- Email: [email protected]
Solvent-free infiltration method to prepare mesoporous SnO2 templated by SiO2 nanoparticles for ethanol sensing
Sensors and Actuators B 210 (2015) 700–705
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Solvent-free infiltration method to prepare mesoporous SnO2 templated by SiO2 nanoparticles for ethanol sensing Sen Liu a , Yong Zhang a , Bo Yu a , Ziying Wang a , Hongran Zhao a , Nan Zhou a , Tong Zhang a,b,∗ a b
State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, PR China State Key Laboratory of Transducer Technology, Chinese Academy of Sciences, Beijing 100190, PR China
a r t i c l e
i n f o
Article history: Received 17 September 2014 Received in revised form 9 December 2014 Accepted 12 January 2015 Available online 20 January 2015 Keywords: Mesoporous SnO2 Solvent-free infiltration SiO2 nanoparticle Detection of ethanol
a b s t r a c t Mesoporous SnO2 has been successfully prepared by the solvent-free infiltration method using SiO2 nanoparticles as template. The combined characterizations of X-ray diffraction pattern, nitrogen sorption isothermal, and transmission electron microscopy indicate the successful preparation of mesoporous SnO2 . It is found that the mesoporous SnO2 exhibits high response, good selectivity, fast response and recovery rate for detection of ethanol, which are much better than that of bulky SnO2 prepared in the absence of SiO2 nanoparticles. © 2015 Elsevier B.V. All rights reserved.
1. Introduction SnO2 , a typical n-type semiconductor, has attracted considerable attention due to its excellent properties for gas sensing, such as fast response rate, high sensitivity, and highly chemical stability [1–3]. Up to now, SnO2 materials with various structures have been successfully used as sensing materials for detection of ethanol [4], hydrogen [5], carbon monoxide [6], hydrogen sulfide [7], acetone [8], chlorine [9,10] and so on. The SnO2 -based sensing materials prepared by the conventional processes exhibit relatively low surface area, leading to poor sensing performances. It is well known that the structures of sensing materials play an important role in their sensing performances. As a result, much interest has been paid on preparation of SnO2 -based sensing materials with new structure, which has been proven as an effective method for fabrication of high-performances SnO2 -based gas sensors. Among these methods, the introduction of mesoporous structure into SnO2 -based host sensing materials is a good candidate for improvement of the sensing performances. Indeed, mesoporous metal oxides exhibit better sensing performances than the bulky ones [11–14], where the improvement of sensing performance is attributed to the unique mesostructure, such as high surface area, and large pore volume [15,16]. To date, numerous meso-
∗ Corresponding author. Tel.: +86 431 85168385; fax: +86 431 85168270. E-mail address: [email protected] (T. Zhang). http://dx.doi.org/10.1016/j.snb.2015.01.037 0925-4005/© 2015 Elsevier B.V. All rights reserved.
porous SnO2 materials have been successfully constructed for gas sensing. For example, Kawi and co-authors have fabricated H2 sensors using nano-SnO2 loaded mesoporous SiO2 (MCM-41 and SBA-15) as sensing materials [17,18]. However, the presence of SiO2 results in the relatively high resistance of the sensors, limiting their wide application. Furthermore, the soft-template method has also been used to prepare mesoporous SnO2 materials for gas sensing applications, where the soft templates include P123 (EO20 PO70 EO20 ) [13], Brij58 [C16 H33 (OCH2 CH2 )20 OH] [19], C16 PyCl [(C5 H5 NC16 H33 )Cl·H2 O] [20], CTAB [C16 H33 (CH3 )3 NBr] [21], etc. Notably, the sensing performances have been tremendously improved by introduction of mesostructure templated by soft templates. Unfortunately, these mesoporous SnO2 materials exhibit relatively poor thermal stability. Additionally, the use of soft templates also leads to the shortcoming of high cost for preparation of mesoporous SnO2 . To improve the thermal stability of the obtained mesoporous SnO2 , hard-template method has also been developed for preparation of mesoporous SnO2 using mesoporous SiO2 (SBA-15 and KIT-6) as hard templates [22,23]. The mesoporous SnO2 -based materials obtained by the hard-template method have also been used for construction of gas sensors for detection of H2 , ethanol [24,25]. However, these methods exhibit the disadvantages of high cost, complicated experimental process. More recently, self-assembled SiO2 nanoparticles with small particle size have been used for preparation of mesoporous TiO2 crystals, which exhibit excellent optoelectronic device performance [26–28]. To the best of our knowledge, however, few reports
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
on preparation mesoporous metal oxides using small size SiO2 nanoparticles as template for gas sensing applications have been reported so far. In this paper, mesoporous SnO2 has been prepared by solventfree infiltration method using small size SiO2 nanoparticles as template. More importantly, the mesoporous SnO2 exhibits better sensing performances toward the detection of ethanol than that of bulky SnO2 prepared by the similar method in the absence of SiO2 nanoparticles. 2. Experimental 2.1. Materials SnCl2 ·2H2 O, l-lysine, n-octane, NaOH, ethanol, formaldehyde, acetone, and toluene were purchased from Beijing Chemical Co. Tetraethyl orthosilicate (TEOS) was purchased from Tianjin Chemical Co. All chemicals were used as received without further purification. The water used throughout all experiments was purified through a Millipore system.
701
the ceramic tube before it was coated with the paste, and each electrode was connected with two Pt wires. Then a Ni–Cr heating wire was inserted into the tube to form an indirect-heated gas sensor. The details of the sensors fabrication were similar to those reported in our previous literatures [14,30]. Gas sensing properties were examined using a static test system. Saturated target vapor was injected into a test chamber (about 1 L in volume) by a microinjector through a rubber plug. After fully mixed with air (relative humidity was about 25%), the sensor was put into the test chamber. When the response reached a constant value, the sensor was taken out to recover in air. The electrical properties of the sensor were measured by CGS-8 intelligent test meter (China). To improve the contact between the sensing materials and substrate, the sensors were annealed in air at 250 ◦ C for 10 h. The response of the sensor was defined as the ratio of the sensor resistance in dry air (Ra ) to that in target gas (Rg ). The time taken by the sensor to achieve 90% of the total resistance change was defined as the response time in the case of adsorption or the recovery time in the case of desorption.
