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Facile approach to polymer–inorganic nanocomposite membrane through a biomineralization-inspired process
Journal of Membrane Science 357 (2010) 171–177
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Journal of Membrane Science journal homepage: www.elsevier.com/locate/memsci
Facile approach to polymer–inorganic nanocomposite membrane through a biomineralization-inspired process Fusheng Pan, Qinglai Cheng, Huiping Jia, Zhongyi Jiang ∗ Key Laboratory for Green Technology, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
a r t i c l e
i n f o
Article history: Received 22 February 2010 Received in revised form 6 April 2010 Accepted 11 April 2010 Available online 24 April 2010 Keywords: Nanocomposite membrane Gelatin Biomineralization Silica Gas dehumidification
a b s t r a c t A novel and facile biomineralization-inspired approach to fabricating the polymer–inorganic nanocomposite membrane was proposed utilizing manifold functions of polymer: forming the ultrathin membrane scaffold, inducing (templating and catalyzing) the in situ generation of inorganic nanoparticles, confining and suppressing the aggregation of inorganic particles. More specifically, ultrathin gelatin–silica nanocomposite membranes (0.4–0.6 m) with homogeneously dispersed silica nanoparticles (40–80 nm) were fabricated onto a porous substrate mildly and rapidly. The morphology and the size of the silica nanoparticles can be conveniently tuned by simply varying the fabrication conditions such as concentration of the silica precursor, pH value of the membrane casting solution. The as-prepared membranes displayed well-defined free volume characteristics, and superior dehumidification performance. The dehumidification experiments using 0.3 wt.% water vapor/propylene mixture gas as model showed that water permeance was 1.87 × 10−8 m3 (STP)/(m2 s Pa) and separation factor was infinite for the composite membranes fabricated at the sodium silicate concentration 30 mM and the pH 7.0. © 2010 Elsevier B.V. All rights reserved.
1. Introduction Polymer–inorganic nanocomposite membranes where inorganic nanoparticles are dispersed inside polymer membrane matrix have been of great interest in recent years due to their intrinsic advantages over pure polymeric or inorganic membranes as well as their immense application potential in energy, environment, biomedical materials and devices [1–4]. In most cases, the presence of nanoparticles will significantly increase mechanical, thermal, chemical stability and working performance of the nanocomposite membranes [5–8]. Until now, the most common methods for fabricating nanocomposite membranes encompass physical blending, in situ polymerization (simultaneous polymerization, consecutive polymerization and twin polymerization). (1) Physical blending. Inorganic nanoparticles are added into the organic monomers, oligomers or polymers solution under mechanical stirring and/or ultrasonic treatment. The nanocomposite membranes are obtained after the solvent evaporation or polymerization [9]. In some cases, functional groups such as hydroxyl, carboxyl are usually existed on the surface of inorganic particles, which can generate initiating radicals, cations or anions to initiate the polymerization of the monomers on their surface [10]. Although this method is facile and generic, and in particular the proportion of the polymer moiety and inorganic moiety
∗ Corresponding author. Tel.: +86 22 23500086; fax: +86 22 23500086. E-mail address: [email protected] (Z. Jiang). 0376-7388/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2010.04.017
are easy to control, it severely suffers from the liable aggregation of inorganic nanoparticles [11,12]. (2) In situ polymerization. Organic monomers, oligomers or polymers and inorganic precursors are mixed together in aqueous/organic solution or water–oil emulsion [13,14]. Through hydrolysis and condensation of the inorganic precursors, nanoparticles are in situ generated and homogeneously dispersed in polymer matrix. The advantage of this method is manifold: the reaction conditions usually take place at room temperature and ambient pressure, and the concentrations of organic and inorganic components can be conveniently altered in solution or emulsion. Additionally, the organic and inorganic moieties are mixed at the molecular level within the membranes. However, the involvement of acid or base catalyst incurs the considerable difficulty in controlling the reaction rate and the morphologies of the inorganic particles. Furthermore, the harsh microenvironment limits its wide applicability to some extent. If we take a look at nature-existing biomaterials, we will discover with ease that biomineralization, the process by which living organisms produce minerals, can achieve this goal in a surprisingly facile way. Since 1990s, many biomineralization-inspired processes were developed to prepare the inorganic nanoparticles with controllable morphology in vitro by the induction of natural and synthesized polymers [15–18]. It is envisaged by us that if these natural or synthetic biomineral inducers can be directly employed as bulk membrane materials, the hierarchically structure polymer–inorganic nanocomposite membranes will be formed through the simultaneous crosslinking and biomineralization or biomimetic mineralization process. More explicitly, the polymer
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exerts the following multiple functions: forming the ultrathin membrane scaffold, inducing (templating and catalyzing) the in situ generation of inorganic nanoparticles, confining and suppressing the aggregation of inorganic particles. Such bioinspired approach will manifest several distinct advantages: (1) Rapid. The process can be accomplished even within seconds. (2) Polymorphous. Morphology of the inorganic particles can be tailored by varying the deposition conditions. It is also intuitive that small building blocks can be further organized into complex forms [19,20]. (3) Mild. Formation of the inorganic particles occurs at ambient temperature and neutral pH. (4) Inexpensive. Both polymer and inorganic precursor can be available at rather low cost. (5) Green. All the relevant materials and steps are environmentally benign. To the best of our knowledge, quite rare if not none of such reports have been found in the existing literatures. For the one-step fabrication of the polymer–inorganic nanocomposite membranes, the exquisite match of polymers and inorganic precursors are of paramount significance to acquire the synchronized mineralization rates of inorganic precursor and crosslinking/curing rate of the polymeric materials. Take the case of biosilification, lysozyme (pI 11.0), polyarginine (pI 10.9) and polylysine (pI 9.7) can deposit sodium silicate or silicon precursors into silica nanoparticles spontaneously and instantly, but the too quick reaction rate often leads to the segregation or sedimentation of the resulting nanoparticles into undesirable micro-scale aggregates [21–23]. On the other hand, the biomacromolecules with pI values less than 7.0 usually have no or weak silica-precipitating capacity [24]. To resolve the dilemma, polymers with moderate interaction towards silicon precursors should be preferred. The silica nanoparticles will occur when the silicon precursor mingle with the polymer solution thoroughly. The resultant nanoparticles will distribute uniformly in the solution with long inter-particles distance. Meanwhile, the polymer chains can isolate these particles and thus suppress their aggregation. Since pI values are directly related to the mineralization rate [24], in this study, gelatin with lower pI value (8.5) is chosen as the most preferential candidate. It has been discovered that gelatin solution is capable of manipulating the formation of silica nanoparticles from sodium silicate [25–27]. Meanwhile, it is well known that gelatin displays outstanding film-forming ability. Accordingly, when utilized for the nanocomposite membrane fabrication, it may delicately integrate the multiple functions of gelatin. In this study, the feasibility of fabricating gelatin–silica nanocomposite membrane was demonstrated. The effects of the fabrication conditions (sodium silicate concentration and pH value) on the synthesis of the gelatin-inspired silica nanoparticles were investigated, and the effects of silica incorporation on the chemical and physical structures and water vapor adsorption of the nanocomposite membranes were systematically characterized. The dehumidification performance of the resultant membranes was explored.
2. Experimental 2.1. Chemicals Gelatin from porcine skin (type A, 300 Bloom, isoelectric point pI = 8–9) was purchased from Sigma Chemical Company. Sodium silicate (23% SiO2 ) was obtained from Tianjin Jiangtian Chemical Co. Ltd. Porous polysulfone (PS) hollow-fiber membranes (the support layer) with molecular weight cut off 30,000 were supplied by Tianjin Motian Membrane Engineering and Technology Co., Ltd. High-purity propylene (99.999+% pure) and nitrogen (99.999+% pure) were used as feed and sweep gas.
