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SBA-15 hybrid nanocomposite as highly efficient humidity sensor
Accepted Manuscript Title: In-situ synthesis of SnO2 /SBA-15 hybrid nanocomposite as highly efficient humidity sensor Author: Vijay K. Tomer Surender Duhan PII: DOI: Reference:
S0925-4005(15)00227-0 http://dx.doi.org/doi:10.1016/j.snb.2015.02.054 SNB 18117
To appear in:
Sensors and Actuators B
Received date: Revised date: Accepted date:
4-12-2014 30-1-2015 7-2-2015
Please cite this article as: V.K. Tomer, S. Duhan, In-situ synthesis of SnO2 /SBA-15 hybrid nanocomposite as highly efficient humidity sensor, Sensors and Actuators B: Chemical (2015), http://dx.doi.org/10.1016/j.snb.2015.02.054 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Highlights 1. SnO2/SBA-15 mesoporous nanocomposite was synthesized using hydrothermal method.
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2. SnO2 was loaded in SBA-15 using in-situ and wet impregnation process. 3. The prepared nanocomposites performance towards change in relative humidity (RH) was
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observed in 11-98 %RH range.
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4. The nanocomposite synthesized using in-situ process shows comparatively superior RH
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sensing characteristics in complete RH range.
5. A change of 5.5 orders in impedance magnitude, negligible hysteresis (1.5%) with fast
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response (15 sec) and recovery time (21 sec) was observed in 11-98 %RH range.
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In-situ synthesis of SnO2/SBA-15 hybrid nanocomposite as highly efficient humidity sensor Vijay K. Tomer, Surender Duhan* Nanomaterials Research Laboratory Department of Materials Science & Nanotechnology
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D.C.R. University of Science & Technology, Murthal (Sonepat) Haryana, 131039 (INDIA)
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Abstract
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We report a hydrothermally derived novel scheme to synthesize SnO2 supported mesoporous SBA-15 nanocomposite for relative humidity (RH) sensing at room temperature. Two loading
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procedures of SnO2 nanoparticles in SBA-15 were followed: in-situ and wet impregnation, in order to reveal information regarding the effect of synthesis strategies on the RH sensing
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response of the nanocomposite. The obtained nanocomposites were characterized using a combination of X-ray diffraction (XRD), N2 adsorption-desorption isotherms, High resolution
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transmission electron microscope (HRTEM), Field emission scanning electron microscope
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(FESEM) and Energy dispersive X-ray (EDX) spectroscopy. The humidity sensing properties of the presented nanocomposite sensor, such as linearity, response–recovery characteristics, hysteresis and stability, were investigated by exposing sensors to wide range of 11–98 %RH at room temperature. Due to uniform and homogeneous dispersion of SnO2 nanoparticles in the pore channels of SBA-15, the nanocomposite sensor synthesized using in-situ process not only exhibit superior sensing response towards change in %RH but also posses swift response– recovery time, good repeatability, negligible hysteresis and stability, highlighting the unique advantages of the synthesis procedures for fabrication of sensor materials. The complex impedance spectra of the sensor at different RHs were analyzed to explore the humidity-sensing mechanism. This study demonstrates that the SnO2/SBA-15 nanocomposite prepared by in-situ method can be used as the humidity-sensing material for the fabrication of humidity sensors. 2
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Keywords: SnO2/SBA-15; in-situ; hydrothermal; relative humidity. * Corresponding author E-mail: [email protected]
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Tel.: +91- 9813170944.
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1. Introduction Moisture contained in the atmosphere is a highly variable and unpredictable quantity
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which frequently changes in line with geographical and topographical condition. It is important to keep an eye on and command the profile involving water vapors present in the environment
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for human ease and comfort and also numerous industrial processes [1-4]. During the last
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decade, limits have been shoved additionally by researchers globally with regard to fabricating and designing efficient relative humidity sensors based on mesoporous materials [5-7]. The
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unique properties of mesoporous materials like high surface area and interconnected pore channels provide easier adsorption and facile transportation of water molecules across their
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surfaces [8-9]. Mesoporous silica SBA-15 is particularly important material among its class for its high surface area, pore volume, excellent thermal stability, interconnected with tunable pore
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channels [10] and is particularly obtaining exclusive attention in applications like photocatalysis,
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sensing, drug delivery and nanomaterials fabrication [11-14]. SBA-15, whilst functioning as a host matrix has been keenly investigated to accommodate various metal and metal oxides oxide dopants for a variety of novel applications [15-17]. Moreover, the uniform meso-ordered pore channels of SBA-15 can extensively control the particle size of dopant while enabling it to effectively prevent debris from agglomeration [18]. Stannic oxide (SnO2) is an important n-type semiconductor material for humidity detection due to its chemical sensitivity to oxygen and water vapor in air, high chemical stability, non-toxicity and low cost [19-20]. Water is adsorbed on SnO2 surface in the molecular and hydroxyl form and conduct electronically at room temperature [21]. Kuang et. al has synthesized RH sensors based on single SnO2 nanowire [22]. They have obtained an average response time of 145 s and recovery time of 40 s. Similarly, Parthibavarman et. al. have synthesized spherical 4
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SnO2 nanostructures and obtained response time and recovery time of 32s and 25 s respectively [23]. Considering the dependability of RH sensing properties on surface area of SnO2, there remains a consistent effort in increasing its surface area so as to create more active sites for rapid
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adsorption of water molecules to improve the RH sensing characteristics [24-25]. With the mesoporous nanocomposite based on SnO2/SBA-15, we aim at better sensitivity, quick
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response/recovery times, wide operating %RH range, low working temperature range and
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improved stability than those of the RH sensors made out of only pure SBA-15 and SnO2 materials.
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In the recent times, SBA-15 assisted SnO2 mesoporous nanocomposite has been synthesized by researchers using incipient wet impregnation process. This is a two step
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procedure wherein SBA-15 is synthesized using conventional hydrothermal method followed by soaking it in solvent containing SnO2 precursor [14, 26-27]. Previous studies reveal that in wet
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impregnation method, the pores channels of SBA-15 gets partially or completely chocked
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resulting in agglomeration of guest nanoparticles on the pore openings and surface of SBA-15 which causes the nanocomposite possessing poor pore characteristics [28-29]. To overcome this loss in mesoporous efficiency, we propose a simple, economical and energy saving in-situ loading method wherein the SnO2 precursor salt is introduced in the host matrix prior to the silica hydrolysis process. In comparison to wet impregnation process, the SnO2/SBA-15 nanocomposite utilizing in-situ loading procedure exhibit better mesoporous characteristics. The response of the as synthesized SnO2/SBA-15 nanocomposites towards RH was measured in 1198% range at room temperature. The sample synthesized following in-situ loading approach exhibit comparatively better RH sensing response and a change of 5.5 orders in magnitude was recorded in 11-98 %RH range at 25 °C. Moreover, the sensor shows excellent linearity,
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negligible hysteresis (1.5 %), quick response time (15 sec), rapid recovery time (21 sec), stability and broad operating range (11-98 %RH). These excellent sensing characteristics make the SnO2/SBA-15 nanocomposite prepared by in-situ method a good candidate for the fabrication of
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high performance humidity sensors. 2. Experimental
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2.1 Materials
Tetraethoxy orthosilicate [(C2H5O)4Si, TEOS, Sigma Aldrich], Pluronic P123 [Ethylene
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Oxide-Propylene Oxide-Ethylene Oxide, (EO20PO70EO20), Mw = 5800, Sigma Aldrich], Tin (II)
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chloride [SnCl2•2H2O, Merck], Sodium Dodecyl Sulphate [(CH3(CH2)11OSO3Na), Merck], Sodium Hydroxide (NaOH, Fisher Scientific), Ethanol (Fisher Scientific) and HCl (35%, Fisher
2.2 Material Preparation
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Scientific) were used as received. Double distilled water was used throughout the experiments.
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Synthesis of SBA-15: The mesoporous SBA-15 was prepared according to previous
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method [18]. 2 g P123 was dissolved in 70 ml distilled water at 40 °C with vigorous stirring (1000 rpm), followed by addition of 10 ml HCl (2M). After obtaining a clear transparent solution for 3 h of continuous stirring, 4.5 g of TEOS was added and resultant solution was kept under stirring for 24 h at 40 °C. The dried white product thus obtained was put for hydrothermal treatment in a Teflon lined stainless steel autoclave and treated at 100 °C for 24 hrs. After cooling down to room temperature, the solid products were recovered, filtered, washed and dried at 70 °C. The powder mesoporous silica SBA-15 was obtained by calcination of the products at 600 °C (heating rate of 1 °C/min) for 6 hrs in air to remove organic templates. Synthesis of SnO2/SBA-15(I): For loading of 5 wt% SnO2 in SBA-15 using in-situ method, 0.1g of Tin chloride salt solution was added in aqueous miceller solution of P123. The
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mixture was stirred for 3 h followed by addition of TEOS and kept under stirring for 24 h and further following the same route as used for pure SBA-15. Synthesis of SnO2/SBA-15(W): In order to prepare 5 wt% SnO2 loaded SBA-15
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nanocomposites by wet impregnation method, aqueous solution of 0.1 g SnCl2•2H2O was prepared followed by addition of 1 g SBA-15 to the solution under stirring. The samples were
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left overnight to dry and were calcined at 600 °C to obtain the mesoporous nanocomposite.