2.2. Preparation of sensing materials
3. Results and discussion
2.2.1. Preparation of SiO2 nanoparticles SiO2 nanoparticles were prepared by the modified method according to the previous report [29]. In a typical run, 0.146 g of l-lysine was added into 139 g of H2 O, followed by addition of 7.3 g of n-octane. After that, the mixture was heated to 60 ◦ C, and 10.41 g of TEOS was added into the above mixture. After stirring for further 20 h, the mixture was heated to 100 ◦ C and kept statically at 100 ◦ C for 20 h. Then, the solution was directly evaporated in an oven at 100 ◦ C and solid products were obtained. After calcination in air at 600 ◦ C for 3 h for removal of l-lysine and n-octane, SiO2 nanoparticles were obtained.
In this paper, the mesoporous SnO2 was prepared using SiO2 nanoparticles as templates, which were synthesized by hydrolysis of TEOS catalyzed by l-lysine. Scheme 1 shows the scheme to illustrate the preparation of SiO2 nanoparticles and subsequently used as template for preparation of mesoporous SnO2 . The structure of the products was first characterized by XRD technique. Fig. 1 shows the XRD patterns of the samples prepared in the presence and absence of SiO2 . It is seen that both samples exhibit several obvious diffraction peaks at 2 of 26.56◦ , 33.77◦ , 37.80◦ , 51.66◦ , 54.75◦ , 58.03◦ , 61.96◦ , 64.68◦ , 65.99◦ , 71.23◦ and 78.82◦ , which are attributed to the (1 1 0), (1 0 1), (2 0 0), (2 1 1), (2 2 0), (0 0 2), (3 1 0), (1 1 2), (3 0 1), (2 0 2) and (3 2 1) planes of tetragonal rutile SnO2 (JCPDS File No. 41-1445) [31]. It should be noted that no other peaks associated with Sn containing materials are observed, indicating the formation of highly pure SnO2 materials. The average size of mesoporous SnO2 and bulky SnO2 are 13.5 nm and 44.8 nm, respectively, calculated using the Scherrer’s equation based on the strongest diffraction peak of (1 1 0). The Scherrer’s equation is as follows: D = 0.89/ˇ cos , where D is the average diameter of the crystallite, (Cu K␣) = 0.15418 nm and ˇ is the full-width at half-maximum of the diffraction lines [32]. The
2.2.2. Preparation of mesoporous SnO2 Mesoporous SnO2 was prepared by the solvent-free infiltration method using SiO2 nanoparticles as template. In a typical synthesis, 1 g of SiO2 nanoparticles was mixed with 0.5 g of SnCl2 ·2H2 O, followed by heating at 85 ◦ C for 12 h. Then, the mixture was calcined in air at 600 ◦ C for 3 h for conversion of SnCl2 ·2H2 O into SnO2 . After that, the mixture was added into 50 mL of 2 M NaOH solution, followed by stirring for 12 h and this process was repeated for twice. The resulting samples were centrifuged, washed with water and ethanol, and then dried at 60 ◦ C in air. 2.2.3. Preparation of bulky SnO2 For comparison, bulky SnO2 was prepared by calcination of 0.5 g of SnCl2 ·2H2 O in the absence of SiO2 in air at 600 ◦ C for 3 h. 2.3. Characterizations Powder X-ray diffraction (XRD) data were recorded on a RigakuD/MAX 2550 diffractometer with Cu-K␣ radiation ˚ Nitrogen isotherm was obtained at −196 ◦ C with a ( = 1.5418 A). JW-BK 132F analyzer. Samples were prepared for measurement by treating at 150 ◦ C under nitrogen atmosphere for 12 h. Pore size distributions were calculated using Barrett–Joyner–Halenda (BJH) method. Transmission electron microscopy (TEM) measurement was made on a HITACHI H-8100 electron microscopy (Hitachi, Tokyo, Japan) with an accelerating voltage of 200 kV. 2.4. Fabrication and measurement of sensor Sensing materials (mesoporous SnO2 or bulky SnO2 ) were mixed with H2 O in a weight ratio of 4:1 to form a paste. The sensors were obtained by coating the paste onto the ceramic tube to form a sensing film. A pair of gold electrodes was installed at each end of
Scheme 1. A scheme to illustrate the preparation of SiO2 nanoparticles and subsequently using as template for preparation of mesoporous SnO2 .
702
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
Fig. 1. XRD patterns of SnO2 materials prepared in the presence and absence of SiO2 nanoparticles.
relatively small particle size of mesoporous SnO2 leads to improving the number of catalytic active sites of sensing materials, which may be beneficial for enhancing the sensing performances. Fig. 2 shows the N2 sorption isothermal and pore size distribution curve of mesoporous SnO2 thus obtained. It is seen that the sample exhibits a typical hysteresis loop, indicating the formation of mesoporous structure. The formation of mesopores is attributed to the presence of SiO2 nanoparticles during the synthesis process for SnO2 . Fig. 2b shows the pore size distribution curve of mesoporous SnO2 . It is seen that mesoporous SnO2 has uniform mesopores at 30.7 nm, further confirming the formation of mesoporous structure. The BET surface area and pore volume of mesoporous SnO2 are 27 m2 /g and 0.12 cm3 /g, respectively, which are similar with the previous report on preparation of mesoporous TiO2 using SiO2 nanoparticles as templates [28]. Although the BET surface area of mesoporous SnO2 templated by SiO2 nanoparticles is smaller than that of mesoporous SnO2 templated by mesoporous silica, the present method exhibits the advantages of low cost, simple synthesis process. Fig. 3 shows the TEM image of the mesoporous SnO2 , revealing that the samples are consisting of numerous nanoparticles. It is also found that obvious pores are observed between the nanoparticles, confirming the successful preparation of mesoporous SnO2 . It is well known that SnO2 is a promising sensing material for detection of ethanol, and thus, the sensing performances of mesoporous SnO2 toward ethanol are examined. Fig. 4 shows the responses of the sensor based on mesoporous SnO2 to 100 ppm ethanol at operating temperatures ranging from 250 ◦ C to 310 ◦ C. It
Fig. 3. TEM image of mesoporous SnO2 .
Fig. 4. The responses of the sensor based on mesoporous SnO2 to 100 ppm ethanol operating at various temperatures.
Fig. 2. (a) N2 sorption isothermal and (b) pore size distributions of mesoporous SnO2 .
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
703
Fig. 5. The response and recovery curve of the sensors based on (a) mesoporous SnO2 and (b) bulky SnO2 toward 100 ppm ethanol at 280 ◦ C.