2.2. Fabrication of gelatin–silica nanocomposite membranes Gelatin solutions of 4 wt.% in water were prepared by stirring the initial powder in water for 1 h at 40 ◦ C. Silicate solutions of specific concentration (from 10 mM to 50 mM) were obtained by dilution of the sodium silicate solution in water followed by acidification to desired pH value (pH 5.0 or 7.0) with 0.5 M HCl solution. After equilibration at 40 ◦ C for 5 min, 50 ml of sodium silicate solutions were added dropwise to 50 ml of gelatin solutions and kept stirred for 1 h. After the solution cast on the porous PS hollow-fiber support layer, the pristine membranes were dried at room temperature for 12 h. The resultant membranes were designated as gelatin–silicaX/PS, where X indicates the fabrication condition. Considering that the polymer–inorganic nanocomposite membranes on the support layer were too thin, the flat-sheet membranes were used instead to characterize the chemical and physical properties. The flat-sheet membranes were fabricated by casting the gelatin–silica solution onto a glass plate to a desired thickness. Placing at room temperature for about 48 h, the completely dried membranes were subsequently peeled off. The asprepared flat-sheet nanocomposite membranes were designated as gelatin–silica-X, where X indicates the fabrication condition. 2.3. Characterization Silica nanoparticles were obtained by centrifuging the gelatin–silica solution and subsequently redispersed in water. This process was repeated two times to thoroughly get rid of free gelatin. The Nanosem 430 field emission scanning electron microscopy (FESEM) was utilized to characterize the size and morphology of the nanoparticles after the samples were deposited on the monocrystalline silicon. Thermogravimetric analyzer (PerkinElmer TGA 7) over a temperature range of 25–800 ◦ C at a heating rate of 10 ◦ C/min under air atmosphere was used to determine the contents of the organic/inorganic components in the gelatin-deposited silica nanoparticles. The morphologies and size distributions of the nanoparticles in the cross-section of gelatin–silica nanocomposite membranes was characterized by FESEM. 29 Si NMR was employed to judge the mean condensation degree of silica network. The nanocomposite membranes were cut into small fragments and loaded into the rotor. The solid-state NMR spectra were recorded on a InfinityPlus-400 MHz with spinning rate of 4.5 kHz. The crystallinity of the gelatin membranes and gelatin–silica nanocomposite membranes were acquired using a X-ray diffractometer (Rigaku D/max 2500v/pc, CuK 40 kV, 200 mA) in the range of 3–50◦ at the speed of 8◦ min−1 . The content of silica nanoparticles in the gelatin–silica nanocomposite membranes was determined by TGA analysis over a temperature range of 25–800 ◦ C at a heating rate of 10 ◦ C/min under air atmosphere. Dynamic light scattering (ZetaPALS/BI-9000) was used to measure the size of the gelatin aggregates in the aqueous solution for elucidating the relevant mechanism in the mineralization process. Free volume properties of the nanocomposite membranes were probed by the Positron Annihilation Lifetime Spectroscopy (PALS) EG&G ORTEC fast–fast system with a resolution of 201 ps. Two pieces of membranes, each with an overall thickness of about 1 mm, were placed on either side of the 22 Na positron source. The integral statistics for each spectrum was equal to 10 million coincidences. The PALS spectra were further analyzed using Melt program. The PALS spectra were analyzed using the Maximum Entropy for Lifetime Analysis (MELT) program [28], which is based on the Bayesian theorem [29,30] and is implemented in MATLAB software. In the analysis using MELT, there is no need to specify the number of peaks beforehand. The entropy weight was approximately 5 × 10−8 , and
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the maximum probability was selected. A semi-empirical Eq. (1) is proposed for estimating the average radii of free volume elements from o-Ps lifetime based on the assumption that the o-Ps is localized in a spherical potential well surrounded by an electron layer of thickness r equal to 0.1656 nm [31–33]. i =
1 ri 1− + 2 ri + r
1 2
sin
2r −1 i ri + r
(1)
where i is the o-Ps lifetime (ns), and ri is the radius of the free volume element. 2.4. Adsorption experiments The flat-sheet films were dried under vacuum for at least 48 h. Then the dried films were weighed (m0 ) and exposed in propylene or feed at room temperature for 24 h. After reaching adsorption equilibrium, films were weighted (mt ) quickly using electronic balance (Sartorius, BS 224S). The concentration of absorbed water in the film is defined as: c=
mt − m0 m0
(2)
where c is the equilibrium concentration of water in the films (g water/g polymer). 2.5. Gas permeation experiments Dehumidification of 0.3 wt.% water–propylene mixture gas was performed on the gas separation apparatus as introduced in our previous papers [34–36]. A feed pressure of 350 kPa was applied to the shell side of the fibers, and the permeate side was swept by nitrogen and the pressure was maintained at about 180 kPa. Water concentration was 0.3 wt.% in the feed; operation temperature was 298 K; feed and sweeping gas flowing rate was 3.33 × 10−6 m3 (STP)/s and 1.67 × 10−6 m3 (STP)/s, respectively. Under pressure, the feed gas was being fed into the shell side. And the sweep gas permeated to the inside of the fibers. The compositions of the feed and permeate were measured using Agilent 6820 gas chromatography equipped with a TCD detector. The separation properties of membranes are usually evaluated by two parameters, permeation coefficient and separation factor. For a defect-free hollow-fiber membrane, only an outer skin layer is responsible for the selective separation, while the porous support layer renders mechanical strength. Because the thickness of the skin layer is often difficult to accurately measure due to the complicated morphology, “permeance”, (P/l)i , is employed to characterize the transport of component i in the hollow-fiber composite membrane. This eliminates the need to know the authentic thickness, l, of the selective skin layer. (P/l)i = Qi /(Pi A), where Qi is the volumetric flow rate of gas ‘i’ at standard temperature and pressure, p is the transmembrane pressure difference, and A is the membrane skin surface area. The separation factor is the ratio of permeance of components i and j, which is defined as ˛i/j = (P/l)i /(P/l)j . 3. Results and discussion 3.1. Morphology of the nanocomposite membranes Cross-section structure of the gelatin–silica nanocomposite membrane was detected by FESEM and shown in Fig. 1a, which clearly indicated that the nanocomposite membrane with a thickness about 0.4–0.6 m was uniformly and tightly deposited on the support layer. The silica particles were embedded in the polymer matrix with elaborate homogeneity and dispersion (as shown in Fig. 1b–d).
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3.2. Morphology of silica nanoparticles in the nanocomposite membranes Silica nanopaticles for the subsequent morphology characterization was obtained by the rigorous centrifugation of gelatin–silica solution. After redispersion in water, the resultant silica nanoparticles were deposited on the monocrystalline silicon wafer for FESEM observation (shown in Fig. 1e–f). The size and morphology of the silica nanoparticles in the nanocomposite can be regulated by switching the fabrication conditions such as pH value. The diameter of silica particles was 40–60 nm when the pH was 5.0, and the size became 60–80 nm when the pH was 7.0. The gelatin molecules can facilitate the formation of the silica nanoparticles through the interaction between the gelatin amino groups and the silica precursors. For silicate solution used in this work at pH 5.0 and pH 7.0 with concentration ranging from 10 mM to 50 mM, it was observed that no gel formation occurred within 6 h reaction time in the absence of gelatin. Accordingly, no colloidal particles larger than 1–2 nm were observable. However, when silicate solution was mixed with gelatin solution, turbid suspension occurred within 1 h, which demonstrated that the gelatin facilitated the formation of the silica nanoparticles. Gelatin was composed of many kinds of amino acids among which lysine, arginine possessed the distinct ability to catalyze the silica deposition [22,23]. The positively charged amino acids in gelatin chain interacted specifically with the negatively charged silicate precursors, rendering nucleation and growth sites for silica nanoparticles. Furthermore, the silica morphology may be controlled by the self-assembly properties of the gelatin molecules. To understand the effect of the pH values on the final silica morphology, the assembly behavior of gelatin in aqueous solutions was monitored by dynamic light scattering (DLS) experiments. The hydrodynamic diameters of gelatin aggregates were 372 ± 12 nm and 239 ± 12 nm when pH value was 5.0 and 7.0, respectively. The gelatin chains selfassembled into aggregates of different sizes, which were governed by the charge balance. At higher pH, more carboxylate groups were deprotonated. The larger attractive interaction between these positively charged –NH3 + and the negatively charged –COO− would lead to the smaller size of the gelatin aggregates. In gelatin chains, the proportion of amino acid groups, which can facilitate the deposition of silica, such as the arginine, lysine, was about 10%. The deposition of silica initially occurred at these sites. The negatively charged silica precursors were adsorbed by the positively charged amino acid groups on the gelatin chains [25]. Further growth of silica was due to the condensation of silica precursors. Subsequently, the primary particles would aggregate with each other [26]. When the pH was 7.0, the distance between the catalysis sites became shorter owing to the smaller gelatin aggregates size. The aggregation of these primary particles became more evident and induced larger silica nanoparticles. 3.3. Chemical structure of the nanocomposite membranes 29 Si NMR spectra of the nanocomposite membranes in Fig. 2 showed two signals at ca. −103.2 and −113.5 ppm, assigned to Q3 [Si(OSi)3 (OH)] and Q4 [Si(OSi)4 ], respectively with intensity distribution of 23.9% and 76.1%. The high Q3 and Q4 content implied that the condensation of silica precursor proceeded quite completely within the membranes.
3.4. Physical structure of the nanocomposite membranes 3.4.1. TGA study The composition of the gelatin-deposited silica nanoparticles was characterized by TGA. Upon vacuum drying, the obtained silica nanoparticles were conducted thermogravimetric analysis
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Fig. 1. (a) SEM cross-sectional image of gelatin–silica nanocomposite membrane on PS support layer. (b) Cross-sectional image of the gelatin–silica-30 mM nanocomposite membrane (pH 7.0) and its incorporated silica nanoparticles (e). (c) Cross-sectional image of the gelatin–silica-30 mM nanocomposite membrane (pH 5.0) and its incorporated silica nanoparticles (f). (d) Cross-sectional image of the gelatin–silica-50 mM nanocomposite membrane (pH 7.0) and its incorporated silica nanoparticles (g).
(20–800 ◦ C) under air atmosphere. The organic components would decompose at 800 ◦ C and the residue of the silica nanoparticles should be inorganic SiO2 . The TGA result, shown in Fig. 3a, indicated that the gelatin-induced silica nanoparticles comprised of silica (around 52 wt.%) and gelatin (around 48 wt.%). The content of gelatin-deposited silica nanoparticles in the gelatin–silica nanocomposite membranes was also characterized by TGA analysis. The content of silica nanoparticles in the nanocomposite membranes was 1.7 wt.%, 4.6 wt.% and 7.4 wt.% (shown in Fig. 3a), corresponding to the sodium silicate concentration 10 mM, 30 mM and 50 mM. The sodium silicate concentration exerted dramatic effect on the content of silica particle in the nanocomposite
membranes, whereas in majority of cases the size of silica particles changed only slightly. The interaction between the nanoparticles and gelatin improved the thermal stability of the nanocompoisite membranes. And the higher the content of the nanoparticles, the higher thermal stability of the nanocomposite membranes. Fig. 3b indicated that the pH values had little influence on the content of silica nanoparticles in the nanocomposite membranes. Since the size of silica nanoparticles obtained at pH 5.0 were smaller than that at pH 7.0, the amount of silica nanoparticles would be higher at pH 5.0. The larger interaction between gelatin and silica nanoparticles would generate and lead to higher thermal stability at pH 5.0 as shown in Fig. 3b.
Fig. 2. 29 Si NMR spectra of gelatin–silica nanocomposite membranes (sodium silicate concentration 30 mM, pH 7.0, 40 ◦ C).
3.4.2. XRD study The XRD patterns of gelatin film and gelatin–silica nanocomposite membranes were shown in Fig. 4. Gelatin film exhibited the characteristic peak at around 2 = 7.5◦ and 20◦ due to the semicrystalline characteristics. With the incorporation of silica nanoparticles, the orderly packed crystalline regions in gelatin were destroyed. Thus, the intensity of the characteristic peak became weaker. The crystallinity of the nanocomposite membranes could be tuned by changing the fabrication conditions. With the increase of sodium silicate concentration, the peak at 2 = 7.5◦ disappeared and the peak at 2 = 20◦ became lower. The decrease in crystallinity was attributed to that more silica nanoparticles in the membranes cause more severely disrupted chain packing. The crystallinity of the membrane at pH 7.0 was lower than that at pH 5.0. This phenomenon was inconsistent with the previous study: smaller nanoparticles would affect the polymer structure more effectively [2]. The reason might be that smaller nanoparticles at pH 5.0 were easier to aggregate into larger ones.
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Fig. 3. (a) Effect of sodium silicate concentration on the TGA results of gelatin membrane, gelatin-deposited silica and gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of pH values on the TGA results of gelatin membrane, gelatin-deposited silica and gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
3.5. Free volume characterization of the nanocomposite membranes The in situ synthesized silica nanoparticles also exerted dramatic influences on the microscopic structure of the nanocomposite membrane. Fig. 5 displayed cavity size distribution of gelatin membrane and gelatin–silica nanocomposite membranes. PALS of the membranes suggested a bimodal distribution of the free volume elements. The two measured components usually represented two kinds of free volume voids, namely networks pores (r3 ) and aggregates pores (r4 ) [37]. Compared with pure gelatin membranes, the size of large cavities with a radius between 0.3 nm and 0.4 nm and small cavities with a radius between 0.1 nm and 0.3 nm decreased in the nanocomposite membranes after the silica nanoparticles were incorporated. The decrease of the pore size was arisen from the interfered polymer chain packing since the incorporated silica nanoparticles destroyed the crystalline region in the gelatin. Quite probably, the increasing intensity of the network pores derived from the gelatin–silica interfacial region. The free volume properties of the nanocomposite membranes could be tuned by changing the fabrication conditions. With the increase of sodium silicate concentration, the gelatin chains packing were disrupted more severely due to the higher silica nanoparticle content in the membranes, leading to the smaller cavity size of the networks pores and the aggregates pores. When the sodium silicate concentration increased to 50 mM, the intensity of the aggregates pores was considerably increased due to the substantial aggregation of the silica nanoparticles. Both the network pores and the aggregates pores in the nanocomposite membranes which fabricated at pH 5.0 exhibited smaller cavity size and higher intensity than those in the membranes which fabricated at pH 7.0. The reason might be that part of smaller silica nanoparticles destroyed the crystalline region and formed the smaller network pores, and part of the aggregated nanoparticles led to the formation of large voids (exhibited as the aggregates pores).
3.6. Sorption of water vapor/propylene In the sorption measurement, less than 0.2 mg propylene/g membrane was adsorbed in the membrane, which could be ignored when compared to that of water (approximately 15 mg water/g membrane). Accordingly, it was considered that the increasing weight was mainly attributed to adsorbed water. The high sorption selectivity should be arisen from the strong hydrophilic nature of the membrane. The effect of the fabrication condition (sodium silicate concentration and pH values) on water vapor sorption was shown in Fig. 6. Although the silica content in the membranes increased or the size of silica nanoparticles changed, the sorption amount of water vapor in various membranes was quite close. The reason might be that the silica particles had the similar hydrophilicity to gelatin. 3.7. Dehumidification performance of the nanocomposite membranes 3.7.1. Sodium silicate concentration Effects of sodium silicate concentration on the permeance and separation factor of gelatin–silica/PS membranes were shown in Fig. 7a. It was indicated that the permeance and separation factor of the composite membranes in the absence of silica was around 9.37 × 10−9 m3 (STP)/(m2 s Pa) and 96,808, respectively. The dehumidification performances of the composite membranes were highly enhanced by the incorporated silica nanoparticles. When the sodium silicate concentration increased from 10 mM to 30 mM, the permeances were increased gradually to 1.87 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor kept infinite (no propylene could be detected in the permeate). The high separation factor indicated that the gelatin–silica layer was defectfree. With the further increase of the sodium silicate concentration, although the permeance still increased, the separation factor decreased sharply.
Fig. 4. (a) Effect of sodium silicate concentration on the XRD patterns of gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of pH values on the XRD patterns of gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
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Fig. 5. (a) Effect of sodium silicate concentration on the free volume cavity size and distribution in the gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of the pH values on the free volume cavity size and distribution in the gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
Fig. 6. (a) Effect of sodium silicate concentration on water vapor uptake of gelatin–silica nanocomposite membranes in the feed gas at pH 7.0. (b) Effect of pH values on water vapor uptake of gelatin–silica nanocomposite membranes in the feed gas when the sodium silicate concentration is 30 mM.
The separation performance could be elucidated by the free volume characteristics of the membranes (size and size distribution of the free volume voids). In pure gelatin membranes, the aggregates pores and part of the network pores were larger than the propylene molecules (kinetic radius is 0.225 nm [38]). Propylene molecules would penetrate through these pores, which led to low separation factor. And the permeance of the membranes was also very low since the diffusion of water molecules was blocked by propylene molecules. After incorporating silica nanoparticles, the size of the network pores decreased, and the propylene molecules cannot penetrate through these pores. Since water molecules (kinetic radius is 0.132 nm [39]) could penetrate through both the network pores and the aggregates pores, the higher intensity of the network pores facilitated the diffusion of water molecules and led to higher water permeance. Meanwhile, the separation factor was highly improved since the propylene molecules could only penetrate the aggregates pores with low intensity.
When the sodium silicate concentration increased to 40 mM, remarkably increased intensity of the aggregates pores caused the diffusion of propylene easier and resulted in lower separation factor.
3.7.2. pH values Effects of pH on the dehumidification performance of the gelatin–silica/PS membranes were shown in Fig. 7b. When the pH value decreased from 7.0 to 5.0, permeance of the membranes increased from 1.87 × 10−8 m3 (STP)/(m2 s Pa) to 4.31 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor decreased from infinite to 163,423. The higher intensity of the network pores and the aggregates pores facilitated the diffusion of water molecules, which enhanced the permeance of the membranes. Meanwhile, the higher intensity of the aggregates pores rendered the diffusion of propylene molecules easier, while decreased the separation factors.
Fig. 7. (a) Effect of sodium silicate concentrations on the separation performance of the gelatin–silica/PS membranes at pH 7.0. (b) Effect of pH values on the separation performance of the gelatin–silica/PS membranes when the sodium silicate concentration is 30 mM (the * means that the separation factor is infinite).
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When the pH values further increased to 8.5 or 10.0, no silica nanoparticles formed within the gelatin. The permeance was kept almost constant around 1.88 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor sharply decreased to 4000. 4. Conclusion In summary, in the present study, polymer–inorganic nanocomposite membranes were prepared via in situ generation of inorganic nanoparticles using the biomineralization-inspired process. The polymer matrix of the nanocomposite membranes coincidently served as the catalyst for inorganic precursor, and confined-space for the inorganic nanoparticles, which ensured the facile membrane fabrication and suppressed the aggregation of inorganic particles within the membranes. The homogeneously distributed nanoparticles endowed the membranes with appropriate free volume properties and superior dehumidification performances. The permeance and separation factor reached 1.87 × 10−8 m3 (STP)/(m2 s Pa) and infinite of the gelatin–silica nanocomposite membranes fabricated at the sodium silicate concentration 30 mM and pH 7.0. This novel approach allows superior control of the nanoparticles morphology and the membrane architecture, and hopefully it will establish a facile, efficient and generic new-generation platform for preparing a variety of polymer–inorganic nanocomposite materials. Acknowledgements We gratefully acknowledge the help of Mr. P. Yao and Mr. L.Q. Shi with the FESEM and 29 Si NMR characterizations. We also acknowledge the financial supports from the National Basic Research Program of China (No. 2009CB623404), the Program for Changjiang Scholars and Innovative Research Team in University from the Ministry of Education of China, and the Program of Introducing Talents of Discipline to Universities (No: B06006). References [1] W.U. Huyuh, J.J. Dittmer, A.P. Alivisatos, Hybrid nanorod-polymer solar cells, Science 295 (2002) 2425–2427. [2] T.C. Merkel, B.D. Freeman, R.J. Spontak, Z. He, I. Pinnau, P. Meakin, A.J. Hill, Ultrapermeable, reverse-selective nanocomposite membranes, Science 296 (2002) 519–522. [3] N.P Patel, A.C. Miller, R.J. Spontak, Highly CO2 -permeable and selective polymer nanocomposite membranes, Adv. Mater. 15 (2003) 729–733. [4] M. MacLachlan, M. Ginzburg, N. Coombs, T.W. Coyle, N.P. Raju, J.E. Greedan, G.A. Ozin, I. Manners, Shaped ceramics with tunable magnetic properties from metal-containing polymers, Science 287 (2000) 1460–1463. [5] K. Valle, P. Belleville, F. Pereira, C. Sanchez, Hierarchically structured transparent hybrid membranes by in situ growth of mesostructured organosilica in host polymer, Nat. Mater. 5 (2006) 107–111. [6] T.J. Kang, M. Cha, E.Y. Jang, J. Shin, H.U. Im, Y. Kim, J. Lee, Y.H. Kim, Ultra-thin and conductive nanomembrane arrays for nanomechanical transducers, Adv. Mater. 20 (2008) 3131–3137. [7] C.Y. Jiang, S. Markutsya, Y. Pikus, V.V. Tsukruk, Freely suspended nanocomposite membranes as highly sensitive sensors, Nat. Mater. 3 (2004) 721–728. [8] Z.W. Chen, B. Holmberg, W.Z. Li, X. Wang, W.Q. Deng, R. Munoz, Y.S. Yan, Nafion/zeolite nanocomposite membrane by in situ crystallization for a direct methanol fuel cell, Chem. Mater. 18 (2006) 5669–5675. [9] P. Podsiadlo, A.K. Kaushik, E.M. Arruda, A.M. Waas, B.S. Shim, J.D. Xu, H. Nandivada, B.G. Pumplin, J. Lahann, A. Ramamoorthy, N.A. Kotov, Ultrastrong and stiff layered polymer nanocomposites, Science 318 (2007) 80–83. [10] K. Lee, S.W. Park, M.J. Ko, K. Kim, N.G. Park, Selective positioning of organic dyes in a mesoporous inorganic oxide film, Nat. Mater. 8 (2009) 665–671. [11] H.Y. Chen, E. Ruckenstein, Nanoparticle aggregation in the presence of a block copolymer, J. Chem. Phys. 131 (2009) 244904.