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Synthesis of SnO2: 2.7 g of SnCl2•2H2O was dissolved in 40 ml water followed by addition of 50 ml NaOH (1M) solution to obtain clear transparent solution. Then 40 ml aqueous
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solution of 0.024g SDS was added to the above solution with addition of 15 ml ethanol. Obtained solution was then treated hydrothermally in a Teflon-lined autoclave at 170 °C for 24 h. The
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white precipitates were recovered, washed with distilled water and put to dry at 80°C overnight. Finally, the white powder was calcined at 600 °Ϲ for 4 h to obtain pure SnO2 material. For the
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ease of analysis, all the four samples SBA-15, SnO2/SBA-15(I), SnO2/SBA-15(W) and SnO2
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were denoted as S1, S2, S3 and S4 respectively. 2.3 Fabrication of humidity sensors
For fabrication of sensors, the materials (S1, S2, S3 and S4) were coated on ceramic rod of 10 mm length and 3 mm diameter with metallic lead end caps. The schematic diagram of fabricated sensor is shown in Fig. 1. Prior to use, the ceramic rod was cleaned by an ultrasonic treatment in acetone, then rinsed thoroughly with double-distilled water and dried in vacuum. The samples were ground and mixed with ethanol to form a paste and coated on the ceramic rod using drop casting method. The coated ceramic rods were dried at 80 °C for 12 h and used as sensing elements to evaluate the humidity sensing characteristics. 2.4 Humidity sensor measurement
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The different RH levels were generated by the different saturated salt solutions in air tight closed glass chambers at room temperature (25 °C). The six different standard saturated aqueous salt solutions of LiCl, MgCl2•6H2O, MgNO3•4H2O, NaCl, KCl and K2SO4 which yielded 11%,
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33%, 54%, 75%, 84% and 98% relative humidity, respectively were used to act as humidity source [30]. The saturated salt solutions were placed overnight in the chambers at room
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temperature to ensure that the air in the chamber reached to equilibrium states. These RH levels
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were monitored by a standard hygrometer. The material coated ceramic rod was placed successively into the chambers with different RH levels at room temperature and the impedance
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of the sensor was measured as a function of RH at 25 °C (± 1°C) using a simple two-probe configuration with a LCR Meter. The voltage applied was AC 1 V and the frequency was varied
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from 50 Hz to 10 kHz. The characteristics RH response curves were obtained by exposing the sensor in the closed chambers with different %RH environment for the uptake of water
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molecules until the impedance of the sensing material reached a stable value. The exposure of
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sensing element to laboratory atmosphere during switching of sensor material between different chambers makes it almost impossible to measure the response transients precisely. However, during the experiments, we have tried to complete the chamber change process as quick as possible, which could be done less than 1 s. 2.5 Characterization of materials
The sensor materials were characterized using various techniques to identify the structural, morphological and physicochemical properties. The Low angle and Wide angle XRD information was obtained on a Bruker D8 advance diffractometer using CuKα monochromatic radiation (λ=1.5418 Å) 40 kV and 40 mA with a step size of 0.02°. The N2 adsorption-desorption isotherms were carried out using Micrometrices (Tristar 3000) at 77K. Before the measurements,
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the samples were degassed at 300 °C for 6 h. The BET and BJH method were used to determine the specific surface area and pore characteristics of the materials respectively [31, 32]. The mesoporous structure of the sensor materials was further investigated using High-Resolution
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Transmission Electron Microscopy (HR-TEM) on TECNAI G20 electron microscope at an accelerating voltage of 200 kV. Morphology of the samples along with its elemental composition
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was characterized by Field emission scanning electron microscope equipped with an Energy-
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dispersive X-Ray spectroscopy (SEM-EDX, FEI QUANTA 200F) at an acceleration voltage of 10-15 kV. The samples for analysis were prepared by distributing the powder samples on a two
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sided leading sticky tape. 3. Results and Discussions
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3.1 Characterization of samples
The Low angle XRD spectra for SBA-15 (S1), SnO2/SBA-15 nanocomposites (S2, S3)
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and pure SnO2 (S4) is shown in Fig. 2. For S1, S2 and S3, almost similar LAXRD patterns are
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noted. Three well resolved peaks in the range of 2θ = 0.5° – 3° for nanocomposites S2 and S3 were observed similar to that for S1 which demonstrates that SnO2 loaded SBA-15 possesses meso-ordered, hexagonal structures [10, 33]. For S1, these peaks are indexed to the (1 0 0) (d100= 107 Å), (1 1 0) (d110= 58.28 Å) and (2 0 0) (d200= 51.97 Å) reflections of the 2D hexagonal space group p6mm, which is comparable to those described by Zhao [10]. For pure SnO2 (S4, inset), the peak at 2θ = 0.8° indicates the disordered mesoporous structure. The physicochemical properties of SBA-15 and SnO2/SBA-15 nanocomposites as determined by LA-XRD results are summarized in Table 1. Fig. 3 shows the wide angle XRD pattern (2θ = 15° - 70°) for S1-S4. For S4, well resolved SnO2 peaks are obtained at 2θ = 26.9°, 34.2°, 38.2°, 52.3°, 54.9°, 57.8°, 62.2°, 64.6°
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and 66.2° corresponding to (110), (101), (200), (211), (220), (002), (310), (112) and (301) planes of SnO2 (JCPDS no. 03-1116) respectively. A broad peak centered at 2θ = 22° corresponding to the pristine material is observed for S1, S2 and S3. Small peaks of SnO2 are observed for S2 and
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S3 confirming that SnO2 has been loaded in the channels of SBA-15 matrix. The N2 adsorption-desorption isotherm for S1-S3 is shown in Fig. 4(a). A sharp inflection
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peak was observed which can be attributed to type IV characteristic curve as deduced from
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IUPAC classification of sorption isotherms for mesoporous materials [34]. Both the nanocomposite sample S2 and S3 retains their mesoporous structure even after loading of SnO2
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nanoparticles. However, the surface area exhibited by S2 is comparatively higher than S3. This was consistent with the results obtained from Low angle XRD. The hysteresis loop of S1-S3
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resembles the H1 type curve which corresponds to uniform cylindrical geometry exhibited by mesoporous solids [35]. The information regarding pore size, volume and wall thickness as
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determined from BET isotherms is listed in Table 1. The BJH pore size distribution curves
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shown in Fig. 4(b) determine the average pore size of the samples. It can be seen that with the loading of SnO2 nanoparticles in SBA-15 (S2 and S3), the pore size get reduced due to the presence of SnO2 nanoparticles in the SBA-15 channels. However, the thickness of pore walls for the two nanocomposites was found to be higher than the pure SBA-15 due to pore filling effect illustrating that the SnO2 nanoparticles have been confined inside the channels of SBA-15. The pore morphology of S1 and presence of SnO2 nanoparticles inside mesoporous silica framework in hybrid nanocomposite S2 and S3 were investigated by HRTEM. Fig. 5 shows that all the samples represent a long range pore order of 2-D (p6mm) mesoporous channels which confirms the mesoporosity of the obtained materials [10]. As estimated from the HRTEM images, the separation between two sequential centers of hexagonal pores for pure SBA-15 is
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~12.48 nm. The average pore diameter and wall thickness are around 8.7 nm and 3.78 nm, respectively which is quite consistent with the results acquired from BET surface area analysis and XRD. The long range order of channels does not change by virtue of SnO2 stacking in SBA-
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15 however the dimensions are shrunk by the interaction of the nanoparticles with the host SBA15. It is supported by the HRTEM results that SnO2 loaded SBA-15 has high level of
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crystallinity and phase purity. Also the hexagonal mesostructure of SBA-15 remains intact after
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the incorporation of SnO2 nanoparticles. Fig 5(b) shows nanocomposite S2 prepared by in-situ method of loading. Exceedingly scattered SnO2 nanoparticles were observed uniformly in the
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pore channels of SBA-15 framework. In the in-situ method of synthesis, TEOS and SnCl2•2H2O were simultaneously added to the reaction system and mixed evenly by continuous stirring over a
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long period of time. So we considered that the formed SnO2 nanoparticles are mixed evenly with SBA-15 matrix. Moreover, during the calcination process, the SnO2 nanoparticles move inside
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the channels of SBA-15 [36]. Fig 5(c) corresponds to nanocomposite S3 prepared by wet
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impregnation method. As seen clearly, some pore channels of SBA-15 were chocked in the process of nanocomposite formation. Due to these blocked pore channels, S3 possess lower mesoporous characteristics than S2.
The SEM images of sample S2 and S3 are shown in Fig. 6(a-b) which shows that both the nanocomposite samples have similar wheat like morphologies of packed aggregates of 0.5-1 µm sized rod-like structures wherein the major unit of a single rod consists of small domains. This kind of morphology has been demonstrated to have long range parallel channels with the 2-D hexagonal mesostructure [10]. The EDX spectra of nanocomposite sample S2 and S3 are shown in inset of Fig. 6(a) and Fig. 6(b) respectively where no other elements were detected except O, Si and Sn, thus confirming the purity of samples. The comparatively higher wt% of ‘Sn’ content
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in S2 than S3 arise from the fact that wet impregnation method causes some SnO2 nanoparticles to agglomerate on the pore opening of SBA-15 thus causing a blockage of pore channels for successive loading of SnO2 nanoparticles while in case of in-situ method, the uniform dispersion
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of SnO2 nanoparticles in SBA-15 happens because the precursor salt of SnO2 was introduced into the reaction system simultaneously with silica precursor. The results obtained from EDX
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analysis (Table-1) show that for 5 wt% of SnO2 incorporated into SBA-15, approximately 70.6%
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and 61.2% of the total weight of SnO2 was loaded in the channels of SBA-15 for nanocomposites sample S2 and S3 respectively.