Fig. 6. The responses of the sensors based on mesoporous SnO2 toward the ethanol concentrations ranging from 10 ppm to 2000 ppm at 280 ◦ C.
is seen that the responses to 100 ppm ethanol increase with increasing the operating temperature from 250 ◦ C to 280 ◦ C. A further increase of operating temperature leads to decreasing the response. The sensor based on mesoporous SnO2 exhibits the largest response of 4.6–100 ppm ethanol operated at 280 ◦ C. Thus, the following sensing performances were carried out at 280 ◦ C. Fig. 5a shows the response and recovery curve of the sensor based on mesoporous SnO2 toward 100 ppm ethanol at 280 ◦ C. The resistance of the sensor decreases rapidly by placing the sensor into ethanol atmosphere, and recovers fully by placing the sensor into air, indicating the fast response and recovery rate. The response time and recovery time of ethanol thus fabricated are 2 s and 15 s, respectively. The control experiment for using bulky SnO2 as sensing material is also examined and Fig. 5b shows the response and recovery curve of the sensor based on bulky SnO2 toward 100 ppm ethanol at 280 ◦ C. Although the sensor based on bulky SnO2 exhibits a faster recovery time (6 s) to 100 ppm ethanol than that of mesoporous SnO2 (15 s), the response to 100 ppm ethanol at bulky SnO2 (3.17) is much lower than that of mesoporous SnO2 (4.6). The mesoporous SnO2 exhibits higher response to ethanol than that of bulky SnO2 , which is attributed to the unique porous structure of mesoporous materials, where the high surface area and abundant mesostructure could increase the amounts of active sites of the sensing materials. All these observations indicate that the sensing performances can be enhanced by introduction of mesoporous structure using SiO2 nanoparticles as templates. The responses of sensor based on mesoporous SnO2 to various concentrations of ethanol are also examined, as shown in Fig. 6. It is seen that the response of the sensor increases with increasing
Fig. 7. The selectivity of the sensors based on mesoporous SnO2 and bulky SnO2 toward ethanol, toluene, ammonia formaldehyde, nitrogen dioxide, carbon monoxide, chlorine, and acetone, where the gas concentration is 500 ppm and the operating temperature is 280 ◦ C.
the ethanol concentrations from 10 ppm to 2000 ppm, indicating the good responses of the sensor toward ethanol. For exposition of sensor into low ethanol concentrations from 10 ppm to 500 ppm, a good linear between the response to ethanol and concentrations of ethanol is obtained, as shown in inset of Fig. 6. It is well known that the selectivity is also an important factor for high-performance gas sensors, and thus the selectivity of the sensor based on mesoporous SnO2 is also examined. Fig. 7 shows the responses of the sensor based on mesoporous SnO2 and bulky SnO2 to 500 ppm gases, including ethanol, toluene, ammonia, formaldehyde, nitrogen dioxide, carbon monoxide, chlorine, and acetone. Mesoporous SnO2 exhibits a response of 14.5–500 ppm ethanol, which is much higher than other gases, indicating the good selectivity for detection of ethanol. Furthermore, the responses of sensor based on bulky SnO2 to all the gases except acetone are ranging from 1.82 to 4.82, suggesting the relatively poor selectivity for detection of ethanol. It is seen that the response of the sensor based on mesoporous SnO2 toward acetone is higher than that of other gases. However, the response to ethanol of the sensor based on mesoporous SnO2 is also higher than response to acetone. It is well known that the operating temperature plays an important role in the sensing performance for gas sensing. In the present study, relatively low operating temperature for ethanol sensing is obtained by introduction of mesostructure. However, the operating temperature for maximum response toward other gases may
704
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
Acknowledgements This research work was financially supported by the National Natural Science Foundation of China (Grant No. 51202085) and Program for Changjiang Scholars and Innovative Research Team in University (No. IRT3018). The Open Project from State Key Laboratory of Transducer Technology (Granted No. SKT1402). References
Fig. 8. The response and recovery repeatability curve of the sensor based on mesoporous SnO2 to 100 ppm ethanol at 280 ◦ C.
be not quite consistent with that of ethanol. Thus, high selectivity toward ethanol is obtained. All these observations indicate that the selectivity of SnO2 materials could be enhanced by introduction of mesoporous structure. The reproducibility of the sensors based on mesoporous SnO2 is also examined. Fig. 8 shows the response and recovery repeatability curve of the sensor based on mesoporous SnO2 to 100 ppm ethanol at 280 ◦ C. It is seen that the sensor maintains its initial response amplitude without a clear decrease upon three successive sensing tests to 100 ppm ethanol, indicating that the mesoporous SnO2 possesses good repeatability. Furthermore, the long-term stability of the ethanol sensor based on mesoporous SnO2 is also examined by periodical measurements of the sensor responses to 100 ppm ethanol. It is seen that the responses to 100 ppm ethanol are 97%, 95% and 92% of its initial response after the sensors stored for 10, 20 and 30 days, respectively. All these results indicate the good stability of the ethanol sensor based on mesoporous SnO2 . It is well known that SnO2 is a typical n-type semiconductor, and sensing performance is strongly depended on the width of surface depletion layer resulting from oxygen adsorption [33]. When mesoporous SnO2 was exposed in air, the oxygen molecules are adsorbed on the surface of mesoporous SnO2 , resulting in O− and O2 − by capturing electrons from the conduction band of mesoporous SnO2 . As a result, a high-resistance state of mesoporous SnO2 in air is obtained. When the mesoporous SnO2 was exposed into ethanol, the reductive ethanol reacts with the absorbed O− and O2 − , the depleted electrons are fed back into the conductance band of mesoporous SnO2 , resulting in a narrowed depletion layer and therefore the senor resistance is decreased. The sensing mechanism of the mesoporous SnO2 toward ethanol is similar with the previous reported ethanol sensors based on SnO2 [32,34,35]. 4. Conclusion In summary, mesoporous SnO2 templated by SiO2 nanoparticles has been successfully prepared as sensing materials for ethanol sensing. This synthesis method exhibits obvious advantages of low cost, simple synthesizing process, compared to the previously reported soft-template and hard-template methods. Furthermore, the sensing performances have also been enhanced by the formation of porous structure due to the presence of SiO2 nanoparticles during the synthesis process. Our present work is important because it provides an effective method to prepare mesoporous metal oxides for gas sensing applications.