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Facile approach to polymer–inorganic nanocomposite membrane through a biomineralization-inspired process Fusheng Pan, Qinglai Cheng, Huiping Jia, Zhongyi Jiang ∗ Key Laboratory for Green Technology, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
a r t i c l e
i n f o
Article history: Received 22 February 2010 Received in revised form 6 April 2010 Accepted 11 April 2010 Available online 24 April 2010 Keywords: Nanocomposite membrane Gelatin Biomineralization Silica Gas dehumidification
a b s t r a c t A novel and facile biomineralization-inspired approach to fabricating the polymer–inorganic nanocomposite membrane was proposed utilizing manifold functions of polymer: forming the ultrathin membrane scaffold, inducing (templating and catalyzing) the in situ generation of inorganic nanoparticles, confining and suppressing the aggregation of inorganic particles. More specifically, ultrathin gelatin–silica nanocomposite membranes (0.4–0.6 m) with homogeneously dispersed silica nanoparticles (40–80 nm) were fabricated onto a porous substrate mildly and rapidly. The morphology and the size of the silica nanoparticles can be conveniently tuned by simply varying the fabrication conditions such as concentration of the silica precursor, pH value of the membrane casting solution. The as-prepared membranes displayed well-defined free volume characteristics, and superior dehumidification performance. The dehumidification experiments using 0.3 wt.% water vapor/propylene mixture gas as model showed that water permeance was 1.87 × 10−8 m3 (STP)/(m2 s Pa) and separation factor was infinite for the composite membranes fabricated at the sodium silicate concentration 30 mM and the pH 7.0. © 2010 Elsevier B.V. All rights reserved.
1. Introduction Polymer–inorganic nanocomposite membranes where inorganic nanoparticles are dispersed inside polymer membrane matrix have been of great interest in recent years due to their intrinsic advantages over pure polymeric or inorganic membranes as well as their immense application potential in energy, environment, biomedical materials and devices [1–4]. In most cases, the presence of nanoparticles will significantly increase mechanical, thermal, chemical stability and working performance of the nanocomposite membranes [5–8]. Until now, the most common methods for fabricating nanocomposite membranes encompass physical blending, in situ polymerization (simultaneous polymerization, consecutive polymerization and twin polymerization). (1) Physical blending. Inorganic nanoparticles are added into the organic monomers, oligomers or polymers solution under mechanical stirring and/or ultrasonic treatment. The nanocomposite membranes are obtained after the solvent evaporation or polymerization [9]. In some cases, functional groups such as hydroxyl, carboxyl are usually existed on the surface of inorganic particles, which can generate initiating radicals, cations or anions to initiate the polymerization of the monomers on their surface [10]. Although this method is facile and generic, and in particular the proportion of the polymer moiety and inorganic moiety
∗ Corresponding author. Tel.: +86 22 23500086; fax: +86 22 23500086. E-mail address: [email protected] (Z. Jiang). 0376-7388/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2010.04.017
are easy to control, it severely suffers from the liable aggregation of inorganic nanoparticles [11,12]. (2) In situ polymerization. Organic monomers, oligomers or polymers and inorganic precursors are mixed together in aqueous/organic solution or water–oil emulsion [13,14]. Through hydrolysis and condensation of the inorganic precursors, nanoparticles are in situ generated and homogeneously dispersed in polymer matrix. The advantage of this method is manifold: the reaction conditions usually take place at room temperature and ambient pressure, and the concentrations of organic and inorganic components can be conveniently altered in solution or emulsion. Additionally, the organic and inorganic moieties are mixed at the molecular level within the membranes. However, the involvement of acid or base catalyst incurs the considerable difficulty in controlling the reaction rate and the morphologies of the inorganic particles. Furthermore, the harsh microenvironment limits its wide applicability to some extent. If we take a look at nature-existing biomaterials, we will discover with ease that biomineralization, the process by which living organisms produce minerals, can achieve this goal in a surprisingly facile way. Since 1990s, many biomineralization-inspired processes were developed to prepare the inorganic nanoparticles with controllable morphology in vitro by the induction of natural and synthesized polymers [15–18]. It is envisaged by us that if these natural or synthetic biomineral inducers can be directly employed as bulk membrane materials, the hierarchically structure polymer–inorganic nanocomposite membranes will be formed through the simultaneous crosslinking and biomineralization or biomimetic mineralization process. More explicitly, the polymer
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exerts the following multiple functions: forming the ultrathin membrane scaffold, inducing (templating and catalyzing) the in situ generation of inorganic nanoparticles, confining and suppressing the aggregation of inorganic particles. Such bioinspired approach will manifest several distinct advantages: (1) Rapid. The process can be accomplished even within seconds. (2) Polymorphous. Morphology of the inorganic particles can be tailored by varying the deposition conditions. It is also intuitive that small building blocks can be further organized into complex forms [19,20]. (3) Mild. Formation of the inorganic particles occurs at ambient temperature and neutral pH. (4) Inexpensive. Both polymer and inorganic precursor can be available at rather low cost. (5) Green. All the relevant materials and steps are environmentally benign. To the best of our knowledge, quite rare if not none of such reports have been found in the existing literatures. For the one-step fabrication of the polymer–inorganic nanocomposite membranes, the exquisite match of polymers and inorganic precursors are of paramount significance to acquire the synchronized mineralization rates of inorganic precursor and crosslinking/curing rate of the polymeric materials. Take the case of biosilification, lysozyme (pI 11.0), polyarginine (pI 10.9) and polylysine (pI 9.7) can deposit sodium silicate or silicon precursors into silica nanoparticles spontaneously and instantly, but the too quick reaction rate often leads to the segregation or sedimentation of the resulting nanoparticles into undesirable micro-scale aggregates [21–23]. On the other hand, the biomacromolecules with pI values less than 7.0 usually have no or weak silica-precipitating capacity [24]. To resolve the dilemma, polymers with moderate interaction towards silicon precursors should be preferred. The silica nanoparticles will occur when the silicon precursor mingle with the polymer solution thoroughly. The resultant nanoparticles will distribute uniformly in the solution with long inter-particles distance. Meanwhile, the polymer chains can isolate these particles and thus suppress their aggregation. Since pI values are directly related to the mineralization rate [24], in this study, gelatin with lower pI value (8.5) is chosen as the most preferential candidate. It has been discovered that gelatin solution is capable of manipulating the formation of silica nanoparticles from sodium silicate [25–27]. Meanwhile, it is well known that gelatin displays outstanding film-forming ability. Accordingly, when utilized for the nanocomposite membrane fabrication, it may delicately integrate the multiple functions of gelatin. In this study, the feasibility of fabricating gelatin–silica nanocomposite membrane was demonstrated. The effects of the fabrication conditions (sodium silicate concentration and pH value) on the synthesis of the gelatin-inspired silica nanoparticles were investigated, and the effects of silica incorporation on the chemical and physical structures and water vapor adsorption of the nanocomposite membranes were systematically characterized. The dehumidification performance of the resultant membranes was explored.
2. Experimental 2.1. Chemicals Gelatin from porcine skin (type A, 300 Bloom, isoelectric point pI = 8–9) was purchased from Sigma Chemical Company. Sodium silicate (23% SiO2 ) was obtained from Tianjin Jiangtian Chemical Co. Ltd. Porous polysulfone (PS) hollow-fiber membranes (the support layer) with molecular weight cut off 30,000 were supplied by Tianjin Motian Membrane Engineering and Technology Co., Ltd. High-purity propylene (99.999+% pure) and nitrogen (99.999+% pure) were used as feed and sweep gas.
