Intersegmental distances Very similar values for d-spacing were obtained for all the membranes cast from different solvents with an average distance ˚ which is a very similar value to that reported by of 5.8 ± 0.2 A, ˚ Wang et al. for polymer 6FDA–6FpDA [21], of 5.9 A. Similar intersegmental distance as obtained in this work for membranes cast from different solvents is compatible with the existence of different chain segments mobilities and also for different free volume fractions. 3.4. Fractal dimension Fractals are at the frontier between Euclidean geometry and random disorder as far as they show a certain self-similarity but not so complete as Euclidean objects. This is why fractals are objects which dimension is not an integer but fractional.

Fig. 8. Fractal dimension vs. the Hildebrand solubility parameter for all the solvents used.

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fluorine, chlorine, or bromine [32]. Therefore, the value of δp obtained from Figs. 8 and 9 is very similar to that determined by other methods and could be considered as a good value for δp . In Fig. 10, the distance to the Robeson bound is plotted versus δs − δp , considering δp  10.3 (cal/cm3 )1/2 . It is experimentally observed that the best selectivity–permeability balance is obtained for solvents that show negative δs − δp values, although the best polymer–solvent solubility is expected when δs − δp is 0. These negative values for δs − δp seem to correspond to a certain repulsive interaction between the solvent and the polymer chain. For zero values of δs − δp , the polymer chains should be more extended, what would lead to higher glass transition temperatures and plausibly to more planar surfaces. 4. Conclusions Fig. 9. Glass transition temperature vs. the Hildebrand solubility parameter for all the solvents used.

membranes is given as a function of the solvent solubility parameter, δs . In this case, there is also an approximately parabolic plot with a maximum centred around 10.3 (cal/cm3 )1/2 . 3.6. Calculated solubility parameter According to the results shown in Figs. 8 and 9, the Hildebrand solubility parameter of 6FDA–6FpDA should be δp  10.3 (cal/cm3 )1/2 . The molecular simulation of 6FDA–6FpDA using the module Shyntia, included in the Materials Studio package [30], gave us a value of 10.78 (cal/cm3 )1/2 whilst Chung and Kafchinsky obtained a value of 11.8 (cal/cm3 )1/2 [31], from cohesive energy tables. Synthia can predict a wide range of thermodynamic, mechanical, and transport properties for bulk amorphous homopolymers and statistical copolymers. The key advantage of Synthia is that it uses connectivity indices as opposed to group contributions in its correlations; this means that no database of group contributions is required, and properties may be predicted for any polymer comprised of any of the following nine elements: carbon, hydrogen, nitrogen, oxygen, silicon, sulfur,

Fig. 10. Distance below (negative) or above (positive) the Robeson bound vs. the differences in solubility parameter of the solvent and the polymer.

A set of membranes from 6FDA–6FpDA, cast from different solvents, has been manufactured and their gas permeability properties have been tested. A change of the solvent allows an advance above the Robeson’s upper bound (better membrane productivity) for the CO2 /CH4 gas pair while only a marginal improvement is obtained for O2 /N2 . In both cases, there is an improvement in the selectivity–permeability balance when the boiling temperature of the solvent comes close to the temperature of membrane preparation. Once assumed that in our experimental conditions there is not any important effect of solvent trapping, this result seems to denote that a faster evacuation of the solvent gives better values of permeability and selectivity, probably because a fast evaporation does not allow the polymer to relax and it remains in a meta-stable structure with higher FFV. In fact, FFV has been shown to decrease when the difference between the solvent boiling temperature and the membrane cast temperature, T, increases, approaching to the value obtained by Wang from molecular dynamics simulations for 6FDA–6FpDA [21]. On the other hand, it has been obtained experimentally in this work that the use of a better solvent for making the membrane, gives a higher glass transition temperature and also a lower fractal dimension. This fact is probably due to the low mobility of the chain segments of the polymer linked to their more extended disposition. Also, the membranes cast from THF, Ac and DCM, solvents with the lower δs − δp value for 6FDA–6FpDA, gave the better selectivity versus permeability characteristics probably due to a higher fractional free volume. In conclusion it seems that, in the case of 6FDA–6FpDA, there are two concomitant factors that give better selectivity– permeability balance by hindering the relaxation of the chains and consequently increasing the fractional free volume: (a) the faster evaporation of the solvent and (b) the lower difference between solvent and polymer, δs − δp , solubility parameters. The special relevance of these changes in fractional free volume on the permeability of CO2 is probably due to its particularly high solubility. By increasing the fractional free volume, the increment in the adsorption surface inside the polymer increases the solubility of condensable gases. According to the mechanisms proposed here, polymers with lower chain mobility should lead to higher fractional free

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