[1] Y. Wang, X. Jiang, Y. Xia, A solution-phase, precursor route to polycrystalline SnO2 nanowires that can be used for gas sensing under ambient conditions, J. Am. Chem. Soc. 125 (2003) 16176–16177. [2] J.-H. Lee, Gas sensors using hierarchical and hollow oxide nanostructures: overview, Sens. Actuators B: Chem. 140 (2009) 319–336. [3] Y. Wang, J.Y. Lee, H.C. Zeng, Polycrystalline SnO2 nanotubes prepared via infiltration casting of nanocrystallites and their electrochemical application, Chem. Mater. 17 (2005) 3899–3903. [4] Y. Zhang, X. He, J. Li, Z. Miao, F. Huang, Fabrication and ethanol-sensing properties of micro gas sensor based on electrospun SnO2 nanofibers, Sens. Actuators B: Chem. 132 (2008) 67–73. [5] T. Hyodo, K. Sasahara, Y. Shimizu, M. Egashira, Preparation of macroporous SnO2 films using PMMA microspheres and their sensing properties to NOx and H2 , Sens. Actuators B: Chem. 106 (2005) 580–590. [6] B. Kim, Y. Lu, A. Hannon, M. Meyyappan, J. Li, Low temperature Pd/SnO2 sensor for carbon monoxide detection, Sens. Actuators B: Chem. 177 (2013) 770–775. [7] S.-J. Choi, B.-H. Jang, S.-J. Lee, B.K. Min, A. Rothschild, I.-D. Kim, Selective detection of acetone and hydrogen sulfide for the diagnosis of diabetes and halitosis using SnO2 nanofibers functionalized with reduced graphene oxide nanosheets, ACS Appl. Mater. Interfaces 6 (2014) 2588–2597. [8] H. Chen, Q. Wang, C. Kou, Y. Sui, Y. Zeng, F. Du, One-pot synthesis and improved sensing properties of hierarchical flowerlike SnO2 assembled from sheet and ultra-thin rod subunits, Sens. Actuators B: Chem. 194 (2013) 447–453. [9] D. Wang, P. Hu, J. Xu, X. Dong, Q. Pan, Fast response chlorine gas sensor based on mesoporous SnO2 , Sens. Actuators B: Chem. 140 (2009) 383–389. [10] H. Wang, J. Xu, Q. Pan, Synthesis and chlorine sensing properties of nanocrystalline hierarchical porous SnO2 by a phenol formaldehyde resin-assisted process, CrystEngComm 12 (2010) 1280–1285. [11] T. Wagner, S. Haffer, C. Weiberger, D. Klaus, M. Tiemann, Mesoporous materials as gas sensors, Chem. Soc. Rev. 42 (2013) 4036–4053. [12] T. Waitz, T. Wagner, T. Sauerwald, C.-D. Kohl, M. Tiemann, Ordered mesoporous In2 O3 : synthesis by structure replication and application as a methane gas sensor, Adv. Funct. Mater. 19 (2009) 653–661. [13] Y. Shimizu, A. Jono, T. Hyodo, M. Egashira, Preparation of large mesoporous SnO2 powder for gas sensor application, Sens. Actuators B: Chem. 108 (2005) 56–61. [14] S. Liu, Z. Wang, H. Zhao, T. Fei, T. Zhang, Ordered mesoporous Co3 O4 for highperformance toluene sensing, Sens. Actuators B: Chem. 197 (2014) 342–349. [15] D. Zhao, J. Feng, Q. Huo, N. Melosh, G.H. Fredrickson, B.F. Chmelka, G.D. Stucky, Triblock copolymer syntheses of mesoporous silica with periodic 50 to 300 angstrom pores, Science 279 (1998) 548–552. [16] S. Liu, H. Zhang, X. Meng, Y. Zhang, L. Ren, F. Nawaz, J. Liu, Z. Li, F.-S. Xiao, Ordered hexagonal mesoporous silica materials (SBA-15) with additional disordered large-mesopore networks formed by gaseous expansion, Microporous Mesoporous Mater. 136 (2010) 126–131. [17] G. Li, S. Kawi, MCM-41 modified SnO2 gas sensors: sensitivity and selectivity properties, Sens. Actuators B: Chem. 59 (1999) 1–8. [18] J. Yang, K. Hidajat, S. Kawi, Synthesis, characterization and sensing properties of nano-SnO2 supported on SBA-15 as highly sensitive semiconductor gas sensors, J. Mater. Chem. 19 (2009) 292–298. [19] N.S. Ramgir, Y.K. Hwang, S.H. Jhung, I.S. Mulla, J.-S. Chang, Effect of Pt concentration on the physicochemical properties and CO sensing activity of mesostructured SnO2 , Sens. Actuators B: Chem. 114 (2006) 275–282. [20] M. Hayashi, T. Hyodo, Y. Shimizu, M. Egashira, Effects of microstructure of mesoporous SnO2 powders on their H2 sensing properties, Sens. Actuators B: Chem. 141 (2009) 465–470. [21] Y. Kuang, G. Chen, X. Lei, L. Luo, X. Sun, Mesoporous assembled SnO2 nanospheres: controlled synthesis, structural analysis and ethanol sensing investigation, Sens. Actuators B: Chem. 181 (2013) 629–636. [22] E. Ramasamy, J. Lee, Ordered mesoporous SnO2 -based photoanodes for high-performance dye-sensitized solar cells, J. Phys. Chem. C 114 (2010) 22032–22037. [23] J.K. Shon, S.S. Kong, Y.S. Kim, J.-H. Lee, W.K. Park, S.C. Park, J.M. Kim, Solvent-free infiltration method for mesoporous SnO2 using mesoporous silica templates, Microporous Mesoporous Mater. 120 (2009) 441–446. [24] J. Zhao, W. Wang, Y. Liu, J. Ma, X. Li, Y. Du, G. Lu, Ordered mesoporous Pd/SnO2 synthesized by a nanocasting route for high hydrogen sensing performance, Sens. Actuators B: Chem. 160 (2011) 604–608. [25] L. Li, H. Lin, F. Qu, Synthesis of mesoporous SnO2 nanomaterials with selective gas-sensing properties, J. Sol–Gel Sci. Technol. 67 (2013) 545–555. [26] E.J.W. Grossland, N. Noel, V. Sivaram, T. Leijtens, J.A. Alexander-Webber, H.J. Snaith, Mesoporous TiO2 single crystals delivering enhanced mobility and optoelectronic device performance, Nature 495 (2013) 215–219.