2.2. Fabrication of gelatin–silica nanocomposite membranes Gelatin solutions of 4 wt.% in water were prepared by stirring the initial powder in water for 1 h at 40 ◦ C. Silicate solutions of specific concentration (from 10 mM to 50 mM) were obtained by dilution of the sodium silicate solution in water followed by acidification to desired pH value (pH 5.0 or 7.0) with 0.5 M HCl solution. After equilibration at 40 ◦ C for 5 min, 50 ml of sodium silicate solutions were added dropwise to 50 ml of gelatin solutions and kept stirred for 1 h. After the solution cast on the porous PS hollow-fiber support layer, the pristine membranes were dried at room temperature for 12 h. The resultant membranes were designated as gelatin–silicaX/PS, where X indicates the fabrication condition. Considering that the polymer–inorganic nanocomposite membranes on the support layer were too thin, the flat-sheet membranes were used instead to characterize the chemical and physical properties. The flat-sheet membranes were fabricated by casting the gelatin–silica solution onto a glass plate to a desired thickness. Placing at room temperature for about 48 h, the completely dried membranes were subsequently peeled off. The asprepared flat-sheet nanocomposite membranes were designated as gelatin–silica-X, where X indicates the fabrication condition. 2.3. Characterization Silica nanoparticles were obtained by centrifuging the gelatin–silica solution and subsequently redispersed in water. This process was repeated two times to thoroughly get rid of free gelatin. The Nanosem 430 field emission scanning electron microscopy (FESEM) was utilized to characterize the size and morphology of the nanoparticles after the samples were deposited on the monocrystalline silicon. Thermogravimetric analyzer (PerkinElmer TGA 7) over a temperature range of 25–800 ◦ C at a heating rate of 10 ◦ C/min under air atmosphere was used to determine the contents of the organic/inorganic components in the gelatin-deposited silica nanoparticles. The morphologies and size distributions of the nanoparticles in the cross-section of gelatin–silica nanocomposite membranes was characterized by FESEM. 29 Si NMR was employed to judge the mean condensation degree of silica network. The nanocomposite membranes were cut into small fragments and loaded into the rotor. The solid-state NMR spectra were recorded on a InfinityPlus-400 MHz with spinning rate of 4.5 kHz. The crystallinity of the gelatin membranes and gelatin–silica nanocomposite membranes were acquired using a X-ray diffractometer (Rigaku D/max 2500v/pc, CuK 40 kV, 200 mA) in the range of 3–50◦ at the speed of 8◦ min−1 . The content of silica nanoparticles in the gelatin–silica nanocomposite membranes was determined by TGA analysis over a temperature range of 25–800 ◦ C at a heating rate of 10 ◦ C/min under air atmosphere. Dynamic light scattering (ZetaPALS/BI-9000) was used to measure the size of the gelatin aggregates in the aqueous solution for elucidating the relevant mechanism in the mineralization process. Free volume properties of the nanocomposite membranes were probed by the Positron Annihilation Lifetime Spectroscopy (PALS) EG&G ORTEC fast–fast system with a resolution of 201 ps. Two pieces of membranes, each with an overall thickness of about 1 mm, were placed on either side of the 22 Na positron source. The integral statistics for each spectrum was equal to 10 million coincidences. The PALS spectra were further analyzed using Melt program. The PALS spectra were analyzed using the Maximum Entropy for Lifetime Analysis (MELT) program [28], which is based on the Bayesian theorem [29,30] and is implemented in MATLAB software. In the analysis using MELT, there is no need to specify the number of peaks beforehand. The entropy weight was approximately 5 × 10−8 , and
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the maximum probability was selected. A semi-empirical Eq. (1) is proposed for estimating the average radii of free volume elements from o-Ps lifetime based on the assumption that the o-Ps is localized in a spherical potential well surrounded by an electron layer of thickness r equal to 0.1656 nm [31–33]. i =
1 ri 1− + 2 ri + r
1 2
sin
2r −1 i ri + r
(1)
where i is the o-Ps lifetime (ns), and ri is the radius of the free volume element. 2.4. Adsorption experiments The flat-sheet films were dried under vacuum for at least 48 h. Then the dried films were weighed (m0 ) and exposed in propylene or feed at room temperature for 24 h. After reaching adsorption equilibrium, films were weighted (mt ) quickly using electronic balance (Sartorius, BS 224S). The concentration of absorbed water in the film is defined as: c=
mt − m0 m0
(2)
where c is the equilibrium concentration of water in the films (g water/g polymer). 2.5. Gas permeation experiments Dehumidification of 0.3 wt.% water–propylene mixture gas was performed on the gas separation apparatus as introduced in our previous papers [34–36]. A feed pressure of 350 kPa was applied to the shell side of the fibers, and the permeate side was swept by nitrogen and the pressure was maintained at about 180 kPa. Water concentration was 0.3 wt.% in the feed; operation temperature was 298 K; feed and sweeping gas flowing rate was 3.33 × 10−6 m3 (STP)/s and 1.67 × 10−6 m3 (STP)/s, respectively. Under pressure, the feed gas was being fed into the shell side. And the sweep gas permeated to the inside of the fibers. The compositions of the feed and permeate were measured using Agilent 6820 gas chromatography equipped with a TCD detector. The separation properties of membranes are usually evaluated by two parameters, permeation coefficient and separation factor. For a defect-free hollow-fiber membrane, only an outer skin layer is responsible for the selective separation, while the porous support layer renders mechanical strength. Because the thickness of the skin layer is often difficult to accurately measure due to the complicated morphology, “permeance”, (P/l)i , is employed to characterize the transport of component i in the hollow-fiber composite membrane. This eliminates the need to know the authentic thickness, l, of the selective skin layer. (P/l)i = Qi /(Pi A), where Qi is the volumetric flow rate of gas ‘i’ at standard temperature and pressure, p is the transmembrane pressure difference, and A is the membrane skin surface area. The separation factor is the ratio of permeance of components i and j, which is defined as ˛i/j = (P/l)i /(P/l)j . 3. Results and discussion 3.1. Morphology of the nanocomposite membranes Cross-section structure of the gelatin–silica nanocomposite membrane was detected by FESEM and shown in Fig. 1a, which clearly indicated that the nanocomposite membrane with a thickness about 0.4–0.6 m was uniformly and tightly deposited on the support layer. The silica particles were embedded in the polymer matrix with elaborate homogeneity and dispersion (as shown in Fig. 1b–d).
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3.2. Morphology of silica nanoparticles in the nanocomposite membranes Silica nanopaticles for the subsequent morphology characterization was obtained by the rigorous centrifugation of gelatin–silica solution. After redispersion in water, the resultant silica nanoparticles were deposited on the monocrystalline silicon wafer for FESEM observation (shown in Fig. 1e–f). The size and morphology of the silica nanoparticles in the nanocomposite can be regulated by switching the fabrication conditions such as pH value. The diameter of silica particles was 40–60 nm when the pH was 5.0, and the size became 60–80 nm when the pH was 7.0. The gelatin molecules can facilitate the formation of the silica nanoparticles through the interaction between the gelatin amino groups and the silica precursors. For silicate solution used in this work at pH 5.0 and pH 7.0 with concentration ranging from 10 mM to 50 mM, it was observed that no gel formation occurred within 6 h reaction time in the absence of gelatin. Accordingly, no colloidal particles larger than 1–2 nm were observable. However, when silicate solution was mixed with gelatin solution, turbid suspension occurred within 1 h, which demonstrated that the gelatin facilitated the formation of the silica nanoparticles. Gelatin was composed of many kinds of amino acids among which lysine, arginine possessed the distinct ability to catalyze the silica deposition [22,23]. The positively charged amino acids in gelatin chain interacted specifically with the negatively charged silicate precursors, rendering nucleation and growth sites for silica nanoparticles. Furthermore, the silica morphology may be controlled by the self-assembly properties of the gelatin molecules. To understand the effect of the pH values on the final silica morphology, the assembly behavior of gelatin in aqueous solutions was monitored by dynamic light scattering (DLS) experiments. The hydrodynamic diameters of gelatin aggregates were 372 ± 12 nm and 239 ± 12 nm when pH value was 5.0 and 7.0, respectively. The gelatin chains selfassembled into aggregates of different sizes, which were governed by the charge balance. At higher pH, more carboxylate groups were deprotonated. The larger attractive interaction between these positively charged –NH3 + and the negatively charged –COO− would lead to the smaller size of the gelatin aggregates. In gelatin chains, the proportion of amino acid groups, which can facilitate the deposition of silica, such as the arginine, lysine, was about 10%. The deposition of silica initially occurred at these sites. The negatively charged silica precursors were adsorbed by the positively charged amino acid groups on the gelatin chains [25]. Further growth of silica was due to the condensation of silica precursors. Subsequently, the primary particles would aggregate with each other [26]. When the pH was 7.0, the distance between the catalysis sites became shorter owing to the smaller gelatin aggregates size. The aggregation of these primary particles became more evident and induced larger silica nanoparticles. 3.3. Chemical structure of the nanocomposite membranes 29 Si NMR spectra of the nanocomposite membranes in Fig. 2 showed two signals at ca. −103.2 and −113.5 ppm, assigned to Q3 [Si(OSi)3 (OH)] and Q4 [Si(OSi)4 ], respectively with intensity distribution of 23.9% and 76.1%. The high Q3 and Q4 content implied that the condensation of silica precursor proceeded quite completely within the membranes.
3.4. Physical structure of the nanocomposite membranes 3.4.1. TGA study The composition of the gelatin-deposited silica nanoparticles was characterized by TGA. Upon vacuum drying, the obtained silica nanoparticles were conducted thermogravimetric analysis
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Fig. 1. (a) SEM cross-sectional image of gelatin–silica nanocomposite membrane on PS support layer. (b) Cross-sectional image of the gelatin–silica-30 mM nanocomposite membrane (pH 7.0) and its incorporated silica nanoparticles (e). (c) Cross-sectional image of the gelatin–silica-30 mM nanocomposite membrane (pH 5.0) and its incorporated silica nanoparticles (f). (d) Cross-sectional image of the gelatin–silica-50 mM nanocomposite membrane (pH 7.0) and its incorporated silica nanoparticles (g).
(20–800 ◦ C) under air atmosphere. The organic components would decompose at 800 ◦ C and the residue of the silica nanoparticles should be inorganic SiO2 . The TGA result, shown in Fig. 3a, indicated that the gelatin-induced silica nanoparticles comprised of silica (around 52 wt.%) and gelatin (around 48 wt.%). The content of gelatin-deposited silica nanoparticles in the gelatin–silica nanocomposite membranes was also characterized by TGA analysis. The content of silica nanoparticles in the nanocomposite membranes was 1.7 wt.%, 4.6 wt.% and 7.4 wt.% (shown in Fig. 3a), corresponding to the sodium silicate concentration 10 mM, 30 mM and 50 mM. The sodium silicate concentration exerted dramatic effect on the content of silica particle in the nanocomposite
membranes, whereas in majority of cases the size of silica particles changed only slightly. The interaction between the nanoparticles and gelatin improved the thermal stability of the nanocompoisite membranes. And the higher the content of the nanoparticles, the higher thermal stability of the nanocomposite membranes. Fig. 3b indicated that the pH values had little influence on the content of silica nanoparticles in the nanocomposite membranes. Since the size of silica nanoparticles obtained at pH 5.0 were smaller than that at pH 7.0, the amount of silica nanoparticles would be higher at pH 5.0. The larger interaction between gelatin and silica nanoparticles would generate and lead to higher thermal stability at pH 5.0 as shown in Fig. 3b.
Fig. 2. 29 Si NMR spectra of gelatin–silica nanocomposite membranes (sodium silicate concentration 30 mM, pH 7.0, 40 ◦ C).
3.4.2. XRD study The XRD patterns of gelatin film and gelatin–silica nanocomposite membranes were shown in Fig. 4. Gelatin film exhibited the characteristic peak at around 2 = 7.5◦ and 20◦ due to the semicrystalline characteristics. With the incorporation of silica nanoparticles, the orderly packed crystalline regions in gelatin were destroyed. Thus, the intensity of the characteristic peak became weaker. The crystallinity of the nanocomposite membranes could be tuned by changing the fabrication conditions. With the increase of sodium silicate concentration, the peak at 2 = 7.5◦ disappeared and the peak at 2 = 20◦ became lower. The decrease in crystallinity was attributed to that more silica nanoparticles in the membranes cause more severely disrupted chain packing. The crystallinity of the membrane at pH 7.0 was lower than that at pH 5.0. This phenomenon was inconsistent with the previous study: smaller nanoparticles would affect the polymer structure more effectively [2]. The reason might be that smaller nanoparticles at pH 5.0 were easier to aggregate into larger ones.
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Fig. 3. (a) Effect of sodium silicate concentration on the TGA results of gelatin membrane, gelatin-deposited silica and gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of pH values on the TGA results of gelatin membrane, gelatin-deposited silica and gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
3.5. Free volume characterization of the nanocomposite membranes The in situ synthesized silica nanoparticles also exerted dramatic influences on the microscopic structure of the nanocomposite membrane. Fig. 5 displayed cavity size distribution of gelatin membrane and gelatin–silica nanocomposite membranes. PALS of the membranes suggested a bimodal distribution of the free volume elements. The two measured components usually represented two kinds of free volume voids, namely networks pores (r3 ) and aggregates pores (r4 ) [37]. Compared with pure gelatin membranes, the size of large cavities with a radius between 0.3 nm and 0.4 nm and small cavities with a radius between 0.1 nm and 0.3 nm decreased in the nanocomposite membranes after the silica nanoparticles were incorporated. The decrease of the pore size was arisen from the interfered polymer chain packing since the incorporated silica nanoparticles destroyed the crystalline region in the gelatin. Quite probably, the increasing intensity of the network pores derived from the gelatin–silica interfacial region. The free volume properties of the nanocomposite membranes could be tuned by changing the fabrication conditions. With the increase of sodium silicate concentration, the gelatin chains packing were disrupted more severely due to the higher silica nanoparticle content in the membranes, leading to the smaller cavity size of the networks pores and the aggregates pores. When the sodium silicate concentration increased to 50 mM, the intensity of the aggregates pores was considerably increased due to the substantial aggregation of the silica nanoparticles. Both the network pores and the aggregates pores in the nanocomposite membranes which fabricated at pH 5.0 exhibited smaller cavity size and higher intensity than those in the membranes which fabricated at pH 7.0. The reason might be that part of smaller silica nanoparticles destroyed the crystalline region and formed the smaller network pores, and part of the aggregated nanoparticles led to the formation of large voids (exhibited as the aggregates pores).
3.6. Sorption of water vapor/propylene In the sorption measurement, less than 0.2 mg propylene/g membrane was adsorbed in the membrane, which could be ignored when compared to that of water (approximately 15 mg water/g membrane). Accordingly, it was considered that the increasing weight was mainly attributed to adsorbed water. The high sorption selectivity should be arisen from the strong hydrophilic nature of the membrane. The effect of the fabrication condition (sodium silicate concentration and pH values) on water vapor sorption was shown in Fig. 6. Although the silica content in the membranes increased or the size of silica nanoparticles changed, the sorption amount of water vapor in various membranes was quite close. The reason might be that the silica particles had the similar hydrophilicity to gelatin. 3.7. Dehumidification performance of the nanocomposite membranes 3.7.1. Sodium silicate concentration Effects of sodium silicate concentration on the permeance and separation factor of gelatin–silica/PS membranes were shown in Fig. 7a. It was indicated that the permeance and separation factor of the composite membranes in the absence of silica was around 9.37 × 10−9 m3 (STP)/(m2 s Pa) and 96,808, respectively. The dehumidification performances of the composite membranes were highly enhanced by the incorporated silica nanoparticles. When the sodium silicate concentration increased from 10 mM to 30 mM, the permeances were increased gradually to 1.87 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor kept infinite (no propylene could be detected in the permeate). The high separation factor indicated that the gelatin–silica layer was defectfree. With the further increase of the sodium silicate concentration, although the permeance still increased, the separation factor decreased sharply.
Fig. 4. (a) Effect of sodium silicate concentration on the XRD patterns of gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of pH values on the XRD patterns of gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
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Fig. 5. (a) Effect of sodium silicate concentration on the free volume cavity size and distribution in the gelatin–silica nanocomposite membranes at pH 7.0. (b) Effect of the pH values on the free volume cavity size and distribution in the gelatin–silica nanocomposite membranes when the sodium silicate concentration is 30 mM.
Fig. 6. (a) Effect of sodium silicate concentration on water vapor uptake of gelatin–silica nanocomposite membranes in the feed gas at pH 7.0. (b) Effect of pH values on water vapor uptake of gelatin–silica nanocomposite membranes in the feed gas when the sodium silicate concentration is 30 mM.
The separation performance could be elucidated by the free volume characteristics of the membranes (size and size distribution of the free volume voids). In pure gelatin membranes, the aggregates pores and part of the network pores were larger than the propylene molecules (kinetic radius is 0.225 nm [38]). Propylene molecules would penetrate through these pores, which led to low separation factor. And the permeance of the membranes was also very low since the diffusion of water molecules was blocked by propylene molecules. After incorporating silica nanoparticles, the size of the network pores decreased, and the propylene molecules cannot penetrate through these pores. Since water molecules (kinetic radius is 0.132 nm [39]) could penetrate through both the network pores and the aggregates pores, the higher intensity of the network pores facilitated the diffusion of water molecules and led to higher water permeance. Meanwhile, the separation factor was highly improved since the propylene molecules could only penetrate the aggregates pores with low intensity.
When the sodium silicate concentration increased to 40 mM, remarkably increased intensity of the aggregates pores caused the diffusion of propylene easier and resulted in lower separation factor.
3.7.2. pH values Effects of pH on the dehumidification performance of the gelatin–silica/PS membranes were shown in Fig. 7b. When the pH value decreased from 7.0 to 5.0, permeance of the membranes increased from 1.87 × 10−8 m3 (STP)/(m2 s Pa) to 4.31 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor decreased from infinite to 163,423. The higher intensity of the network pores and the aggregates pores facilitated the diffusion of water molecules, which enhanced the permeance of the membranes. Meanwhile, the higher intensity of the aggregates pores rendered the diffusion of propylene molecules easier, while decreased the separation factors.
Fig. 7. (a) Effect of sodium silicate concentrations on the separation performance of the gelatin–silica/PS membranes at pH 7.0. (b) Effect of pH values on the separation performance of the gelatin–silica/PS membranes when the sodium silicate concentration is 30 mM (the * means that the separation factor is infinite).
F. Pan et al. / Journal of Membrane Science 357 (2010) 171–177
When the pH values further increased to 8.5 or 10.0, no silica nanoparticles formed within the gelatin. The permeance was kept almost constant around 1.88 × 10−8 m3 (STP)/(m2 s Pa), and the separation factor sharply decreased to 4000. 4. Conclusion In summary, in the present study, polymer–inorganic nanocomposite membranes were prepared via in situ generation of inorganic nanoparticles using the biomineralization-inspired process. The polymer matrix of the nanocomposite membranes coincidently served as the catalyst for inorganic precursor, and confined-space for the inorganic nanoparticles, which ensured the facile membrane fabrication and suppressed the aggregation of inorganic particles within the membranes. The homogeneously distributed nanoparticles endowed the membranes with appropriate free volume properties and superior dehumidification performances. The permeance and separation factor reached 1.87 × 10−8 m3 (STP)/(m2 s Pa) and infinite of the gelatin–silica nanocomposite membranes fabricated at the sodium silicate concentration 30 mM and pH 7.0. This novel approach allows superior control of the nanoparticles morphology and the membrane architecture, and hopefully it will establish a facile, efficient and generic new-generation platform for preparing a variety of polymer–inorganic nanocomposite materials. Acknowledgements We gratefully acknowledge the help of Mr. P. Yao and Mr. L.Q. Shi with the FESEM and 29 Si NMR characterizations. We also acknowledge the financial supports from the National Basic Research Program of China (No. 2009CB623404), the Program for Changjiang Scholars and Innovative Research Team in University from the Ministry of Education of China, and the Program of Introducing Talents of Discipline to Universities (No: B06006). References [1] W.U. Huyuh, J.J. Dittmer, A.P. Alivisatos, Hybrid nanorod-polymer solar cells, Science 295 (2002) 2425–2427. [2] T.C. Merkel, B.D. Freeman, R.J. Spontak, Z. He, I. Pinnau, P. Meakin, A.J. Hill, Ultrapermeable, reverse-selective nanocomposite membranes, Science 296 (2002) 519–522. [3] N.P Patel, A.C. Miller, R.J. Spontak, Highly CO2 -permeable and selective polymer nanocomposite membranes, Adv. Mater. 15 (2003) 729–733. [4] M. MacLachlan, M. Ginzburg, N. Coombs, T.W. Coyle, N.P. Raju, J.E. Greedan, G.A. Ozin, I. Manners, Shaped ceramics with tunable magnetic properties from metal-containing polymers, Science 287 (2000) 1460–1463. [5] K. Valle, P. Belleville, F. Pereira, C. Sanchez, Hierarchically structured transparent hybrid membranes by in situ growth of mesostructured organosilica in host polymer, Nat. Mater. 5 (2006) 107–111. [6] T.J. Kang, M. Cha, E.Y. Jang, J. Shin, H.U. Im, Y. Kim, J. Lee, Y.H. Kim, Ultra-thin and conductive nanomembrane arrays for nanomechanical transducers, Adv. Mater. 20 (2008) 3131–3137. [7] C.Y. Jiang, S. Markutsya, Y. Pikus, V.V. Tsukruk, Freely suspended nanocomposite membranes as highly sensitive sensors, Nat. Mater. 3 (2004) 721–728. [8] Z.W. Chen, B. Holmberg, W.Z. Li, X. Wang, W.Q. Deng, R. Munoz, Y.S. Yan, Nafion/zeolite nanocomposite membrane by in situ crystallization for a direct methanol fuel cell, Chem. Mater. 18 (2006) 5669–5675. [9] P. Podsiadlo, A.K. Kaushik, E.M. Arruda, A.M. Waas, B.S. Shim, J.D. Xu, H. Nandivada, B.G. Pumplin, J. Lahann, A. Ramamoorthy, N.A. Kotov, Ultrastrong and stiff layered polymer nanocomposites, Science 318 (2007) 80–83. [10] K. Lee, S.W. Park, M.J. Ko, K. Kim, N.G. Park, Selective positioning of organic dyes in a mesoporous inorganic oxide film, Nat. Mater. 8 (2009) 665–671. [11] H.Y. Chen, E. Ruckenstein, Nanoparticle aggregation in the presence of a block copolymer, J. Chem. Phys. 131 (2009) 244904.
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