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3.2 Humidity sensing properties
Fig. 7 shows the RH dependent impedance response of the as synthesized samples at
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room temperature in the 11- 98 %RH range. As can be seen, at low %RH, all samples exhibit very high impedance, however, as the %RH increases, a dramatic decrease in impedance was
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observed. The samples consisting of pure SBA-15 and SnO2 exhibits a change of 2.5 and 3.5
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orders of magnitude change in impedance in 11-98% RH range. The poor RH response of SBA15 is attributed to its high intrinsic impedance caused by decrease of –OH groups during calcination process. However, for nanocomposites S2 and S3, a drop of 5.5 and 4.5 orders in impedance magnitude respectively was observed in complete %RH range indicating improved humidity sensing response of the hybrid nanocomposite than pure SBA-15 and SnO2 materials. This reveals that the loading of SnO2 nanoparticles has directly contributes in enhancement of conductivity and improving the linearity of the synthesized nanocomposites. Among the nanocomposites S2 and S3, in spite of same loading concentration of SnO2 in SBA-15, S2 shows comparatively enhanced sensing response towards change in %RH due to two reasons: (a) higher wt% loading of SnO2 in nanocomposite and (b) homogeneous and uniform dispersion of SnO2
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nanoparticles in SBA-15. However, in case of S3, the loading procedure involving the loading of SnO2 precursor salt in preformed SBA-15 causes some SnO2 nanoparticles to agglomerate on the pore opening of SBA-15 thus causing a blockage of pore channels. This blockage (dead ends)
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hinders in the free movement of water molecules or charge carriers across the surface of nanocomposite on exposing to humid conditions. This effect is also reflected in Table 1, where
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S2 exhibit comparatively better mesoporous characteristics than S3. In Fig. 7, nanocomposite
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sample S2 has shown highest change in order of magnitude in impedance and excellent linearity therefore it has been selected for the evaluation of humidity sensing properties.
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The impedance measurement at different frequencies in 11-98 %RH range for S2 is shown in Fig. 8. It was observed that the impedance decreases with increase in frequency and the
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best linearity was obtained at 100 Hz. The impedance is almost flat at higher frequencies because of the fact that adsorbed water cannot be polarized at higher frequencies [37]. Considering the
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high response with good linearity, a lower frequency is preferred. Hence we choose to perform
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experiments at 100 Hz in the following experiments. The response time and recovery time are important parameters to evaluate the performance of humidity sensor materials. According to literature, the time taken by a sensor to achieve ~90% of total impedance change is defined as the response time and recovery time in case of adsorption and desorption, respectively [12]. Fig. 9(a-b) shows response/recovery time for nanocomposite samples S2 and S3 respectively and the results obtained are summarized in Table 2. As can be seen, while switching between 11% - 98% - 11% RH, the sample S2 possess fast response and recovery time than S3. This could possibly be due to the presence of more open pore channels which provides quick movement of charge carriers during humidification as well as desiccation process. However, in case of sample S3, the transmission of charge carriers is
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comparatively slower because of chocked pore channels of nanocomposite causing dead ends for movement of water molecules. Nevertheless, on comparing with the results obtained in previous works [8, 12, 38-42], our results show that this sensor synthesized using in-situ method has a
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very good response and recovery property. Hysteresis is one of the most important characteristics of a humidity sensor, which is
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defined as the maximum difference between the adsorption and desorption curves [8]. It is used
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to estimate the reliability of a sensor by measuring the time lag in adsorption and desorption processes. Generally, a sensing material undergoes hysteresis effect at increasing and decreasing
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%RH. The hysteresis was measured by switching the sensor between the closed chambers with 11%, 33%, 43%, 75%, 85% and 98% RH and then transferred back. The humidity hysteresis
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error (HE) was calculated using the expression, HE
, where,
is the difference in
output of forward and backward operations and FFS is the full scale output. The hysteresis curves
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for S2 and S3 based humidity sensor are shown in Fig. 10 where solid square/circle line represents the adsorption process (low %RH to high %RH) and hollow square/circle line represents the desorption process (high %RH to low %RH). As can be seen, sensor S2 exhibits highly reversible sensing properties and the sensing curves for the humidification and desiccation processes almost overlap with each other, showing approximately negligible hysteresis. However, for sample S3, hysteresis is recorded larger in 11-98 %RH range. The maximum absolute value of humidity hysteresis error HE is found to be ~1.5% and 2.9% for samples S2 and S3 in the range of 11–98% RH. The results obtained are listed in Table-2. The hysteresis obtained for S2 is lower than earlier reported results [35, 40-42], which indicates the good reliability of the sensor.
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The dynamic response of sample S2 based sensor towards rapid variations in the 11-98% RH range is shown in Fig. 11(a). The sensor was switched back and forth between two closed chambers with RH values of 11% and 98%, respectively. It was observed that the impedance of
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the sensor reverts always to the original value, when RH is restored to the former state, indicating that the humidity-sensing process is extremely reversible. Moreover, the response and
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recovery times do not change during the four repeated loops of measurements, implying a good
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reproducibility of the humidity response. The standard deviation in process of switching of sensor response was only 1.7%.
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The stability is also an important parameter of humidity-sensing properties. The sample S2 was tested repeatedly under different %RH levels over a span of 60 days. The measurement
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was repeated after every 10th day. As can be seen in Fig. 11(b), the impedance of the sensor fluctuates slightly with time. The sensor shows consistency and acceptable variation in
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3.3 Humidity sensing mechanism
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impedance (~2%) is measured at each humidity level.
In order to understand the sensing mechanism, the ac complex impedance spectra of sample S2 were measured at different %RH. As shown in Fig. 12(a), a part of semicircle is observed at low %RH (11%, 33% and 55%), which indicates the intrinsic impedance of sample [5,6]. This semicircle represents the “non-debye” relation and can be modeled by an equivalent parallel circuit of a capacitor and a resistor [7]. At low %RH, the water molecules form a hydrogen bond with the surface of material. Additional layer of water molecules is facilitated by the H-bonding between oxygen atom of water molecule and base hydroxyl layer. The H3O+ ions hopping across these chemisorbed layers of water molecules is the major source of conduction at low %RH [43]. At higher %RH (75%, 84% and 98%), a line appears at lower frequency leading
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to the formation of smaller semicircle (Fig 12(b)). The line increases with the increase in %RH. The line represents Warburg impedance due to the diffusion of the electroactive species at the electrode [44]. Under this condition, water molecule layers get adsorbed physically leading to
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pore channel filling of S2. This continuous chemisorption of water molecules layers looks like bulk liquid phase of water in which proton generation occurs from the hydration of H3O+ (H3O+
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→ H2O + H+). These protons actively took part in charge transportation and so a significant
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decrease in impedance is observed. Also, the presence of Sn4+ ions provides active sites for the adsorption of water molecules due to their high charge density and causes the frequent ionization
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of physisorbed water molecules at the surface and pores of the sample resulting in generation of H+ ions for electrical conduction. The process of ionization of water molecules increases from
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11-98 %RH resulting in increase in effective charge carriers on the surface of SBA-15 and we obtain a change of more than 5 orders of magnitude in impedance.
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From the above results it is concluded that the comparably enhanced mesoporous nature
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of hybrid nanocomposite synthesized using in-situ method creates abundant opportunities for facile adsorption-desorption of water molecules on internal and external surface of material which results in quick transportation of charge carriers across the sample and consequently exhibits higher RH sensing response while the nanocomposite involving wet impregnation method of synthesis suffers from choking of pore channels with SnO2 nanoparticles and the resulting hindrances caused by these dead ends in free movement of charge transporters is reflected in its lower RH sensing response. In general, our SnO2/SBA-15 hybrid nanocomposite synthesized using in-situ method exhibits higher order of systematic change in impedance, negligible hysteresis with super fast response and recovery time. Thus it can be considered as a potential promising RH sensor material.
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4. Conclusion In summary, SnO2/SBA-15 nanocomposites were synthesized using in-situ and wet impregnation loading processes. A study on their humidity sensing properties reveals that the
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nanocomposite utilizing in-situ loading approach display enhanced humidity sensing response and a change of 5.5 orders in impedance was observed. The sensor material shows swift response
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(15 s) and recovery time (21 s), negligible hysteresis and outstanding stability over a span of 2
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months in the 11-98 %RH range. The improved humidity sensing properties of SnO2/SBA-15 nanocomposite synthesized using in-situ loading approach possess large mesoporous surface
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area, high porosity, 3D interconnectivity of pore channels and well dispersion of guest SnO2 nanoparticles which creates effective surface reaction and facilitates charge propagation across
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the channels of SnO2/SBA-15. It is expected that RH sensor based on mesoporous nanocomposite materials synthesized using in-situ loading approach will be effective in
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designing materials for novel RH sensing applications.
Acknowledgements
Surender Duhan is grateful to UGC, New Delhi (Grant No. 41-997/2012(SR)) for providing Major Research Grant. Vijay K. Tomer also acknowledges UGC for providing fellowship.