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705 [27] W. Jiao, Y. Xie, R. Chen, C. Zhen, G. Liu, X. Ma, H.-M. Cheng, Synthesis of mesoporous single crystal rutile TiO2 with improved photocatalytic and photoelectrochemical activities, Chem. Commun. 49 (2013) 11770–11772. [28] X. Zheng, Q. Kuang, K. Yan, Y. Qiu, J. Qiu, S. Yang, Mesoporous TiO2 single crystals: facile shape-, size-, and phase-controlled growth and efficient photocatalytic performance, ACS Appl. Mater. Interfaces 5 (2013) 11249–11257. [29] T. Tokoi, Y. Sakamoto, O. Terasaki, Y. Kubota, T. Okubo, T. Tatsumi, Periodic arrangement of silica nanospheres assisted by amino acids, J. Am. Chem. Soc. 128 (2006) 13664–13665. [30] J. Cao, T. Zhang, F. Li, H. Yang, S. Liu, Enhanced ethanol sensing of SnO2 hollow micro/nanofibers fabricated by coaxial electrospinning, New J. Chem. 37 (2013) 2031–2036. [31] Q. Qi, T. Zhang, L. Liu, X. Zheng, G. Lu, Improved NH3 , C2 H5 OH, and CH3 COCH3 sensing properties of SnO2 nanofibers by adding block copolymer P123, Sens. Actuators B: Chem. 141 (2009) 174–178. [32] L. Wang, S. Wang, Y. Wang, H. Zhang, Y. Kang, W. Huang, Synthesis of hierarchical SnO2 nanostructures assembled with nanosheets and their improved gas sensing properties, Sens. Actuators B: Chem. 188 (2013) 85–93. [33] L. Mei, J. Deng, X. Yin, M. Zhang, Q. Li, E. Zhang, Z. Xu, L. Chen, T. Wang, Ultrasensitive ethanol sensor based on 3D aloe-like SnO2 , Sens. Actuators B: Chem. 166–167 (2012) 7–11. [34] B. Liu, L. Zhang, H. Zhao, Y. Chen, H. Yang, Synthesis and sensing properties of spherical flowerlike architectures assembled with SnO2 submicron rods, Sens. Actuators B: Chem. 173 (2012) 643–651. [35] W. Tang, J. Wang, P. Yao, X. Li, Hollow hierarchical SnO2 –ZnO composite nanofibers with heterostructure based on electrospinning method for detecting methanol, Sens. Actuators B: Chem. 192 (2014) 543–549.
Biographies Sen Liu received his BS degree in 2005 in chemistry and PhD degree in 2010 in inorganic chemistry from Jilin University. During the period of 2010–2012, he worked in Prof. Xuping Sun’s group as a postdoctoral research associate in State Key Lab
705
of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. He joined in College of Electronic Science and Engineering at Jilin University in 2012. Now he is an associate professor in Jilin University and his current research is focused on the nano/micro functional materials and chemical sensors. Yong Zhang received his BS degree from the College of Science, Changchun University of Science and Technology, China in 2011. He received his MS degree from the College of Science, Changchun University of Science and Technology, China in 2014. During MS course, he took part in the joint training program for two years in Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. He entered the PhD course in 2014, majoring in microelectronics and solid-state electronics. His research focuses on the preparation of electrochemical sensor based on nano-micron functional materials. Bo Yu received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2012. As an MS student, his research interests include sensing functional materials and devices. Ziying Wang received her BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2011. He entered the MS course in 2011, majoring in microelectronics and solid-state electronics. She is studying the preparation of gas sensors and flexible strain sensors. Hongran Zhao received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2013. He entered the MS course in 2013, majoring in microelectronics and solid-state electronics. He is studying the humidity-sensitive properties of mesoporous silica composites. Nan Zhou received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2014. His research interests include sensing functional materials for gas sensors. Tong Zhang completed her MS degree in semiconductor materials in 1992 and her PhD in the field of microelectronics and solid-state electronics in 2001 from Jilin University. She was appointed as a full-time professor in the College of Electronics Science and Engineering, Jilin University in 2001. Her research interests are sensing functional materials, gas sensors, and humidity sensors.
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Solvent-free infiltration method to prepare mesoporous SnO2 templated by SiO2 nanoparticles for ethanol sensing Sen Liu a , Yong Zhang a , Bo Yu a , Ziying Wang a , Hongran Zhao a , Nan Zhou a , Tong Zhang a,b,∗ a b
State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun 130012, PR China State Key Laboratory of Transducer Technology, Chinese Academy of Sciences, Beijing 100190, PR China
a r t i c l e
i n f o
Article history: Received 17 September 2014 Received in revised form 9 December 2014 Accepted 12 January 2015 Available online 20 January 2015 Keywords: Mesoporous SnO2 Solvent-free infiltration SiO2 nanoparticle Detection of ethanol
a b s t r a c t Mesoporous SnO2 has been successfully prepared by the solvent-free infiltration method using SiO2 nanoparticles as template. The combined characterizations of X-ray diffraction pattern, nitrogen sorption isothermal, and transmission electron microscopy indicate the successful preparation of mesoporous SnO2 . It is found that the mesoporous SnO2 exhibits high response, good selectivity, fast response and recovery rate for detection of ethanol, which are much better than that of bulky SnO2 prepared in the absence of SiO2 nanoparticles. © 2015 Elsevier B.V. All rights reserved.
1. Introduction SnO2 , a typical n-type semiconductor, has attracted considerable attention due to its excellent properties for gas sensing, such as fast response rate, high sensitivity, and highly chemical stability [1–3]. Up to now, SnO2 materials with various structures have been successfully used as sensing materials for detection of ethanol [4], hydrogen [5], carbon monoxide [6], hydrogen sulfide [7], acetone [8], chlorine [9,10] and so on. The SnO2 -based sensing materials prepared by the conventional processes exhibit relatively low surface area, leading to poor sensing performances. It is well known that the structures of sensing materials play an important role in their sensing performances. As a result, much interest has been paid on preparation of SnO2 -based sensing materials with new structure, which has been proven as an effective method for fabrication of high-performances SnO2 -based gas sensors. Among these methods, the introduction of mesoporous structure into SnO2 -based host sensing materials is a good candidate for improvement of the sensing performances. Indeed, mesoporous metal oxides exhibit better sensing performances than the bulky ones [11–14], where the improvement of sensing performance is attributed to the unique mesostructure, such as high surface area, and large pore volume [15,16]. To date, numerous meso-
∗ Corresponding author. Tel.: +86 431 85168385; fax: +86 431 85168270. E-mail address: [email protected] (T. Zhang). http://dx.doi.org/10.1016/j.snb.2015.01.037 0925-4005/© 2015 Elsevier B.V. All rights reserved.
porous SnO2 materials have been successfully constructed for gas sensing. For example, Kawi and co-authors have fabricated H2 sensors using nano-SnO2 loaded mesoporous SiO2 (MCM-41 and SBA-15) as sensing materials [17,18]. However, the presence of SiO2 results in the relatively high resistance of the sensors, limiting their wide application. Furthermore, the soft-template method has also been used to prepare mesoporous SnO2 materials for gas sensing applications, where the soft templates include P123 (EO20 PO70 EO20 ) [13], Brij58 [C16 H33 (OCH2 CH2 )20 OH] [19], C16 PyCl [(C5 H5 NC16 H33 )Cl·H2 O] [20], CTAB [C16 H33 (CH3 )3 NBr] [21], etc. Notably, the sensing performances have been tremendously improved by introduction of mesostructure templated by soft templates. Unfortunately, these mesoporous SnO2 materials exhibit relatively poor thermal stability. Additionally, the use of soft templates also leads to the shortcoming of high cost for preparation of mesoporous SnO2 . To improve the thermal stability of the obtained mesoporous SnO2 , hard-template method has also been developed for preparation of mesoporous SnO2 using mesoporous SiO2 (SBA-15 and KIT-6) as hard templates [22,23]. The mesoporous SnO2 -based materials obtained by the hard-template method have also been used for construction of gas sensors for detection of H2 , ethanol [24,25]. However, these methods exhibit the disadvantages of high cost, complicated experimental process. More recently, self-assembled SiO2 nanoparticles with small particle size have been used for preparation of mesoporous TiO2 crystals, which exhibit excellent optoelectronic device performance [26–28]. To the best of our knowledge, however, few reports
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
on preparation mesoporous metal oxides using small size SiO2 nanoparticles as template for gas sensing applications have been reported so far. In this paper, mesoporous SnO2 has been prepared by solventfree infiltration method using small size SiO2 nanoparticles as template. More importantly, the mesoporous SnO2 exhibits better sensing performances toward the detection of ethanol than that of bulky SnO2 prepared by the similar method in the absence of SiO2 nanoparticles. 2. Experimental 2.1. Materials SnCl2 ·2H2 O, l-lysine, n-octane, NaOH, ethanol, formaldehyde, acetone, and toluene were purchased from Beijing Chemical Co. Tetraethyl orthosilicate (TEOS) was purchased from Tianjin Chemical Co. All chemicals were used as received without further purification. The water used throughout all experiments was purified through a Millipore system.
701
the ceramic tube before it was coated with the paste, and each electrode was connected with two Pt wires. Then a Ni–Cr heating wire was inserted into the tube to form an indirect-heated gas sensor. The details of the sensors fabrication were similar to those reported in our previous literatures [14,30]. Gas sensing properties were examined using a static test system. Saturated target vapor was injected into a test chamber (about 1 L in volume) by a microinjector through a rubber plug. After fully mixed with air (relative humidity was about 25%), the sensor was put into the test chamber. When the response reached a constant value, the sensor was taken out to recover in air. The electrical properties of the sensor were measured by CGS-8 intelligent test meter (China). To improve the contact between the sensing materials and substrate, the sensors were annealed in air at 250 ◦ C for 10 h. The response of the sensor was defined as the ratio of the sensor resistance in dry air (Ra ) to that in target gas (Rg ). The time taken by the sensor to achieve 90% of the total resistance change was defined as the response time in the case of adsorption or the recovery time in the case of desorption.
2.2. Preparation of sensing materials
3. Results and discussion
2.2.1. Preparation of SiO2 nanoparticles SiO2 nanoparticles were prepared by the modified method according to the previous report [29]. In a typical run, 0.146 g of l-lysine was added into 139 g of H2 O, followed by addition of 7.3 g of n-octane. After that, the mixture was heated to 60 ◦ C, and 10.41 g of TEOS was added into the above mixture. After stirring for further 20 h, the mixture was heated to 100 ◦ C and kept statically at 100 ◦ C for 20 h. Then, the solution was directly evaporated in an oven at 100 ◦ C and solid products were obtained. After calcination in air at 600 ◦ C for 3 h for removal of l-lysine and n-octane, SiO2 nanoparticles were obtained.
In this paper, the mesoporous SnO2 was prepared using SiO2 nanoparticles as templates, which were synthesized by hydrolysis of TEOS catalyzed by l-lysine. Scheme 1 shows the scheme to illustrate the preparation of SiO2 nanoparticles and subsequently used as template for preparation of mesoporous SnO2 . The structure of the products was first characterized by XRD technique. Fig. 1 shows the XRD patterns of the samples prepared in the presence and absence of SiO2 . It is seen that both samples exhibit several obvious diffraction peaks at 2 of 26.56◦ , 33.77◦ , 37.80◦ , 51.66◦ , 54.75◦ , 58.03◦ , 61.96◦ , 64.68◦ , 65.99◦ , 71.23◦ and 78.82◦ , which are attributed to the (1 1 0), (1 0 1), (2 0 0), (2 1 1), (2 2 0), (0 0 2), (3 1 0), (1 1 2), (3 0 1), (2 0 2) and (3 2 1) planes of tetragonal rutile SnO2 (JCPDS File No. 41-1445) [31]. It should be noted that no other peaks associated with Sn containing materials are observed, indicating the formation of highly pure SnO2 materials. The average size of mesoporous SnO2 and bulky SnO2 are 13.5 nm and 44.8 nm, respectively, calculated using the Scherrer’s equation based on the strongest diffraction peak of (1 1 0). The Scherrer’s equation is as follows: D = 0.89/ˇ cos , where D is the average diameter of the crystallite, (Cu K␣) = 0.15418 nm and ˇ is the full-width at half-maximum of the diffraction lines [32]. The
2.2.2. Preparation of mesoporous SnO2 Mesoporous SnO2 was prepared by the solvent-free infiltration method using SiO2 nanoparticles as template. In a typical synthesis, 1 g of SiO2 nanoparticles was mixed with 0.5 g of SnCl2 ·2H2 O, followed by heating at 85 ◦ C for 12 h. Then, the mixture was calcined in air at 600 ◦ C for 3 h for conversion of SnCl2 ·2H2 O into SnO2 . After that, the mixture was added into 50 mL of 2 M NaOH solution, followed by stirring for 12 h and this process was repeated for twice. The resulting samples were centrifuged, washed with water and ethanol, and then dried at 60 ◦ C in air. 2.2.3. Preparation of bulky SnO2 For comparison, bulky SnO2 was prepared by calcination of 0.5 g of SnCl2 ·2H2 O in the absence of SiO2 in air at 600 ◦ C for 3 h. 2.3. Characterizations Powder X-ray diffraction (XRD) data were recorded on a RigakuD/MAX 2550 diffractometer with Cu-K␣ radiation ˚ Nitrogen isotherm was obtained at −196 ◦ C with a ( = 1.5418 A). JW-BK 132F analyzer. Samples were prepared for measurement by treating at 150 ◦ C under nitrogen atmosphere for 12 h. Pore size distributions were calculated using Barrett–Joyner–Halenda (BJH) method. Transmission electron microscopy (TEM) measurement was made on a HITACHI H-8100 electron microscopy (Hitachi, Tokyo, Japan) with an accelerating voltage of 200 kV. 2.4. Fabrication and measurement of sensor Sensing materials (mesoporous SnO2 or bulky SnO2 ) were mixed with H2 O in a weight ratio of 4:1 to form a paste. The sensors were obtained by coating the paste onto the ceramic tube to form a sensing film. A pair of gold electrodes was installed at each end of
Scheme 1. A scheme to illustrate the preparation of SiO2 nanoparticles and subsequently using as template for preparation of mesoporous SnO2 .
702
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
Fig. 1. XRD patterns of SnO2 materials prepared in the presence and absence of SiO2 nanoparticles.
relatively small particle size of mesoporous SnO2 leads to improving the number of catalytic active sites of sensing materials, which may be beneficial for enhancing the sensing performances. Fig. 2 shows the N2 sorption isothermal and pore size distribution curve of mesoporous SnO2 thus obtained. It is seen that the sample exhibits a typical hysteresis loop, indicating the formation of mesoporous structure. The formation of mesopores is attributed to the presence of SiO2 nanoparticles during the synthesis process for SnO2 . Fig. 2b shows the pore size distribution curve of mesoporous SnO2 . It is seen that mesoporous SnO2 has uniform mesopores at 30.7 nm, further confirming the formation of mesoporous structure. The BET surface area and pore volume of mesoporous SnO2 are 27 m2 /g and 0.12 cm3 /g, respectively, which are similar with the previous report on preparation of mesoporous TiO2 using SiO2 nanoparticles as templates [28]. Although the BET surface area of mesoporous SnO2 templated by SiO2 nanoparticles is smaller than that of mesoporous SnO2 templated by mesoporous silica, the present method exhibits the advantages of low cost, simple synthesis process. Fig. 3 shows the TEM image of the mesoporous SnO2 , revealing that the samples are consisting of numerous nanoparticles. It is also found that obvious pores are observed between the nanoparticles, confirming the successful preparation of mesoporous SnO2 . It is well known that SnO2 is a promising sensing material for detection of ethanol, and thus, the sensing performances of mesoporous SnO2 toward ethanol are examined. Fig. 4 shows the responses of the sensor based on mesoporous SnO2 to 100 ppm ethanol at operating temperatures ranging from 250 ◦ C to 310 ◦ C. It
Fig. 3. TEM image of mesoporous SnO2 .
Fig. 4. The responses of the sensor based on mesoporous SnO2 to 100 ppm ethanol operating at various temperatures.
Fig. 2. (a) N2 sorption isothermal and (b) pore size distributions of mesoporous SnO2 .
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
703
Fig. 5. The response and recovery curve of the sensors based on (a) mesoporous SnO2 and (b) bulky SnO2 toward 100 ppm ethanol at 280 ◦ C.
Fig. 6. The responses of the sensors based on mesoporous SnO2 toward the ethanol concentrations ranging from 10 ppm to 2000 ppm at 280 ◦ C.
is seen that the responses to 100 ppm ethanol increase with increasing the operating temperature from 250 ◦ C to 280 ◦ C. A further increase of operating temperature leads to decreasing the response. The sensor based on mesoporous SnO2 exhibits the largest response of 4.6–100 ppm ethanol operated at 280 ◦ C. Thus, the following sensing performances were carried out at 280 ◦ C. Fig. 5a shows the response and recovery curve of the sensor based on mesoporous SnO2 toward 100 ppm ethanol at 280 ◦ C. The resistance of the sensor decreases rapidly by placing the sensor into ethanol atmosphere, and recovers fully by placing the sensor into air, indicating the fast response and recovery rate. The response time and recovery time of ethanol thus fabricated are 2 s and 15 s, respectively. The control experiment for using bulky SnO2 as sensing material is also examined and Fig. 5b shows the response and recovery curve of the sensor based on bulky SnO2 toward 100 ppm ethanol at 280 ◦ C. Although the sensor based on bulky SnO2 exhibits a faster recovery time (6 s) to 100 ppm ethanol than that of mesoporous SnO2 (15 s), the response to 100 ppm ethanol at bulky SnO2 (3.17) is much lower than that of mesoporous SnO2 (4.6). The mesoporous SnO2 exhibits higher response to ethanol than that of bulky SnO2 , which is attributed to the unique porous structure of mesoporous materials, where the high surface area and abundant mesostructure could increase the amounts of active sites of the sensing materials. All these observations indicate that the sensing performances can be enhanced by introduction of mesoporous structure using SiO2 nanoparticles as templates. The responses of sensor based on mesoporous SnO2 to various concentrations of ethanol are also examined, as shown in Fig. 6. It is seen that the response of the sensor increases with increasing
Fig. 7. The selectivity of the sensors based on mesoporous SnO2 and bulky SnO2 toward ethanol, toluene, ammonia formaldehyde, nitrogen dioxide, carbon monoxide, chlorine, and acetone, where the gas concentration is 500 ppm and the operating temperature is 280 ◦ C.
the ethanol concentrations from 10 ppm to 2000 ppm, indicating the good responses of the sensor toward ethanol. For exposition of sensor into low ethanol concentrations from 10 ppm to 500 ppm, a good linear between the response to ethanol and concentrations of ethanol is obtained, as shown in inset of Fig. 6. It is well known that the selectivity is also an important factor for high-performance gas sensors, and thus the selectivity of the sensor based on mesoporous SnO2 is also examined. Fig. 7 shows the responses of the sensor based on mesoporous SnO2 and bulky SnO2 to 500 ppm gases, including ethanol, toluene, ammonia, formaldehyde, nitrogen dioxide, carbon monoxide, chlorine, and acetone. Mesoporous SnO2 exhibits a response of 14.5–500 ppm ethanol, which is much higher than other gases, indicating the good selectivity for detection of ethanol. Furthermore, the responses of sensor based on bulky SnO2 to all the gases except acetone are ranging from 1.82 to 4.82, suggesting the relatively poor selectivity for detection of ethanol. It is seen that the response of the sensor based on mesoporous SnO2 toward acetone is higher than that of other gases. However, the response to ethanol of the sensor based on mesoporous SnO2 is also higher than response to acetone. It is well known that the operating temperature plays an important role in the sensing performance for gas sensing. In the present study, relatively low operating temperature for ethanol sensing is obtained by introduction of mesostructure. However, the operating temperature for maximum response toward other gases may
704
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705
Acknowledgements This research work was financially supported by the National Natural Science Foundation of China (Grant No. 51202085) and Program for Changjiang Scholars and Innovative Research Team in University (No. IRT3018). The Open Project from State Key Laboratory of Transducer Technology (Granted No. SKT1402). References
Fig. 8. The response and recovery repeatability curve of the sensor based on mesoporous SnO2 to 100 ppm ethanol at 280 ◦ C.
be not quite consistent with that of ethanol. Thus, high selectivity toward ethanol is obtained. All these observations indicate that the selectivity of SnO2 materials could be enhanced by introduction of mesoporous structure. The reproducibility of the sensors based on mesoporous SnO2 is also examined. Fig. 8 shows the response and recovery repeatability curve of the sensor based on mesoporous SnO2 to 100 ppm ethanol at 280 ◦ C. It is seen that the sensor maintains its initial response amplitude without a clear decrease upon three successive sensing tests to 100 ppm ethanol, indicating that the mesoporous SnO2 possesses good repeatability. Furthermore, the long-term stability of the ethanol sensor based on mesoporous SnO2 is also examined by periodical measurements of the sensor responses to 100 ppm ethanol. It is seen that the responses to 100 ppm ethanol are 97%, 95% and 92% of its initial response after the sensors stored for 10, 20 and 30 days, respectively. All these results indicate the good stability of the ethanol sensor based on mesoporous SnO2 . It is well known that SnO2 is a typical n-type semiconductor, and sensing performance is strongly depended on the width of surface depletion layer resulting from oxygen adsorption [33]. When mesoporous SnO2 was exposed in air, the oxygen molecules are adsorbed on the surface of mesoporous SnO2 , resulting in O− and O2 − by capturing electrons from the conduction band of mesoporous SnO2 . As a result, a high-resistance state of mesoporous SnO2 in air is obtained. When the mesoporous SnO2 was exposed into ethanol, the reductive ethanol reacts with the absorbed O− and O2 − , the depleted electrons are fed back into the conductance band of mesoporous SnO2 , resulting in a narrowed depletion layer and therefore the senor resistance is decreased. The sensing mechanism of the mesoporous SnO2 toward ethanol is similar with the previous reported ethanol sensors based on SnO2 [32,34,35]. 4. Conclusion In summary, mesoporous SnO2 templated by SiO2 nanoparticles has been successfully prepared as sensing materials for ethanol sensing. This synthesis method exhibits obvious advantages of low cost, simple synthesizing process, compared to the previously reported soft-template and hard-template methods. Furthermore, the sensing performances have also been enhanced by the formation of porous structure due to the presence of SiO2 nanoparticles during the synthesis process. Our present work is important because it provides an effective method to prepare mesoporous metal oxides for gas sensing applications.
[1] Y. Wang, X. Jiang, Y. Xia, A solution-phase, precursor route to polycrystalline SnO2 nanowires that can be used for gas sensing under ambient conditions, J. Am. Chem. Soc. 125 (2003) 16176–16177. [2] J.-H. Lee, Gas sensors using hierarchical and hollow oxide nanostructures: overview, Sens. Actuators B: Chem. 140 (2009) 319–336. [3] Y. Wang, J.Y. Lee, H.C. Zeng, Polycrystalline SnO2 nanotubes prepared via infiltration casting of nanocrystallites and their electrochemical application, Chem. Mater. 17 (2005) 3899–3903. [4] Y. Zhang, X. He, J. Li, Z. Miao, F. Huang, Fabrication and ethanol-sensing properties of micro gas sensor based on electrospun SnO2 nanofibers, Sens. Actuators B: Chem. 132 (2008) 67–73. [5] T. Hyodo, K. Sasahara, Y. Shimizu, M. Egashira, Preparation of macroporous SnO2 films using PMMA microspheres and their sensing properties to NOx and H2 , Sens. Actuators B: Chem. 106 (2005) 580–590. [6] B. Kim, Y. Lu, A. Hannon, M. Meyyappan, J. Li, Low temperature Pd/SnO2 sensor for carbon monoxide detection, Sens. Actuators B: Chem. 177 (2013) 770–775. [7] S.-J. Choi, B.-H. Jang, S.-J. Lee, B.K. Min, A. Rothschild, I.-D. Kim, Selective detection of acetone and hydrogen sulfide for the diagnosis of diabetes and halitosis using SnO2 nanofibers functionalized with reduced graphene oxide nanosheets, ACS Appl. Mater. Interfaces 6 (2014) 2588–2597. [8] H. Chen, Q. Wang, C. Kou, Y. Sui, Y. Zeng, F. Du, One-pot synthesis and improved sensing properties of hierarchical flowerlike SnO2 assembled from sheet and ultra-thin rod subunits, Sens. Actuators B: Chem. 194 (2013) 447–453. [9] D. Wang, P. Hu, J. Xu, X. Dong, Q. Pan, Fast response chlorine gas sensor based on mesoporous SnO2 , Sens. Actuators B: Chem. 140 (2009) 383–389. [10] H. Wang, J. Xu, Q. Pan, Synthesis and chlorine sensing properties of nanocrystalline hierarchical porous SnO2 by a phenol formaldehyde resin-assisted process, CrystEngComm 12 (2010) 1280–1285. [11] T. Wagner, S. Haffer, C. Weiberger, D. Klaus, M. Tiemann, Mesoporous materials as gas sensors, Chem. Soc. Rev. 42 (2013) 4036–4053. [12] T. Waitz, T. Wagner, T. Sauerwald, C.-D. Kohl, M. Tiemann, Ordered mesoporous In2 O3 : synthesis by structure replication and application as a methane gas sensor, Adv. Funct. Mater. 19 (2009) 653–661. [13] Y. Shimizu, A. Jono, T. Hyodo, M. Egashira, Preparation of large mesoporous SnO2 powder for gas sensor application, Sens. Actuators B: Chem. 108 (2005) 56–61. [14] S. Liu, Z. Wang, H. Zhao, T. Fei, T. Zhang, Ordered mesoporous Co3 O4 for highperformance toluene sensing, Sens. Actuators B: Chem. 197 (2014) 342–349. [15] D. Zhao, J. Feng, Q. Huo, N. Melosh, G.H. Fredrickson, B.F. Chmelka, G.D. Stucky, Triblock copolymer syntheses of mesoporous silica with periodic 50 to 300 angstrom pores, Science 279 (1998) 548–552. [16] S. Liu, H. Zhang, X. Meng, Y. Zhang, L. Ren, F. Nawaz, J. Liu, Z. Li, F.-S. Xiao, Ordered hexagonal mesoporous silica materials (SBA-15) with additional disordered large-mesopore networks formed by gaseous expansion, Microporous Mesoporous Mater. 136 (2010) 126–131. [17] G. Li, S. