Desulfurization of model gasoline by bioinspired oleophilic nanocomposite membranes

Journal of Membrane Science 415–416 (2012) 278–287

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Desulfurization of model gasoline by bioinspired oleophilic nanocomposite membranes Ben Li, Wanpeng Liu, Hong Wu, Shengnan Yu, Ruijian Cao, Zhongyi Jiang n Key Laboratory for Green Chemical Technology, Ministry of Education of China, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, P.R. China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 29 November 2011 Received in revised form 1 May 2012 Accepted 2 May 2012 Available online 11 May 2012

Inspired by the silica formation process mediated by silica deposition vesicle (SDV) in diatoms or sponges, silica nanoparticles (SiO2) were in-situ formed within oleophilic polydimethylsiloxane (PDMS) bulk matrix through the controlled biomimetic mineralization in confined space, using either NH3 or cysteamine as inducer/catalyst. Accordingly, different kinds of PDMS-SiO2 nanocomposite membranes were fabricated. It was observed that alkaline/basic inducers and silicon precursors with higher reactivities were more favorable for tailoring the free volume property of the nanocomposite membranes, rendering the dramatic enhancement of mechanical strength and pervaporation separation performance. The as-prepared membrane displayed an optimum desulfurization performance with permeation flux of 7.36 kg/(m2h) and the selectivity of 4.98 towards thiophene in model gasoline. & 2012 Elsevier B.V. All rights reserved.

Keywords: Gasoline desulfurization Nanocomposite membrane Biomimetic mineralization Reverse microemulsion Free volume property

1. Introduction Environmental concerns have resulted in legislations that place strict limits on the sulfur content of vehicle fuel. For instance, in the European Union, a maximum sulfur level of 50 ppm has been stipulated by 2005, with a further reduction to a maximum of 10 ppm nowadays [1–4]. Currently, hydrodesulfurization (HDS) serves as the most commonly used and efficient technique for sulfur removal [5–8]. In recent years, membrane process has attracted increasing attention due to its potential advantages over conventional desulfurization processes, including greater selectivity towards thiophene over olefins, lower operation and energy costs, without hydrogen source and coproduct of H2S gas. S-Brane of Grace Davison Company and TranSepTM of Trans Ionics Corporation represents the successful membrane-dominated techniques for desulfurization of FCC gasoline, whose overall costs only account for 20% of the conventional HDS process [9–11]. Gradually, membrane technique becomes the competitive technique for the deep desulfurization in hydrocarbon streams [12–14]. The core of the membrane technique is the development of membrane materials with superior separation performance and long-term stability. Polydimethylsiloxane (PDMS) has been demonstrated as one of the most widely utilized membrane materials for pervaporative desulfurization [15,16], owing to its outstanding aging resistance,

n

Corresponding author. Tel.: þ86 22 23500086; fax: þ 86 22 23500086. E-mail address: [email protected] (Z. Jiang).

0376-7388/$ - see front matter & 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.memsci.2012.05.010

thermal/chemical stability, good processability, in particular its superior permeability to small molecules [17,18]. Moreover, according to solubility parameter theory, the solubility parameter (d) of PDMS (d ¼ 21.0) is close to the solubility parameter of thiophene and its derivatives (d varied from  19.0 to 20.0) [12]. As a consequence, PDMS polymer will display the priority in selective dissolution of the sulfur components in gasoline. Pure PDMS membranes, however, have relatively poor mechanical strength due to the high flexibility of molecular chains. A number of strategies have been attempted to reinforce elastomeric PDMS in order to acquire better and wider applications. In recent years, elastomeric polymer–inorganic nanocomposites have been the subject of a huge scientific interest. Theoretically, by introducing inorganic fillers into elastomers, the nanocomposites will exhibit dramatically improved bulk properties. However, the reinforcement of PDMS via physical incorporation of inorganic particles has severe challenges. On one hand, the significant difference in hydrophilicity makes it rather difficult to achieve homogeneous hybridization between the PDMS continuous phase and the inorganic dispersed phase via simple physical blending. The accompanying local stress and interface defects may substantially worsen the mechanical properties of the nanocomposite membranes. On the other hand, since PDMS is usually dissolved in nonaqueous oil-based solvent, it is quite difficult and even impossible to manipulate the simultaneous hydrolysis–condensation of silicon precursors and cross-linking of PDMS oligomers in a homogenous phase. A two-step in-situ method was commonly utilized to incorporate inorganic nanoparticles into PDMS matrix by allowing preformed PDMS network