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[35] S. Y. Choi, M. Mamak, N. Coombs, N. Chopra, G.A. Ozin, Thermally stable two dimensional hexagonal mesoporous nanocrystalline anatase, meso-nc-TiO2: bulk and crack-free thin film morphologies, Adv. Funct. Mater. 14 (2004) 335–344. [36] S. Besson, T. Gacoin, C. Ricolleau, Boilot, Silver nanoparticle growth in 3D-hexagonal mesoporous silica films, J. Chem. Comm., 3 (2003) 360-361. [37] V. Bondarenka, S. Grebinskij, S. Mickevicius, V. Volkov, Thin films of poly- vanadiummolybdenum acid as starting materials for humidity sensors, Sens. Actuator B 28 (1995) 227–231. [38] Q. Yuan, N. Li, W. Geng, Y. Chi, J. Tu, X. Li, C. Shao, Humidity sensing properties of mesoporous iron oxide/silica composite prepared via hydrothermal process, Sens. Actuators B 160 (2011) 334– 340. [39] Q. Qi, T. Zhang, X. Zheng, L. Wan, Preparation and humidity sensing properties of Fedoped mesoporous silica SBA-15, Sens. Actuators B 135 (2008) 255–261 [40] T. Zhang, R. Wang, W. Geng, X. Li, Q. Qi, Y. He, S. Wang, Study on humidity sensing properties based on composite materials of Li-doped mesoporous silica A-SBA-15, Sens. Actuators B 128 (2008) 482–487
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[41] W. Geng, R. Wang, X. Li, Y. Zou, T. Zhang, J. Tu, Y. He, N. Li, Humidity sensitive property of Li-doped mesoporous silica SBA-15, Sens. Actuators B 127 (2007) 323–329
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[42] R. Wang, T. Zhang, Y. He, X. Li, W. Geng, J. Tu, Q. Yuan, Direct-Current and Alternating-Current Analysis of the Humidity-Sensing Properties of Nickel Oxide Doped Polypyrrole Encapsulated in Mesoporous Silica SBA-15, J. App. Polymer Sci. 115 (2010) 3474-3480. [43] D. Grotthuss, Sur la décomposition de l'eau et des corps qu'elle tient en dissolution à l'aide de l'électricité galvanique, Ann. Chim., 58 (1806) 54-73
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[44] P. Christensen, A. Hammett, Techniques and Mechanisms in Electrochemistry, Springer, Netherlands, 1994.
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Table captions: Table 1: Structural and textural properties of mesoporous SBA-15 and SnO2/SBA-15
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nanocomposites.
Table 2: A comparison of humidity sensing properties of hybrid nanocomposites obtained from
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in-situ and wet impregnation method.
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a0 (nm)b
SBET (m2/g)c
DP (nm)d
VP (cm3/g)e
DW (nm)f
S1
10.7
12.36
733.76
8.82
1.10
3.54
Effective SnO2 wt% (obtained from EDX) --
S2
10.23
11.81
661.28
7.11
1.02
4.7
3.53
5
S3
10.11
11.67
598.17
6.93
0.98
4.74
3.06
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d100: d-spacing a0: Unit cell parameter [a0 = 2 x d100/√3] c SBET: Total surface area d DP: Pore size e VP: Pore volume f DW: Pore wall thickness [DW = a0 - DP]
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Theoritical SnO2 loading (wt%) --
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d100 (nm)a
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Sample
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S2 S3
In-situ Wet impregnation
Order of magnitude change in Impedance in 11-98 %RH range 5.5 4.5
Response time (s)
Recovery time (s)
15 33
21 50
Hysteresis (%)
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Synthesis method
1.5 2.9
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Figure Captions Figure 1: Schematic diagram of fabricated sensor.
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Figure 2: Low angle XRD spectra for samples S1, S2, S3 and S4 (inset). Figure 3: Wide angle XRD spectra for S1, S2, S3 and S4.
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Figure 4: adsorption-desorption isotherms curves (a), and their corresponding pore size
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distributions curves (b), for S1, S2 and S3.
Figure 5: HRTEM image showing uniform channels with long range order of (a) SBA-15, (b)
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S2 and (c) S3.
Figure 6: FESEM image of nanocomposite S2 and S3 with their corresponding EDX spectra
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(inset).
Figure 7: Humidity sensing curves showing decrease in impedance with increase in %RH for
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S1, S2, S3 and S4.
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Figure 8: Relationship of impedance and relative humidity based on nanocomposite S2 at various frequencies.
Figure 9: (a) Humidity response (humidification from 11-98 %RH) and recovery (desiccation from 98-11 %RH) curves of S2 and S3.
Figure 10: Hysteresis curve showing adsorption-desorption responses measured in the 11-98 %RH range of S2 and S3
Figure 11: (a) Repeated response and recovery characteristics of S2 measured at consecutive intervals of time in four cycles and (b) The response of S2 monitored at different humidity conditions for 2 months. Figure 12: The measured and simulated complex impedance spectra (Nyquist plot) based on S2, RH varying from 11% to 98%. 25
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Author biographies
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Vijay K. Tomer is a research scholar in Department of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, India, doing PhD in the area of mesoporous materials, gas/humidity sensors. He received his M.Tech degree (2012) from Dept. of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, India. His research interests include mesoporous materials for gas and humidity sensors.
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Surender Duhan received his Ph.D. degree (2009) from Guru Jambheshwar University of Science. & Tech., Hisar. Since 2010, he is working as Assistant Professor in Dept. of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, where he leads a research group dedicated to the synthesis and characterization of functional materials, especially porous metal oxides for applications in gas sensing, catalysis and drug delivery. He has published 37 research papers in reputed International/National Journals including several independent research papers. He is author of six books on Engg. Physics.
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S0925-4005(15)00227-0 http://dx.doi.org/doi:10.1016/j.snb.2015.02.054 SNB 18117
To appear in:
Sensors and Actuators B
Received date: Revised date: Accepted date:
4-12-2014 30-1-2015 7-2-2015
Please cite this article as: V.K. Tomer, S. Duhan, In-situ synthesis of SnO2 /SBA-15 hybrid nanocomposite as highly efficient humidity sensor, Sensors and Actuators B: Chemical (2015), http://dx.doi.org/10.1016/j.snb.2015.02.054 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Highlights 1. SnO2/SBA-15 mesoporous nanocomposite was synthesized using hydrothermal method.
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2. SnO2 was loaded in SBA-15 using in-situ and wet impregnation process. 3. The prepared nanocomposites performance towards change in relative humidity (RH) was
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observed in 11-98 %RH range.
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4. The nanocomposite synthesized using in-situ process shows comparatively superior RH
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sensing characteristics in complete RH range.
5. A change of 5.5 orders in impedance magnitude, negligible hysteresis (1.5%) with fast
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response (15 sec) and recovery time (21 sec) was observed in 11-98 %RH range.
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In-situ synthesis of SnO2/SBA-15 hybrid nanocomposite as highly efficient humidity sensor Vijay K. Tomer, Surender Duhan* Nanomaterials Research Laboratory Department of Materials Science & Nanotechnology
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D.C.R. University of Science & Technology, Murthal (Sonepat) Haryana, 131039 (INDIA)
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Abstract
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We report a hydrothermally derived novel scheme to synthesize SnO2 supported mesoporous SBA-15 nanocomposite for relative humidity (RH) sensing at room temperature. Two loading
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procedures of SnO2 nanoparticles in SBA-15 were followed: in-situ and wet impregnation, in order to reveal information regarding the effect of synthesis strategies on the RH sensing
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response of the nanocomposite. The obtained nanocomposites were characterized using a combination of X-ray diffraction (XRD), N2 adsorption-desorption isotherms, High resolution
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transmission electron microscope (HRTEM), Field emission scanning electron microscope
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(FESEM) and Energy dispersive X-ray (EDX) spectroscopy. The humidity sensing properties of the presented nanocomposite sensor, such as linearity, response–recovery characteristics, hysteresis and stability, were investigated by exposing sensors to wide range of 11–98 %RH at room temperature. Due to uniform and homogeneous dispersion of SnO2 nanoparticles in the pore channels of SBA-15, the nanocomposite sensor synthesized using in-situ process not only exhibit superior sensing response towards change in %RH but also posses swift response– recovery time, good repeatability, negligible hysteresis and stability, highlighting the unique advantages of the synthesis procedures for fabrication of sensor materials. The complex impedance spectra of the sensor at different RHs were analyzed to explore the humidity-sensing mechanism. This study demonstrates that the SnO2/SBA-15 nanocomposite prepared by in-situ method can be used as the humidity-sensing material for the fabrication of humidity sensors. 2
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Keywords: SnO2/SBA-15; in-situ; hydrothermal; relative humidity. * Corresponding author E-mail: [email protected]
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Tel.: +91- 9813170944.
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1. Introduction Moisture contained in the atmosphere is a highly variable and unpredictable quantity
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which frequently changes in line with geographical and topographical condition. It is important to keep an eye on and command the profile involving water vapors present in the environment
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for human ease and comfort and also numerous industrial processes [1-4]. During the last
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decade, limits have been shoved additionally by researchers globally with regard to fabricating and designing efficient relative humidity sensors based on mesoporous materials [5-7]. The
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unique properties of mesoporous materials like high surface area and interconnected pore channels provide easier adsorption and facile transportation of water molecules across their
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surfaces [8-9]. Mesoporous silica SBA-15 is particularly important material among its class for its high surface area, pore volume, excellent thermal stability, interconnected with tunable pore
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channels [10] and is particularly obtaining exclusive attention in applications like photocatalysis,
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sensing, drug delivery and nanomaterials fabrication [11-14]. SBA-15, whilst functioning as a host matrix has been keenly investigated to accommodate various metal and metal oxides oxide dopants for a variety of novel applications [15-17]. Moreover, the uniform meso-ordered pore channels of SBA-15 can extensively control the particle size of dopant while enabling it to effectively prevent debris from agglomeration [18]. Stannic oxide (SnO2) is an important n-type semiconductor material for humidity detection due to its chemical sensitivity to oxygen and water vapor in air, high chemical stability, non-toxicity and low cost [19-20]. Water is adsorbed on SnO2 surface in the molecular and hydroxyl form and conduct electronically at room temperature [21]. Kuang et. al has synthesized RH sensors based on single SnO2 nanowire [22]. They have obtained an average response time of 145 s and recovery time of 40 s. Similarly, Parthibavarman et. al. have synthesized spherical 4
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SnO2 nanostructures and obtained response time and recovery time of 32s and 25 s respectively [23]. Considering the dependability of RH sensing properties on surface area of SnO2, there remains a consistent effort in increasing its surface area so as to create more active sites for rapid
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adsorption of water molecules to improve the RH sensing characteristics [24-25]. With the mesoporous nanocomposite based on SnO2/SBA-15, we aim at better sensitivity, quick
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response/recovery times, wide operating %RH range, low working temperature range and
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improved stability than those of the RH sensors made out of only pure SBA-15 and SnO2 materials.
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In the recent times, SBA-15 assisted SnO2 mesoporous nanocomposite has been synthesized by researchers using incipient wet impregnation process. This is a two step
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procedure wherein SBA-15 is synthesized using conventional hydrothermal method followed by soaking it in solvent containing SnO2 precursor [14, 26-27]. Previous studies reveal that in wet
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impregnation method, the pores channels of SBA-15 gets partially or completely chocked
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resulting in agglomeration of guest nanoparticles on the pore openings and surface of SBA-15 which causes the nanocomposite possessing poor pore characteristics [28-29]. To overcome this loss in mesoporous efficiency, we propose a simple, economical and energy saving in-situ loading method wherein the SnO2 precursor salt is introduced in the host matrix prior to the silica hydrolysis process. In comparison to wet impregnation process, the SnO2/SBA-15 nanocomposite utilizing in-situ loading procedure exhibit better mesoporous characteristics. The response of the as synthesized SnO2/SBA-15 nanocomposites towards RH was measured in 1198% range at room temperature. The sample synthesized following in-situ loading approach exhibit comparatively better RH sensing response and a change of 5.5 orders in magnitude was recorded in 11-98 %RH range at 25 °C. Moreover, the sensor shows excellent linearity,
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negligible hysteresis (1.5 %), quick response time (15 sec), rapid recovery time (21 sec), stability and broad operating range (11-98 %RH). These excellent sensing characteristics make the SnO2/SBA-15 nanocomposite prepared by in-situ method a good candidate for the fabrication of
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high performance humidity sensors. 2. Experimental
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2.1 Materials
Tetraethoxy orthosilicate [(C2H5O)4Si, TEOS, Sigma Aldrich], Pluronic P123 [Ethylene
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Oxide-Propylene Oxide-Ethylene Oxide, (EO20PO70EO20), Mw = 5800, Sigma Aldrich], Tin (II)
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chloride [SnCl2•2H2O, Merck], Sodium Dodecyl Sulphate [(CH3(CH2)11OSO3Na), Merck], Sodium Hydroxide (NaOH, Fisher Scientific), Ethanol (Fisher Scientific) and HCl (35%, Fisher
2.2 Material Preparation
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Scientific) were used as received. Double distilled water was used throughout the experiments.
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Synthesis of SBA-15: The mesoporous SBA-15 was prepared according to previous
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method [18]. 2 g P123 was dissolved in 70 ml distilled water at 40 °C with vigorous stirring (1000 rpm), followed by addition of 10 ml HCl (2M). After obtaining a clear transparent solution for 3 h of continuous stirring, 4.5 g of TEOS was added and resultant solution was kept under stirring for 24 h at 40 °C. The dried white product thus obtained was put for hydrothermal treatment in a Teflon lined stainless steel autoclave and treated at 100 °C for 24 hrs. After cooling down to room temperature, the solid products were recovered, filtered, washed and dried at 70 °C. The powder mesoporous silica SBA-15 was obtained by calcination of the products at 600 °C (heating rate of 1 °C/min) for 6 hrs in air to remove organic templates. Synthesis of SnO2/SBA-15(I): For loading of 5 wt% SnO2 in SBA-15 using in-situ method, 0.1g of Tin chloride salt solution was added in aqueous miceller solution of P123. The
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mixture was stirred for 3 h followed by addition of TEOS and kept under stirring for 24 h and further following the same route as used for pure SBA-15. Synthesis of SnO2/SBA-15(W): In order to prepare 5 wt% SnO2 loaded SBA-15
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nanocomposites by wet impregnation method, aqueous solution of 0.1 g SnCl2•2H2O was prepared followed by addition of 1 g SBA-15 to the solution under stirring. The samples were
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left overnight to dry and were calcined at 600 °C to obtain the mesoporous nanocomposite.
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Synthesis of SnO2: 2.7 g of SnCl2•2H2O was dissolved in 40 ml water followed by addition of 50 ml NaOH (1M) solution to obtain clear transparent solution. Then 40 ml aqueous
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solution of 0.024g SDS was added to the above solution with addition of 15 ml ethanol. Obtained solution was then treated hydrothermally in a Teflon-lined autoclave at 170 °C for 24 h. The
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white precipitates were recovered, washed with distilled water and put to dry at 80°C overnight. Finally, the white powder was calcined at 600 °Ϲ for 4 h to obtain pure SnO2 material. For the
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ease of analysis, all the four samples SBA-15, SnO2/SBA-15(I), SnO2/SBA-15(W) and SnO2
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were denoted as S1, S2, S3 and S4 respectively. 2.3 Fabrication of humidity sensors
For fabrication of sensors, the materials (S1, S2, S3 and S4) were coated on ceramic rod of 10 mm length and 3 mm diameter with metallic lead end caps. The schematic diagram of fabricated sensor is shown in Fig. 1. Prior to use, the ceramic rod was cleaned by an ultrasonic treatment in acetone, then rinsed thoroughly with double-distilled water and dried in vacuum. The samples were ground and mixed with ethanol to form a paste and coated on the ceramic rod using drop casting method. The coated ceramic rods were dried at 80 °C for 12 h and used as sensing elements to evaluate the humidity sensing characteristics. 2.4 Humidity sensor measurement
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The different RH levels were generated by the different saturated salt solutions in air tight closed glass chambers at room temperature (25 °C). The six different standard saturated aqueous salt solutions of LiCl, MgCl2•6H2O, MgNO3•4H2O, NaCl, KCl and K2SO4 which yielded 11%,
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33%, 54%, 75%, 84% and 98% relative humidity, respectively were used to act as humidity source [30]. The saturated salt solutions were placed overnight in the chambers at room
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temperature to ensure that the air in the chamber reached to equilibrium states. These RH levels
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were monitored by a standard hygrometer. The material coated ceramic rod was placed successively into the chambers with different RH levels at room temperature and the impedance
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of the sensor was measured as a function of RH at 25 °C (± 1°C) using a simple two-probe configuration with a LCR Meter. The voltage applied was AC 1 V and the frequency was varied
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from 50 Hz to 10 kHz. The characteristics RH response curves were obtained by exposing the sensor in the closed chambers with different %RH environment for the uptake of water
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molecules until the impedance of the sensing material reached a stable value. The exposure of
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sensing element to laboratory atmosphere during switching of sensor material between different chambers makes it almost impossible to measure the response transients precisely. However, during the experiments, we have tried to complete the chamber change process as quick as possible, which could be done less than 1 s. 2.5 Characterization of materials
The sensor materials were characterized using various techniques to identify the structural, morphological and physicochemical properties. The Low angle and Wide angle XRD information was obtained on a Bruker D8 advance diffractometer using CuKα monochromatic radiation (λ=1.5418 Å) 40 kV and 40 mA with a step size of 0.02°. The N2 adsorption-desorption isotherms were carried out using Micrometrices (Tristar 3000) at 77K. Before the measurements,
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the samples were degassed at 300 °C for 6 h. The BET and BJH method were used to determine the specific surface area and pore characteristics of the materials respectively [31, 32]. The mesoporous structure of the sensor materials was further investigated using High-Resolution
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Transmission Electron Microscopy (HR-TEM) on TECNAI G20 electron microscope at an accelerating voltage of 200 kV. Morphology of the samples along with its elemental composition
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was characterized by Field emission scanning electron microscope equipped with an Energy-
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dispersive X-Ray spectroscopy (SEM-EDX, FEI QUANTA 200F) at an acceleration voltage of 10-15 kV. The samples for analysis were prepared by distributing the powder samples on a two
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sided leading sticky tape. 3. Results and Discussions
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3.1 Characterization of samples
The Low angle XRD spectra for SBA-15 (S1), SnO2/SBA-15 nanocomposites (S2, S3)
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and pure SnO2 (S4) is shown in Fig. 2. For S1, S2 and S3, almost similar LAXRD patterns are
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noted. Three well resolved peaks in the range of 2θ = 0.5° – 3° for nanocomposites S2 and S3 were observed similar to that for S1 which demonstrates that SnO2 loaded SBA-15 possesses meso-ordered, hexagonal structures [10, 33]. For S1, these peaks are indexed to the (1 0 0) (d100= 107 Å), (1 1 0) (d110= 58.28 Å) and (2 0 0) (d200= 51.97 Å) reflections of the 2D hexagonal space group p6mm, which is comparable to those described by Zhao [10]. For pure SnO2 (S4, inset), the peak at 2θ = 0.8° indicates the disordered mesoporous structure. The physicochemical properties of SBA-15 and SnO2/SBA-15 nanocomposites as determined by LA-XRD results are summarized in Table 1. Fig. 3 shows the wide angle XRD pattern (2θ = 15° - 70°) for S1-S4. For S4, well resolved SnO2 peaks are obtained at 2θ = 26.9°, 34.2°, 38.2°, 52.3°, 54.9°, 57.8°, 62.2°, 64.6°
9
Page 9 of 39
and 66.2° corresponding to (110), (101), (200), (211), (220), (002), (310), (112) and (301) planes of SnO2 (JCPDS no. 03-1116) respectively. A broad peak centered at 2θ = 22° corresponding to the pristine material is observed for S1, S2 and S3. Small peaks of SnO2 are observed for S2 and
ip t
S3 confirming that SnO2 has been loaded in the channels of SBA-15 matrix. The N2 adsorption-desorption isotherm for S1-S3 is shown in Fig. 4(a). A sharp inflection
cr
peak was observed which can be attributed to type IV characteristic curve as deduced from
us
IUPAC classification of sorption isotherms for mesoporous materials [34]. Both the nanocomposite sample S2 and S3 retains their mesoporous structure even after loading of SnO2
an
nanoparticles. However, the surface area exhibited by S2 is comparatively higher than S3. This was consistent with the results obtained from Low angle XRD. The hysteresis loop of S1-S3
M
resembles the H1 type curve which corresponds to uniform cylindrical geometry exhibited by mesoporous solids [35]. The information regarding pore size, volume and wall thickness as
d
determined from BET isotherms is listed in Table 1. The BJH pore size distribution curves
Ac ce pt e
shown in Fig. 4(b) determine the average pore size of the samples. It can be seen that with the loading of SnO2 nanoparticles in SBA-15 (S2 and S3), the pore size get reduced due to the presence of SnO2 nanoparticles in the SBA-15 channels. However, the thickness of pore walls for the two nanocomposites was found to be higher than the pure SBA-15 due to pore filling effect illustrating that the SnO2 nanoparticles have been confined inside the channels of SBA-15. The pore morphology of S1 and presence of SnO2 nanoparticles inside mesoporous silica framework in hybrid nanocomposite S2 and S3 were investigated by HRTEM. Fig. 5 shows that all the samples represent a long range pore order of 2-D (p6mm) mesoporous channels which confirms the mesoporosity of the obtained materials [10]. As estimated from the HRTEM images, the separation between two sequential centers of hexagonal pores for pure SBA-15 is
10
Page 10 of 39
~12.48 nm. The average pore diameter and wall thickness are around 8.7 nm and 3.78 nm, respectively which is quite consistent with the results acquired from BET surface area analysis and XRD. The long range order of channels does not change by virtue of SnO2 stacking in SBA-
ip t
15 however the dimensions are shrunk by the interaction of the nanoparticles with the host SBA15. It is supported by the HRTEM results that SnO2 loaded SBA-15 has high level of
cr
crystallinity and phase purity. Also the hexagonal mesostructure of SBA-15 remains intact after
us
the incorporation of SnO2 nanoparticles. Fig 5(b) shows nanocomposite S2 prepared by in-situ method of loading. Exceedingly scattered SnO2 nanoparticles were observed uniformly in the
an
pore channels of SBA-15 framework. In the in-situ method of synthesis, TEOS and SnCl2•2H2O were simultaneously added to the reaction system and mixed evenly by continuous stirring over a
M
long period of time. So we considered that the formed SnO2 nanoparticles are mixed evenly with SBA-15 matrix. Moreover, during the calcination process, the SnO2 nanoparticles move inside
d
the channels of SBA-15 [36]. Fig 5(c) corresponds to nanocomposite S3 prepared by wet
Ac ce pt e
impregnation method. As seen clearly, some pore channels of SBA-15 were chocked in the process of nanocomposite formation. Due to these blocked pore channels, S3 possess lower mesoporous characteristics than S2.
The SEM images of sample S2 and S3 are shown in Fig. 6(a-b) which shows that both the nanocomposite samples have similar wheat like morphologies of packed aggregates of 0.5-1 µm sized rod-like structures wherein the major unit of a single rod consists of small domains. This kind of morphology has been demonstrated to have long range parallel channels with the 2-D hexagonal mesostructure [10]. The EDX spectra of nanocomposite sample S2 and S3 are shown in inset of Fig. 6(a) and Fig. 6(b) respectively where no other elements were detected except O, Si and Sn, thus confirming the purity of samples. The comparatively higher wt% of ‘Sn’ content
11
Page 11 of 39
in S2 than S3 arise from the fact that wet impregnation method causes some SnO2 nanoparticles to agglomerate on the pore opening of SBA-15 thus causing a blockage of pore channels for successive loading of SnO2 nanoparticles while in case of in-situ method, the uniform dispersion
ip t
of SnO2 nanoparticles in SBA-15 happens because the precursor salt of SnO2 was introduced into the reaction system simultaneously with silica precursor. The results obtained from EDX
cr
analysis (Table-1) show that for 5 wt% of SnO2 incorporated into SBA-15, approximately 70.6%
us
and 61.2% of the total weight of SnO2 was loaded in the channels of SBA-15 for nanocomposites sample S2 and S3 respectively.
an
3.2 Humidity sensing properties
Fig. 7 shows the RH dependent impedance response of the as synthesized samples at
M
room temperature in the 11- 98 %RH range. As can be seen, at low %RH, all samples exhibit very high impedance, however, as the %RH increases, a dramatic decrease in impedance was
d
observed. The samples consisting of pure SBA-15 and SnO2 exhibits a change of 2.5 and 3.5
Ac ce pt e
orders of magnitude change in impedance in 11-98% RH range. The poor RH response of SBA15 is attributed to its high intrinsic impedance caused by decrease of –OH groups during calcination process. However, for nanocomposites S2 and S3, a drop of 5.5 and 4.5 orders in impedance magnitude respectively was observed in complete %RH range indicating improved humidity sensing response of the hybrid nanocomposite than pure SBA-15 and SnO2 materials. This reveals that the loading of SnO2 nanoparticles has directly contributes in enhancement of conductivity and improving the linearity of the synthesized nanocomposites. Among the nanocomposites S2 and S3, in spite of same loading concentration of SnO2 in SBA-15, S2 shows comparatively enhanced sensing response towards change in %RH due to two reasons: (a) higher wt% loading of SnO2 in nanocomposite and (b) homogeneous and uniform dispersion of SnO2
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Page 12 of 39
nanoparticles in SBA-15. However, in case of S3, the loading procedure involving the loading of SnO2 precursor salt in preformed SBA-15 causes some SnO2 nanoparticles to agglomerate on the pore opening of SBA-15 thus causing a blockage of pore channels. This blockage (dead ends)
ip t
hinders in the free movement of water molecules or charge carriers across the surface of nanocomposite on exposing to humid conditions. This effect is also reflected in Table 1, where
cr
S2 exhibit comparatively better mesoporous characteristics than S3. In Fig. 7, nanocomposite
us
sample S2 has shown highest change in order of magnitude in impedance and excellent linearity therefore it has been selected for the evaluation of humidity sensing properties.
an
The impedance measurement at different frequencies in 11-98 %RH range for S2 is shown in Fig. 8. It was observed that the impedance decreases with increase in frequency and the
M
best linearity was obtained at 100 Hz. The impedance is almost flat at higher frequencies because of the fact that adsorbed water cannot be polarized at higher frequencies [37]. Considering the
d
high response with good linearity, a lower frequency is preferred. Hence we choose to perform
Ac ce pt e
experiments at 100 Hz in the following experiments. The response time and recovery time are important parameters to evaluate the performance of humidity sensor materials. According to literature, the time taken by a sensor to achieve ~90% of total impedance change is defined as the response time and recovery time in case of adsorption and desorption, respectively [12]. Fig. 9(a-b) shows response/recovery time for nanocomposite samples S2 and S3 respectively and the results obtained are summarized in Table 2. As can be seen, while switching between 11% - 98% - 11% RH, the sample S2 possess fast response and recovery time than S3. This could possibly be due to the presence of more open pore channels which provides quick movement of charge carriers during humidification as well as desiccation process. However, in case of sample S3, the transmission of charge carriers is
13
Page 13 of 39
comparatively slower because of chocked pore channels of nanocomposite causing dead ends for movement of water molecules. Nevertheless, on comparing with the results obtained in previous works [8, 12, 38-42], our results show that this sensor synthesized using in-situ method has a
ip t
very good response and recovery property. Hysteresis is one of the most important characteristics of a humidity sensor, which is
cr
defined as the maximum difference between the adsorption and desorption curves [8]. It is used
us
to estimate the reliability of a sensor by measuring the time lag in adsorption and desorption processes. Generally, a sensing material undergoes hysteresis effect at increasing and decreasing
an
%RH. The hysteresis was measured by switching the sensor between the closed chambers with 11%, 33%, 43%, 75%, 85% and 98% RH and then transferred back. The humidity hysteresis
M
error (HE) was calculated using the expression, HE
, where,
is the difference in
output of forward and backward operations and FFS is the full scale output. The hysteresis curves
Ac ce pt e
d
for S2 and S3 based humidity sensor are shown in Fig. 10 where solid square/circle line represents the adsorption process (low %RH to high %RH) and hollow square/circle line represents the desorption process (high %RH to low %RH). As can be seen, sensor S2 exhibits highly reversible sensing properties and the sensing curves for the humidification and desiccation processes almost overlap with each other, showing approximately negligible hysteresis. However, for sample S3, hysteresis is recorded larger in 11-98 %RH range. The maximum absolute value of humidity hysteresis error HE is found to be ~1.5% and 2.9% for samples S2 and S3 in the range of 11–98% RH. The results obtained are listed in Table-2. The hysteresis obtained for S2 is lower than earlier reported results [35, 40-42], which indicates the good reliability of the sensor.
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Page 14 of 39
The dynamic response of sample S2 based sensor towards rapid variations in the 11-98% RH range is shown in Fig. 11(a). The sensor was switched back and forth between two closed chambers with RH values of 11% and 98%, respectively. It was observed that the impedance of
ip t
the sensor reverts always to the original value, when RH is restored to the former state, indicating that the humidity-sensing process is extremely reversible. Moreover, the response and
cr
recovery times do not change during the four repeated loops of measurements, implying a good
us
reproducibility of the humidity response. The standard deviation in process of switching of sensor response was only 1.7%.
an
The stability is also an important parameter of humidity-sensing properties. The sample S2 was tested repeatedly under different %RH levels over a span of 60 days. The measurement
M
was repeated after every 10th day. As can be seen in Fig. 11(b), the impedance of the sensor fluctuates slightly with time. The sensor shows consistency and acceptable variation in
Ac ce pt e
3.3 Humidity sensing mechanism
d
impedance (~2%) is measured at each humidity level.
In order to understand the sensing mechanism, the ac complex impedance spectra of sample S2 were measured at different %RH. As shown in Fig. 12(a), a part of semicircle is observed at low %RH (11%, 33% and 55%), which indicates the intrinsic impedance of sample [5,6]. This semicircle represents the “non-debye” relation and can be modeled by an equivalent parallel circuit of a capacitor and a resistor [7]. At low %RH, the water molecules form a hydrogen bond with the surface of material. Additional layer of water molecules is facilitated by the H-bonding between oxygen atom of water molecule and base hydroxyl layer. The H3O+ ions hopping across these chemisorbed layers of water molecules is the major source of conduction at low %RH [43]. At higher %RH (75%, 84% and 98%), a line appears at lower frequency leading
15
Page 15 of 39
to the formation of smaller semicircle (Fig 12(b)). The line increases with the increase in %RH. The line represents Warburg impedance due to the diffusion of the electroactive species at the electrode [44]. Under this condition, water molecule layers get adsorbed physically leading to
ip t
pore channel filling of S2. This continuous chemisorption of water molecules layers looks like bulk liquid phase of water in which proton generation occurs from the hydration of H3O+ (H3O+
cr
→ H2O + H+). These protons actively took part in charge transportation and so a significant
us
decrease in impedance is observed. Also, the presence of Sn4+ ions provides active sites for the adsorption of water molecules due to their high charge density and causes the frequent ionization
an
of physisorbed water molecules at the surface and pores of the sample resulting in generation of H+ ions for electrical conduction. The process of ionization of water molecules increases from
M
11-98 %RH resulting in increase in effective charge carriers on the surface of SBA-15 and we obtain a change of more than 5 orders of magnitude in impedance.
d
From the above results it is concluded that the comparably enhanced mesoporous nature
Ac ce pt e
of hybrid nanocomposite synthesized using in-situ method creates abundant opportunities for facile adsorption-desorption of water molecules on internal and external surface of material which results in quick transportation of charge carriers across the sample and consequently exhibits higher RH sensing response while the nanocomposite involving wet impregnation method of synthesis suffers from choking of pore channels with SnO2 nanoparticles and the resulting hindrances caused by these dead ends in free movement of charge transporters is reflected in its lower RH sensing response. In general, our SnO2/SBA-15 hybrid nanocomposite synthesized using in-situ method exhibits higher order of systematic change in impedance, negligible hysteresis with super fast response and recovery time. Thus it can be considered as a potential promising RH sensor material.
16
Page 16 of 39
4. Conclusion In summary, SnO2/SBA-15 nanocomposites were synthesized using in-situ and wet impregnation loading processes. A study on their humidity sensing properties reveals that the
ip t
nanocomposite utilizing in-situ loading approach display enhanced humidity sensing response and a change of 5.5 orders in impedance was observed. The sensor material shows swift response
cr
(15 s) and recovery time (21 s), negligible hysteresis and outstanding stability over a span of 2
us
months in the 11-98 %RH range. The improved humidity sensing properties of SnO2/SBA-15 nanocomposite synthesized using in-situ loading approach possess large mesoporous surface
an
area, high porosity, 3D interconnectivity of pore channels and well dispersion of guest SnO2 nanoparticles which creates effective surface reaction and facilitates charge propagation across
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the channels of SnO2/SBA-15. It is expected that RH sensor based on mesoporous nanocomposite materials synthesized using in-situ loading approach will be effective in
Ac ce pt e
d
designing materials for novel RH sensing applications.
Acknowledgements
Surender Duhan is grateful to UGC, New Delhi (Grant No. 41-997/2012(SR)) for providing Major Research Grant. Vijay K. Tomer also acknowledges UGC for providing fellowship.
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V. K. Tomer, P. V. Adhyapak, S. Duhan, I. S. Mulla, Humidity sensing properties of Agloaded mesoporous silica SBA-15 nanocomposites prepared via hydrothermal process, Microporous Mesoporous Mater. 197 (2014) 140-147.
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[10] D. Zhao, J. Feng, Q. Huo, N. Melosh, G. H. Fredrickson, B. F Chmelka, G. D. Stucky, Triblock Copolymer synthesis of mesoporous silica with periodic 50 to 300 angstrom pores, Science 279 (1998) 548-552. [11] J. Liu, Q. Yang, M.P. Kapoor, N. Setoyama, S. Inagaki, J. Yang, L. Zhang, Structural relation properties of hydrothermally stable functionalized mesoporous organosilicas and catalysis, J. Phys. Chem. B 109 (2005) 12250–12256. [12] V. K. Tomer, S. Duhan, P.V. Adhyapak, I.S. Mulla, Mn loaded mesoporous silica nanocomposite: a highly efficient humidity sensor, J. Am. Ceram. Soc. (2014) 1-7. DOI: 10.1111/jace.13383 [13] V. Mamaeva, C. Sahlgren, M. Lindén, Mesoporous silica nanoparticles in medicine-Recent advances, Adv. Drug Delivery- Reviews 65 (2013) 689-702.
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[14] G. Satishkumar, L. Titelman, M. V. Landau, Mechanism for the formation of tin oxide nanoparticles and nanowires inside the mesopores of SBA-15, J. Solid State Chem. 182 (2009) 2822–2828.
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[15] G. Laugel, J. Arichi, P. Bernhardt, M. Moliere, A. Kiennemann, F. Garin, B. Louis, Preparation and characterization of metal oxides supported on SBA-15 as methane combustion catalysts, C. R. Chimie 12 (2009) 731-739.
cr
[16] F. M. Zhang, B. S. Liu, Y. Zhang, Y. H. Guo, Z.Y. Wan, F. Subhan, Highly stable and regenerable Mn-based/SBA-15 sorbents for desulfurization of hot coal gas, J. Hazardous Mater. 233 (2012) 219– 227.
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[17] G. Du, S. Lim, M. Pinault, C. Wang, F. Fang, L. Pfefferle, G. L. Haller, Synthesis, characterization, and catalytic performance of highly dispersed vanadium grafted SBA-15 catalyst, J. Catalysis 253 (2008) 74–90.
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[18] V. K. Tomer, R. Malik, S. Jangra, S.P. Nehra, S. Duhan, One pot direct synthesis of mesoporous SnO2/SBA-15 nanocomposite by the hydrothermal method, Mater. Lett. 132 (2014) 228-230.
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[19] Q. Kuang, C.S. Lao, Z.L. Wang, Z.X. Xie, L.S. Zheng, High-sensitivity humidity sensor based on a single SnO2 nanowire, J. Am. Chem. Soc. 129 (2007) 6070–6071.
d
[20] E. Comini, G. Faglia, G. Sberveglieri, Z.W. Pan, Z.L. Wang, Stable and highly sensitive gas sensors based on semiconducting oxide nanobelts, Appl. Phys. Lett. 81 (2002) 1869.
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[21] Z. Chen, C. Lu, Humidity Sensors: A Review of Materials and Mechanisms, Sens. Lett. 3 (2005), 274–295 [22] Q. Kuang, C. Lao, Z. L. Wang, Z. Xie, L. Zheng, High-Sensitivity Humidity Sensor Based on a Single SnO2 Nanowire, J. Am. Chem. Soc. 129 (2007), 6070-6071 [23] M. Parthibavarman, V. Hariharan, C. Sekar, High sensitivity humidity sensors based on SnO2 nanoparticles by microwave irradiation method, Mater. Sci. Engg: C 31 (2011) 840844 [24] G. Eranna, B.C. Joshi, D.P. Runthala, R.P. Gupta, Oxide materials for development of integrated gas sensors, Crit. Rev. Solid State Mater. Sci. 29 (2004) 111. [25] Y. Shimizu, A. Jono, T. Hyodo, M. Egashira, Preparation of large mesoporous SnO2 powder for gas sensor application, Sens. Actuators B 108 (2005) 56-61. [26] N. R. Srinivasan, R. Bandyopadhyaya, Highly accessible SnO2 nanoparticle embedded SBA-15 mesoporous silica as a superior photocatalyst, Microporous Mesoporous Mater. 149 (2012) 166–171. [27] J. K. Shon, S. S. Kong, Y. S. Kim, J. H. Lee, W. K. Park, S. C. Park, J. M. Kim, Solventfree infiltration method for mesoporous SnO2 using mesoporous silica templates, Microporous Mesoporous Mater. 120 (2009) 441–446. 19
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[28] P. Shah, A.V. Ramaswamy, K. Lazar, V. Ramaswamy, Direct hydrothermal synthesis of mesoporous Sn-SBA-15, materials under weak acidic conditions, Microporous Mesoporous Mater. 100 (2007) 210–226. [29] E. M. Seftel, P. Cool, A. L. Spetz, D. Luti, Pt-doped semiconductive oxides loaded on mesoporous SBA-15 for gas sensing, C. R. Chimie 17 (2014) 717-724.
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[30] L. Greenspan, Humidity fixed points of binary saturated aqueous solutions, J. Res. Nat. Bur. Stand. 81 (1977) 89–96.
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[32] E. P. Barrett, L. G. Joyner, P. P. Halenda, The Determination of Pore Volume and Area Distributions in Porous Substances. I. Computations from Nitrogen Isotherms, J. Am. Chem. Soc. 73 (1951) 373-380.
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[33] D. Zhao, Q. Huo, J. Feng, B.F. Chmelka G.D. Stucky, Nonionic Triblock and Star Diblock Copolymer and Oligomeric Surfactant Synthesis of Highly Ordered, Hydrothermally Stable, Mesoporous Silica Structures. J. Am. Chem. Soc. 120 (1998) 6024-6036.
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[34] K. S. W. Sing, D. H. Everett, R. A. W. Haul, L. Moscou, R. A. Pierotti, J. Rouquérol, T. Siemieniewska, Reporting Physisorption Data for Gas/Solid Systems with Special Reference to the Determination of Surface Area and Porosity. Pure Appl. Chem. 57 (1985) 603-619.
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[35] S. Y. Choi, M. Mamak, N. Coombs, N. Chopra, G.A. Ozin, Thermally stable two dimensional hexagonal mesoporous nanocrystalline anatase, meso-nc-TiO2: bulk and crack-free thin film morphologies, Adv. Funct. Mater. 14 (2004) 335–344. [36] S. Besson, T. Gacoin, C. Ricolleau, Boilot, Silver nanoparticle growth in 3D-hexagonal mesoporous silica films, J. Chem. Comm., 3 (2003) 360-361. [37] V. Bondarenka, S. Grebinskij, S. Mickevicius, V. Volkov, Thin films of poly- vanadiummolybdenum acid as starting materials for humidity sensors, Sens. Actuator B 28 (1995) 227–231. [38] Q. Yuan, N. Li, W. Geng, Y. Chi, J. Tu, X. Li, C. Shao, Humidity sensing properties of mesoporous iron oxide/silica composite prepared via hydrothermal process, Sens. Actuators B 160 (2011) 334– 340. [39] Q. Qi, T. Zhang, X. Zheng, L. Wan, Preparation and humidity sensing properties of Fedoped mesoporous silica SBA-15, Sens. Actuators B 135 (2008) 255–261 [40] T. Zhang, R. Wang, W. Geng, X. Li, Q. Qi, Y. He, S. Wang, Study on humidity sensing properties based on composite materials of Li-doped mesoporous silica A-SBA-15, Sens. Actuators B 128 (2008) 482–487
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[41] W. Geng, R. Wang, X. Li, Y. Zou, T. Zhang, J. Tu, Y. He, N. Li, Humidity sensitive property of Li-doped mesoporous silica SBA-15, Sens. Actuators B 127 (2007) 323–329
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[42] R. Wang, T. Zhang, Y. He, X. Li, W. Geng, J. Tu, Q. Yuan, Direct-Current and Alternating-Current Analysis of the Humidity-Sensing Properties of Nickel Oxide Doped Polypyrrole Encapsulated in Mesoporous Silica SBA-15, J. App. Polymer Sci. 115 (2010) 3474-3480. [43] D. Grotthuss, Sur la décomposition de l'eau et des corps qu'elle tient en dissolution à l'aide de l'électricité galvanique, Ann. Chim., 58 (1806) 54-73
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d
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[44] P. Christensen, A. Hammett, Techniques and Mechanisms in Electrochemistry, Springer, Netherlands, 1994.
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Table captions: Table 1: Structural and textural properties of mesoporous SBA-15 and SnO2/SBA-15
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nanocomposites.
Table 2: A comparison of humidity sensing properties of hybrid nanocomposites obtained from
Ac ce pt e
d
M
an
us
cr
in-situ and wet impregnation method.
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Page 22 of 39
a0 (nm)b
SBET (m2/g)c
DP (nm)d
VP (cm3/g)e
DW (nm)f
S1
10.7
12.36
733.76
8.82
1.10
3.54
Effective SnO2 wt% (obtained from EDX) --
S2
10.23
11.81
661.28
7.11
1.02
4.7
3.53
5
S3
10.11
11.67
598.17
6.93
0.98
4.74
3.06
5
d100: d-spacing a0: Unit cell parameter [a0 = 2 x d100/√3] c SBET: Total surface area d DP: Pore size e VP: Pore volume f DW: Pore wall thickness [DW = a0 - DP]
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a
Theoritical SnO2 loading (wt%) --
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d100 (nm)a
cr
Sample
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b
Ac ce pt e
d
Table 1
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Page 23 of 39
S2 S3
In-situ Wet impregnation
Order of magnitude change in Impedance in 11-98 %RH range 5.5 4.5
Response time (s)
Recovery time (s)
15 33
21 50
Hysteresis (%)
ip t
Synthesis method
1.5 2.9
cr
Sample
Ac ce pt e
d
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an
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Table 2
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Page 24 of 39
Figure Captions Figure 1: Schematic diagram of fabricated sensor.
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Figure 2: Low angle XRD spectra for samples S1, S2, S3 and S4 (inset). Figure 3: Wide angle XRD spectra for S1, S2, S3 and S4.
cr
Figure 4: adsorption-desorption isotherms curves (a), and their corresponding pore size
us
distributions curves (b), for S1, S2 and S3.
Figure 5: HRTEM image showing uniform channels with long range order of (a) SBA-15, (b)
an
S2 and (c) S3.
Figure 6: FESEM image of nanocomposite S2 and S3 with their corresponding EDX spectra
M
(inset).
Figure 7: Humidity sensing curves showing decrease in impedance with increase in %RH for
d
S1, S2, S3 and S4.
Ac ce pt e
Figure 8: Relationship of impedance and relative humidity based on nanocomposite S2 at various frequencies.
Figure 9: (a) Humidity response (humidification from 11-98 %RH) and recovery (desiccation from 98-11 %RH) curves of S2 and S3.
Figure 10: Hysteresis curve showing adsorption-desorption responses measured in the 11-98 %RH range of S2 and S3
Figure 11: (a) Repeated response and recovery characteristics of S2 measured at consecutive intervals of time in four cycles and (b) The response of S2 monitored at different humidity conditions for 2 months. Figure 12: The measured and simulated complex impedance spectra (Nyquist plot) based on S2, RH varying from 11% to 98%. 25
Page 25 of 39
Author biographies
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Vijay K. Tomer is a research scholar in Department of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, India, doing PhD in the area of mesoporous materials, gas/humidity sensors. He received his M.Tech degree (2012) from Dept. of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, India. His research interests include mesoporous materials for gas and humidity sensors.
Ac ce pt e
d
M
an
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Surender Duhan received his Ph.D. degree (2009) from Guru Jambheshwar University of Science. & Tech., Hisar. Since 2010, he is working as Assistant Professor in Dept. of Materials Science and Nanotechnology, DCR Uni. of Sci. & Tech., Murthal, where he leads a research group dedicated to the synthesis and characterization of functional materials, especially porous metal oxides for applications in gas sensing, catalysis and drug delivery. He has published 37 research papers in reputed International/National Journals including several independent research papers. He is author of six books on Engg. Physics.
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Graphical Abstract (for review)
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Figure-1
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Figure-2
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Figure-3
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Figure-4
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Figure-5
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Figure-6
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Figure-7
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Figure-8
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Figure-9
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Figure-10
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Figure-11
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Figure-12
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