B. Li et al. / Journal of Membrane Science 415–416 (2012) 278–287

Nomenclature A list of symbols

t r I VF FFV

ne n2 u

w

lifetime of positron, ns radius of free volume holes, nm free volume lifetime intensity fractional free volume fractional free volume cross-linking density of the rubber, mol/cm3 volume fraction of rubber phase molar volume of solvent (cm3/mol) interaction parameter between the rubber and the solvent

to swell in silicon precursor in the presence of water and catalyst [19–21]. However, this process was severely restricted by the diffusion of silicon precursor and water within PDMS network. Moreover, the process is difficult to control and the consumption amount of chemical reagents including eco-unfriendly organic solvent is quite large. Thus, it could be envisaged that facile and eco-friendly fabrication of oleophilic polymer networks embedded with homogeneously distributed inorganic particles will bear both academic and technological significance. Herein, we tentatively demonstrated this feasibility by manipulating the silica deposition vesicle (SDV)-inspired silica synthesis within water-in-oil (w/o) reverse microemulsion [22]. In nature, most cell walls are comprised of polymer–inorganic nanocomposite materials. For example, the cell walls of the diatoms are actually chitin-based nanocomposites [23]. In particular, most biominerals are formed in confined spaces. Amorphous hydrated silica nanoparticles in the cell walls are produced by polycondensation of silicic acid molecules within a specific intracellular compartment, termed as the silica deposition vesicle [24]. Silica formation occurs when silicon precursors interact with the enwrapped silica-precipitation inducers [25]. The delineation of biological environments is of crucial importance in biomineralization, because it renders physical boundary for size and shape control of the resultant inorganic nanoparticles [26]. Such a soft confined space endowed aqueous microenvironment for silicaprecipitating inducers, which subsequently directed the silica formation from water insoluble precursor through interfacial molecular recognition and subsequent hydrolysis–condensation reactions [27]. In our recent research, silica nanoparticles were formed by the catalysis and templating of protamine macromolecules in w/o reverse microemulsion, and were in-situ embedded into PDMS bulk matrix, endowing the resultant oleophilic nanocomposite membranes with improved separation performance [28]. In the current study, different kinds of membrane materials, fabricated from small silica-precipitating inducer/catalyst and various silica precursors, were extensively investigated. As a proof-of-principle, PDMS-SiO2 nanocomposite membranes were in-situ fabricated through the synergy of polymerization of PDMS oligomers in the oil phase with silica precipitation in the reverse microemulsion. NH3 and cysteamine were used as inducer/catalyst. Tetraethyl orthosilicate (TEOS) and tetramethyl orthosilicate (TMOS) were used as the silica precursors. The hydrolysis and condensation occurred when the inorganic precursor and the inducer molecules encountered at the water–oil interface. The size and nanostructures of silica could be readily tuned through a rational synergy among hydrolysis/condensation rates, silicaprecipitating inducer type, geometry, interfacial constraints and the size of water droplets in PDMS matrix. The membranes were

J B Td Pi pio pil

gLi0

xLi0 psat i0 @ij

279

permeation flux, kg/(m2h) enrichment factor of thiophene temperature where maximum degradation rate occurred, 1C permeability of component i, gm  1h  1kPa  1 partial pressures of component i on the feed side, kPa partial pressures of component i on the downstream side, kPa activity coefficient of component i mole fraction of the component i in the feed liquid pure component i feed vapor pressure, kPa selectivity of components i and j through the membrane

characterized by Fourier transform-infrared, scanning electron microscope and positron annihilation lifetime spectroscopy, respectively. The mechanical property of the as-prepared nanocomposite membranes was systematically measured by thermogravimetry analysis, tensile strength measurements and equilibrium swelling method. The membrane separation performance was evaluated by pervaporative separation of thiophene/n-octane model gasoline. The effects of feed temperature, feed flow rate and feed concentration on the membrane performance were examined. The manipulation of the free volume property of the nanocomposite membranes as well as its inherent relationship with mechanical property and separation performance were explored.

2. Experimental 2.1. Materials Tris (hydroxymethyl) amino methane hydrochloride (Tris– HCl), tetraethyl orthosilicate (TEOS) and tetramethyl orthosilicate (TMOS) were purchased from Sigma Aldrich. Cysteamine was obtained from Alfa Aesar. Ammonia, Tween 80, Span 80, n-heptane, n-octane and thiophene were supplied by GuangFu fine chemical research institute, China. PDMS oligomer (the viscosity was 5000 mPa s, and the corresponding average molecular weight was around 40,000) and dibutyltin dilaurate were obtained from Beijing chemical company, China. Asymmetric polysulfone (PS) ultrafiltration membranes were ordered from Shanghai Mega Vision Membrane Engineering & Technology Co., Ltd., China. All the other reagents were of analytical grade and utilized without further purification. De-ionized water from a Millipore ultrapure water system was used in all the experiments. 2.2. Synthesis of the PDMS-SiO2 nanocomposite membranes Certain amount of Tween 80/Span 80 mixed surfactant (weight ratio¼1:1), silicon precursor, as well as PDMS oligomer were dissolved in n-heptane at room temperature to make a homogeneous solution. Inducer aqueous solutions were suspended with a concentration of 0.5 M (cysteamine was dissolved in a 25 mM Tris-HCl buffer solution at neutral pH). And then specific amount of the above aqueous solution was drop wise added into the oil solution under vigorous mechanical stirring. After stirring for 30 min, small amount of dibutyltin dilaurate was added. After degassing, the solution was cast onto the polysulfone porous support at room temperature. The membranes were first dried in air for 24 h and then thermally annealed at 80 1C to accomplish cross-linking and evaporate the residual solvent. After that, the

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membranes were washed by water and dried at room temperature. All samples were stored in dust free and dry environment before the pervaporation measurements. For simplicity, samples were designated as PDMS-inducer-(silicon precursor)x. The subscript x demonstrated the molar ratio of silicon precursor to PDMS. For instance, PDMS-NH3-(TMOS)16 illustrated that the molar ratio of TMOS to PDMS was 16.0. PDMS-(TMOS)2 and PDMS-(TEOS)2 were PDMS control membranes, where TEOS/ TMOS only served as crosslinkers. No catalyst (NH3 or cysteamine) solution and surfactant was added.

The volume fraction (n2) of rubber phase was calculated by

n2 ¼

ðm1 Þ=ðr1 Þ ðm2 m1 Þ=ðr2 Þ þ ðm1 Þ=ðr1 Þ

ð4Þ

where m1 and m2 were the weights of the dried and swollen membranes, respectively; r1 and r2 were the density of PDMS and the solvent. The membranes were weighed carefully before being immersed in heptane at 25 1C. The swollen membrane samples were taken out from the solvent solution after 24 h and were subsequently wiped by tissue paper to remove the residual liquid before being weighed.

2.3. Characterizations 2.4. Pervaporative desulfurization experiments The cross-sectional morphology of the nanocomposite membranes was observed with a field emission scanning electron microscope (FESEM, Nanosem 430). Fourier transform infrared spectra (FT-IR) were measured by using a Nicolet, Magna-IR 560 spectrometer. Emulsion and nanoparticles sizes were measured by Brookhaven dynamic light scattering (DLS) instrument. Positron annihilation lifetime spectroscopy (PALS) experiment was conducted by using an ORTEC fast–fast coincidence system (resolution 300 ps) at room temperature. It has been determined that ortho-positronium (o-Ps) was preferentially trapped in freevolume holes. A semiempirical equation given by Eq. (1) correlated lifetime, t with the radius of the free volume cavity, r. This was obtained by assuming that the o-Ps was localized in a spherical potential well surrounded by an electron layer of thickness Dr equal to 0.1656 nm [29,30]. The corresponding intensity I gave the probability of o-Ps formation, and it was proportional to the number of free volume cavities in the system.  1    1 r 1 2pr þ t ¼ 1 ð1Þ sin 2 r þ Dr 2p r þ Dr V F,i ¼

4pr i 3 3

ð2Þ

The PALS results were the first to experimentally show that these pervaporation membranes were composed of two types of pores network pores (r3), and aggregate pores (r4) [31]. The o-Ps lifetime (t3 and t4) and corresponding intensity (I%) contained information about the fractional free volume (FFV) [32]. The value of FFV could be expressed as a product of free volume, VF,i (as deduced from ti) and Ii, as VF3I3 þVF4I4 in the current study. The integral statistics for each spectrum was more than 1  106 coincidences. The spectra were evaluated by using LT-v9 program. The thermogravimetry analysis (TGA) was measured by TGA-50, Shimdzu thermogravimetric analyzer with a nitrogen flow of 25 ml min  1. Tensile strength measurements were made by using a Q800 (TA Instruments, USA) equipment. The specimens were cut to 1  3 cm2 pieces. The thickness of the membranes was measured by a screw micrometer. The stress–strain curve was obtained with an extension rate of 2 cm min  1. The cross-linking density was measured by equilibrium swelling method. When the swelling of vulcanized rubber (PDMS in this study) in certain solvent (heptane in this study) reached equilibrium, the diffusion rate of solvent molecules into the cross-linked network was equal to that of discharging out. On the basis of statistical theory of rubber elasticity, cross-linking density was available by the following Flory–Rehner equation [33]:

ne ¼ 

½lnð1n2 Þ þ n2 þ wn22  1=3

uðn2 n2 =2Þ

ð3Þ

where: ne was the cross-linking density of the rubber (mol/cm3); n2 was the volume fraction of rubber phase; u was the molar volume of solvent (cm3/mol); w was the interaction parameter between the rubber and the solvent (0.49 in the present study).

Permeation experiments were conducted on the P-28 flat membrane module (CM-Celfa AG Company, Switzerland). A scheme of the pervaporation set-up and the configurations of the membrane module were reported in our previous literature [34]. The permeation flux and enrichment factor of the nanocomposite membranes were assessed by pervaporation with n-octane/thiophene binary mixture. The feed solution was pumped into the membrane cell with the flow rate of 40 L/h. The temperature of feed flow was controlled at 30 1C. The sulfur content in the feed solution was maintained at 500 ppm. The permeate vapor was collected in liquid nitrogen traps. When the temperature was stable and amass-transfer equilibrium was established, the cold trap was exchanged every half an hour. The compositions of the feed and penetrating fluid were measured by using HP 6890 gas chromatography equipped with a FID detector and a PONA (paraffin, olefin, naphthene and aromatic) column. The temperatures for injector, detector (FID) and oven were set at 200, 250 and 80 1C, respectively. The pervaporation performances of the nanocomposite membranes were evaluated by three parameters, flux J, which was defined as J¼W/At, enrichment factor b, which was defined asPi ¼ J i ððlÞ=ðpio pil ÞÞ, and pervaporation separation index (PSI), which was defined aspi0 ¼ gLi0 xLi0 psat i0 , where W was the mass of penetrating fluid collected in time t, A was the membrane area, and oP and oF represented the weight fractions of thiophene in the penetrating fluid and the feed, respectively.

3. Results and discussion 3.1. Preparation and characterization of the PDMS-SiO2 nanocomposite membranes In the current study, biomimetic mineralization method with ammonia or neutral cysteamine as the inducer/catalyst was employed to enable the silica precipitation at the water/oil interface. As illustrated in Scheme 1, an approach combining polymerization of PDMS oligomers in the oil phase with silica precipitation in the reverse microemulsion was developed to prepare PDMS-SiO2 nanocomposite membranes. Ammonia was dissolved in water with a concentration of 0.5 M (pH 9.0). The cysteamine aqueous solution with a concentration of 0.5 M was prepared in 0.025 M Tris-HCl buffer, and the final pH value was adjusted to 7.0. PDMS oligomers and TEOS/TMOS were dissolved in alkane. Reverse microemulsion was formed by blending the above two solutions with Tween 80/Span 80 mixed surfactant under vigorous mechanical stirring. The inducer molecules were entrapped in the aqueous core of the microemulsion, which was dispersed in a nonpolar solvent and stabilized by the surfactant. It should be noted that TEOS or TMOS served as not only the silicon precursor but also the cross-linking agent for PDMS. Crosssectional morphology of the nanocomposite membranes probed

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281

Scheme 1. Fabrication of PDMS-SiO2 nanocomposite membranes.

Fig. 1. SEM images of the cross-section of (a) PDMS-NH3-(TMOS)16, (b) PDMS-Cys-(TMOS)16, (c) PDMS-NH3-(TEOS)16, and (d) PDMS-Cys-(TEOS)16 nanocomposite membranes. Scale bars: 3 mm.

by SEM (Fig. 1) demonstrated that spherical particles were homogeneously dispersed within the PDMS matrix. The existence of PDMS can remarkably increase the viscosity of the system, reduce the probability of collision between droplets, and thus substantially enhance the microemulsion stability [35]. In addition, the favorable compatibility between the PDMS matrix and the as-prepared SiO2 inorganic particles facilitated the homogeneous dispersion after mineralization [36]. Owing to the flexible molecular chains, PDMS could self-heal most macro-voids immediately after they were generated in the curing process. No macro-voids could be observed from the SEM cross-sectional images of the membranes. It also indicated that, compared with cysteamine, ammonia tended to generate silica particles of a smaller size. In addition, the silicone precursor TMOS tended to produce nano-sized silica particles, while TEOS promoted the formation of micron-sized slilica particles. To further elucidate the above results, the effect of the inducer and silicon precursor

types on the particle sizes evolving at the water/oil interface in dilute solution (without PDMS) were examined and the particle sizes were correlated to the silicon precursor concentration with the aid of DLS measurement, as shown in Fig. 2. On one hand, the ammonia-catalyzed and the cysteamine-catalyzed hydrolysis both occurred by a nucleophilic substitution mechanism [37,38], where the electronegative anion attacked the silicon atom. It was well known that the size and shape of the silica particles generated at the water/oil interface were strongly influenced by the pH value of the aqueous solution. It has been reported that the rate of hydrolysis of Si (OR)4 exhibited a minimum at pH 7.0 and increased exponentially at higher pH. In contrast, the rate of condensation exhibited a minimum at pH 2.0 and a maximum around pH 7.0, where the dissolution rate of SiO2 reached the highest [39]. In the current study, the pH of 0.5 M ammonia and cysteamine aqueous droplets was 9.0 and 7.0, respectively. The ammonia was favorable for the hydrolysis of Si (OR)4 and was

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unfavorable for the condensation of Si (OH)4. Consequently, the ammonia tended to generate silica particles of smaller size. On the other hand, under both acidic and basic conditions the hydrolysis rate of TMOS was considerably higher than that of TEOS due to the retarding effect of the bulkier ethoxide group [40]. As a result, TMOS as the silicon precursor tended to generate silica particles of much smaller size. 350 300

Particle Size (nm)

250 200

The next issue concerned the tailoring of the content of inorganic moiety within the nanocomposite membranes. Structural characterization of the membranes was carried out by means of FT-IR. Fig. 3 showed the infrared spectra of the PDMS control and PDMS-SiO2 nanocomposite membranes using different inducers and silicon precursors. The infrared spectra have been normalized to the band corresponding to the vibration of Si–O–Si bonds in SiO2 networks. In general, the absorption peak at 1090 cm  1 was associated with Si–O–Si asymmetric stretching vibration, whereas the absorption peak at 810 cm  1 at the peak was attributed to Si–O–Si symmetric stretching vibration. The spectra showed that the intensities of Si–O–Si peaks at 1090 and 811 cm  1 were notably enhanced with increasing silicon precursor concentration, indicating the higher weight fraction of SiO2 in the PDMS-SiO2 nanocomposite membranes. 3.2. Free volume property of the PDMS-SiO2 nanocomposite membranes

150 100 50 0 2

4

6

8

10

12

14

16

18

Silicon Precursor Concentration (mM)

1200

Reflectance (%)

Reflectance (%)

Fig. 2. Relationship between the particle sizes and the silicon precursor concentration using different inducers and silicon precursors. Emulsion sizes: ca. 80 nm (water/surfactant molar ratio ¼18.0).

Free volume property could be regarded as one of the most important properties of nanocomposite membranes, which directly determine their separation performance as well as mechanical strength [41–43]. In the current study, positron beams [44] were used to quantify the amount and size of vacancy-type free volume in the nanocomposite membranes. The correlation between free volume and its physico-mechanical properties was also explored. To understand the microstructure and its influence on the mechanical and pervaporative properties of the nanocomposite membranes, the free volume characteristics

1100

1000

900

800

700

1200

1100

Wave Number (cm )

900

800

700

800

700

Reflectanece (%)

Reflectance (%) 1200

1000

Wave Number (cm )

1100

1000

900

Wave Number (cm )

800

700

1200

1100

1000

900

Wave Number (cm )

Fig. 3. FT-IR spectra of the PDMS control membrane and the PDMS-SiO2 nanocomposite membranes: (a) PDMS-NH3-(TMOS)X, (b) PDMS-NH3-(TEOS)X, (c) PDMS-Cys(TEOS)X, and (d) PDMS-Cys-(TMOS)X.

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283

Table 1 Free volume characteristics and barrier properties of the PDMS control and the PDMS-SiO2 nanocomposite membranes. Entry

Samples

t3/

r3 (nm)

I3 (%)

ns 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

PDMS-(TMOS)2 PDMS-NH3-(TMOS)8 PDMS-NH3-(TMOS)16 PDMS-NH3-(TMOS)24 PDMS-NH3-(TMOS)40 PDMS-Cys-(TMOS)8 PDMS-Cys-(TMOS)16 PDMS-Cys-(TMOS)24 PDMS-Cys-(TMOS)40 PDMS-(TEOS)2 PDMS-NH3-(TEOS)8 PDMS-NH3-(TEOS)16 PDMS-NH3-(TEOS)24 PDMS-NH3-(TEOS)40 PDMS-Cys-(TEOS)8 PDMS-Cys-(TEOS)16 PDMS-Cys-(TEOS)24 PDMS-Cys-(TEOS)40

0.94 1.34 1.82 1.75 1.41 0.96 1.09 1.01 1.21 1.91 1.91 2.03 2.05 1.97 1.43 1.86 1.84 1.21

t4/

r4 (nm)

I4 (%)

FFV(%)

Permeation flux (kg/m2h)

Enrichment factor

PSI

0.368 0.393 0.417 0.405 0.394 0.377 0.377 0.381 0.381 0.386 0.41 0.431 0.434 0.429 0.389 0.415 0.415 0.381

18.9 22.7 21.3 22.2 9.6 20.7 22.8 21.6 19.1 15.6 17.6 15.2 13.6 15.3 19.6 17.4 17.3 19.1

4.0 6.0 7.2 6.7 2.8 4.8 5.3 5.1 4.6 4.6 5.8 6.2 5.9 6.1 5.1 6.0 5.9 4.6

1.82 4.52 7.36 5.89 3.58 6.42 5.6 4.41 3.33 1.91 3.36 4.35 3.12 2.92 2.76 2.25 2.49 2.03

5.96 4.11 4.98 4.01 3.08 2.82 4.09 3.09 2.98 5.32 4.02 3.69 3.15 2.61 4.7 4.33 4.01 3.29

9.03 14.06 29.29 17.73 7.28 11.68 17.3 9.22 6.44 8.25 10.15 11.7 6.7 4.59 10.21 7.49 7.49 4.53

ns 0.155 0.214 0.268 0.261 0.223 0.158 0.18 0.167 0.197 0.276 0.276 0.288 0.289 0.282 0.226 0.272 0.27 0.197

4.5 5.8 9.4 7.4 7 8.1 5.6 6.9 5.6 9.7 8.3 11.5 12.4 11 5.2 9.5 9 5.6

3.08 3.47 3.88 3.67 3.49 3.22 3.22 3.28 3.28 3.36 3.76 4.14 4.20 4.10 3.41 3.85 3.85 3.28

were probed using PALS, a unique tool used for direct measurement of the nanometer sized free volume cavities and their relative number densities. Table 1 showed that the PDMS(TMOS)2 control membrane (entry 1) possessed average free volume cavity radius of the r3 and r4 about 0.155 and 0.368 nm, assigning to the polymer network pores and aggregate pores [31,45]. The network pores were the small cavities between polymer chains constituting the polymer aggregate, whereas the aggregate pores were the large cavities surrounding the polymer aggregates. The PALS results showed that there were two types of pores existing in the membrane, the network pores with a radius of 0.155–0.289 nm and the aggregate pores with a radius of 0.368–0.434 nm. It is generally believed that adding impermeable filler particles to a polymer leads to a reduction in molecular transport, thus enhancing the barrier property of the membrane. In the current study, however, it was observed that filler particles served as ‘‘nanospacers’’ [41] to prevent polymer chains from packing tightly. After embedding the SiO2 nanoparticles (entries 2 and 3), the r3 and r4 were enlarged, arising from the disruption of the PDMS polymer chain packing by the adjacent silica nanoparticles. Consequently, fractional free volume (FFV) increased from 4.01% for the PDMS-(TMOS)2 control membrane to 7.24% for the PDMS-NH3-(TMOS)16 nanocomposite membrane. If the silica weight fraction was further increased (entries 2–5), the FFV value began to decrease. Sol–gel reaction using basic catalyst generally favored the formation of dense silica [46]. Thus, when excessive silica nanoparticles were incorporated, the fractional free volume decreased accordingly. FFV values of entries 2–5 were slightly higher than that of entries 6–9. Table 1 also showed that the FFV of PDMS-(TEOS)2 control membrane (entry 10) and most of the corresponding nanocomposite membranes (entries 11–18) were lower than that of entries 1–9, which could be attributed to better dispersion as well as the smaller size of the particles in PDMS-NH3-(TMOS)x, offering larger interfacial area available for polymer–inorganic interactions. 3.3. Mechanical and thermal properties of the PDMS-SiO2 nanocomposite membranes It is well known that pure PDMS generally has relatively poor mechanical properties. The Si–O bond length is reported to be ˚ which is significantly longer than that of the C–C bond 1.64 A, ˚ Also, the Si–O–Si bond angle is approximately 1431, (1.53 A). which is much larger than the usual tetrahedral value (109.51).

In addition, the torsional potential of Si–O bonds is significantly lower than that of C–C bonds. Therefore, PDMS has to be reinforced to serve for better and wider applications. The mechanical properties of PDMS control membrane and PDMSSiO2 nanocomposite membranes were presented in Fig. 4. The stress–strain curves of PDMS control membrane and PDMS-SiO2 nanocomposite membranes (Fig. 4a) showed typical elastic behavior. At the same strains, the stress of PDMS-SiO2 nanocomposite membranes was remarkably enhanced comparing with PDMS control membrane. The enhanced modulus was mainly ascribed to the strong interaction between silica and PDMS via the hydrogen bonds between the silanol groups on the silica surface and the oxygen atoms on the polymer chains [36]. As revealed in Fig. 4(b), the highest Young’s modulus of PDMS-SiO2 was from those nanocomposite membranes fabricated using ammonia and TMOS as inducer and silicon precursor. Typically, the strong reinforcement was often obtained with particle sizes smaller than 100 nm while the weak reinforcement was often obtained with particle sizes smaller than 1000 nm [47]. As shown in Fig. 1, TMOS silicon precursors tended to produce silica particles with particle sizes smaller than 500 nm. The better dispersion as well as the smaller size of the particles generally offered larger interfacial area available for polymer–inorganic interactions. Thus the Young’s modulus of PDMS-NH3-(TMOS)x were higher than that of PDMS-Cys-(TEOS)x. Moreover, the nanocomposite membrane displayed a favorable mechanical property with Young’s modulus of around 0.19 MPa (6.6-fold larger than that of PDMS control membrane) on the condition that the molar ratio of TMOS to PDMS reached 10.0 with NH3 as inducer. In addition to the enhancement in the Young’s modulus, another feature of inorganic filler reinforcement was reflected by the swelling reduction of PDMS-SiO2 nanocomposite materials in organic solvents. Fig. 5 demonstrated that the cross-linking density in PDMS-SiO2 nanocomposite membranes, as a function of silicon precursor concentration, was notably increased comparing with PDMS control membrane. The SiO2 particles actually endowed a number of additional cross-linking sites, which in turn notably increased the cross-linking density of the nanocomposite membranes. Moreover, in practical applications, the nanocomposite membranes should have enough thermal stability. The thermal property of PDMS-SiO2 nanocomposite membranes was probed by TGA. As shown in Fig. 6, the dm/dT differential result was plotted as a function of temperature. The temperature corresponding to

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0.20

0.7

Young's Modulus (MPa)

0.6

Stress (MPa)

0.5 0.4 0.3 0.2

0.15

0.10

0.05

0.1 0.0 0

200

400

-2

600

0

Strain (%)

2

4

6

8

10

12

14

16

18

Silicon Precursor Concentration (mM)

Fig. 4. (a) Stress–strain curves and (b) Young’s modulus of the PDMS control membrane and the PDMS-SiO2 nanocomposite membranes.

1.6x10 1.4x10 1.2x10 1.0x10 8.0x10 6.0x10

7

0.20

Fractional free volume Young's modulus

6 0.15 5 0.10 4 0.05

3

2 -2

0

2

4

6

8

10

12

14

16

18

Silicon Precursor Concentration (mM)

dm/dT

Fig. 5. Cross-linking density of the PDMS control membrane and the PDMS-SiO2 nanocomposite membranes.

200

300

400

500

600

700

800

Temperature (°C) Fig. 6. dm/dT as a function of temperature for the PDMS control membrane and the PDMS-SiO2 nanocomposite membranes.

the peak of the curve (Td) was the temperature where maximum degradation rate occurred, which could be used to assess the thermal stability of the materials. The Td of PDMS-NH3-(TMOS)16 nanocomposite membranes (585 1C) was increased comparing with PDMS-(TMOS)2 control membrane (525 1C). The Td of PDMS-NH3-(TEOS)16 nanocomposite membranes (562 1C) was

Young's Modulus (MPa)

Fractional Free Volume (%)

Cross-linking Density (mol /cm )

1.8x10

100

0.25

8

2.0x10

0.00 -2

0

2

4

6

8

10

12

14

16

18

Silicon Precursor Concentration (mM) Fig. 7. Relationship between the free volume properties and the mechanical strength of the PDMS-NH3-(TMOS)x nanocomposite membranes.

also increased comparing with PDMS-(TEOS)2 control membrane (520 1C). The incorporation of inorganic particles improved the thermal stability of PDMS. Nanocomposite membranes with high mechanical strength and controllable permeability were always desired in view of long-term utilization. Therefore, it was crucial to correlate the free volume property and the mechanical strength of the PDMSSiO2 nanocomposite membranes. Taking PDMS-NH3-(TMOS)x as an example, the variation in Young’s modulus and fractional free volume of the PDMS control and PDMS-SiO2 nanocomposite membranes was plotted in Fig. 7. The PALS results indicated that the Young’s modulus had a notable dependence on the free volume properties assuming the even dispersion of silica nanoparticles in PDMS matrix. Polymeric materials with higher FFV generally have lower tensile strength and vice versa [42,43]. With regard to the current PDMS-SiO2 nanocomposite membranes, however, along with the increasing dosage of silicon precursor, both tensile strength and fractional free volume increased to a peak where the concentration of TMOS was 10.5 mM. This result was possibly due to the presence of rigid silica particles and the strong interactions between the silica and PDMS polymer chains. When the concentration of TMOS increased from 10.5 to 17.5 mM, the tensile strength was almost constant and the FFV was reduced, probably due to the accumulative defects arising from polymer–inorganic interfaces. Therefore, the nanocomposite membranes in the current study displayed facile controllability over the free volume properties as well as mechanical strength.

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3.4. Pervaporation performance of the PDMS-SiO2 nanocomposite membranes Rubbery PDMS with uniform nanoscale cavities had great potential in the separation of small molecules bearing close physicochemical properties based on solution–diffusion mechanism. Herein, the permeation and selectivity of the PDMS control membrane and PDMS-SiO2 nanocomposite membranes were evaluated using binary mixture (n-octane/thiophene) as model separation system. As shown in Table 1, the permeation flux in PDMS-(TMOS)2 and PDMS-(TEOS)2 control membranes were around 1.82 and 1.91 kg/(m2h), whereas the permeation flux in the PDMS-NH3-(TMOS)16 and PDMS-NH3-(TEOS)16 nanocomposite membranes was increased to 7.36 and 4.35 kg/(m2h). Permeation flux increase of PDMS-SiO2 nanocomposite membranes could be interpreted by both the size and the number (intensity) of the two types of free volume pores: (i) embedding SiO2 into PDMS matrix enhanced the size of both network pores and aggregate pores; therefore, penetrant molecules were easier to permeate compared with pure PDMS membrane; (ii) the number of the two types of pores was increased with the concentration of silicon precursors, offering more diffusion paths for the penetrant molecules. The selectivity of PDMS-SiO2 nanocomposite membranes towards thiophene was only slightly decreased compared to PDMS control membrane. The radiuses of thiophene and n-octane molecules were about 0.265 and 0.315 nm [48–50]. Generally, smaller penetrant molecules (thiophene) diffused faster than larger penetrant molecules (n-octane) due to a high fraction of free volume voids available for smaller penetrant molecules. However, as shown in Table 1, the incorporation of SiO2 into PDMS matrix enhanced the size of both network pores and aggregate pores, therefore, deteriorating the rejection effect PDMS-SiO2 nanocomposite membranes for larger penetrant molecules compared with PDMS control membrane. As a result, the selectivity was decreased to some extent. The effects of operation conditions on the separation performance were investigated. According to the data in Table 1, PDMSNH3-(TMOS)16 membrane displayed the highest separation performance with permeation flux of 7.36 kg/(m2h) and an enrichment factor of 4.98. Therefore, it was chosen as the membrane to reveal the effects of separation temperatures feed concentration and feed flow rate on the separation performance. Fig. 8(a) presented the pervaporation performance of the PDMS-NH3(TMOS)16 membrane at temperatures ranging from 30 1C to 60 1C indicating that total permeation flux increased with feed temperature. In this study, the intrinsic membrane separation coefficients (permeability and selectivity) were introduced to analyze the influencing factors on pervaporation performance. The permeability (Pi) was defined as Pi ¼ Ji

l pio pil

ð5Þ

where l was the membrane thickness (m), pio and pil were the partial pressures (kPa) of component i on the feed side and the downstream side, respectively. pio could be expressed as pi0 ¼ gLi0 xLi0 psat i0 L i0

ð6Þ

where g was the activity coefficient of component i in the feed liquid analogously calculated by Aspen Plus software and xLi0 was the mole fraction of the component i in the feed liquid psat i0 was the pure component i feed vapor pressure (kPa). The variation of permeability of n-octane and thiophene was replotted in terms of membrane permeabilities in Fig. 8(b). The permeability of n-octane decreased notably from 2.43 g m  1h  1k Pa  1 to 1.55 g m  1h  1kPa  1 when the operation temperature increased from 30 1C to 60 1C, whereas the permeability of thiophene

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changed slightly in the range of 0.63–0.74 g m  1h  1kPa  1. Increasing the temperature led to an increase in the flexibility of the polymer chains, leading to more uniform free volume pore size distribution and the reduced concentration of non-selective pore. In addition, the saturated vapor pressure of permeating components at the upstream side increased, while the vapor pressure at the permeate side was hardly affected. Therefore, total permeation flux increased with feed temperature. The selectivity was defined as the ratio of the permeabilities of components i (thiophene) and j (n-octane) through the membrane: @ij ¼

Pi Pj

ð7Þ

As shown in Fig. 8(b), the selectivity increased from 0.26 to 0.46 when the operation temperature increased from 30 1C to 60 1C. Increasing the temperature possibly led to an increase in the concentration of selective pores, which resulted in the increase of the selectivity. The effect of feed sulfur concentration on permeation was shown in Fig. 8(c). Permeation flux increased while enrichment factor decreased with the increase of sulfur content in the feed which was in good accordance with the results of normalized analysis indicated in Fig. 8(d). The increase of sulfur content in the feed led to the increase of activity of thiophene, which was advantageous to the dissolution of thiophene in the membrane. Therefore, the increase in thiophene concentration at the upstream side endowed a continuous increase in the permeation flux. When the sulfur content in feed was increased, more pronounced swelling of the membrane might occur due to the affinity of sulfur towards the membrane, and consequently selectivity towards sulfur decreased with increasing sulfur content in feed. As shown in Fig. 8(e), both the total flux and enrichment factor increased slightly with higher feed flow rate. With the increase of feed flow rate, the thickness of boundary layer was decreased. Therefore, mass transfer resistance of boundary layer on the upstream decreased, which caused an increase in permeation flux. The permeation flux of thiophene molecules increased more remarkably than that of n-octane molecules, which increased the enrichment factor consequently.

4. Conclusions This study tentatively proposed a novel and facile method of one-step fabrication of oleophilic polymer based polymer– inorganic nanocomposite membranes for the pervaporative removal of organosulfur compounds from model gasoline. Through the controlled biomimetic mineralization processes in confined space, the inorganic particles could be in-situ formed and homogeneously embedded into oleophilic polymer bulk matrix, rendering the nanocomposite membranes with tunable free volume properties, superior mechanical strength and separation performance. It was observed that silica-precipitating inducers and silicon precursors with higher reactivities were prone to the formation of smaller silica particles and more favorable for the enhancement of mechanical strength and pervaporation performance of the nanocomposite membranes. It was also observed that the pervaporation performance and mechanical strength were strongly dependent on the free volume properties of the nanocomposite membranes. The PDMS-NH3-(TMOS)16 membrane displayed an optimum desulfurization performance with permeation flux of 7.36 kg/(m2h) (303.9% more than that of PDMS control membrane) and the enrichment factor of 4.98 towards thiophene (slight lower than that of PDMS control membrane). It is expected that the current study will devote a novel method for the rational design and facile fabrication of

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J 

J 

J 

Fig. 8. Effects of (a) operating temperature, (c) sulfur concentration of the feed solution and (e) feed flow rate on the pervaporation performance of the PDMS-NH3(TMOS)16 nanocomposite membrane; effects of (b) operating temperature, (d) sulfur concentration of the feed solution and (f) feed flow rate on the permeability and selectivity of the PDMS-NH3-(TMOS)16 nanocomposite membrane.

oleophilic polymer based polymer–inorganic nanocomposite membranes to better meet the diverse application requirements.

Natural Science Foundation (no. 10JCZDJC22600), State Key Laboratory of Materials-Oriented Chemical Engineering of Nanjing University of Technology (no. KL09-3), the Program of Introducing Talents of Discipline to Universities (no. B06006).

Acknowledgments References We thank the financial support from the National Basic Research Program of China (no. 2009CB623404), National Science Fund for Distinguished Young Scholars (no. 21125627), Tianjin

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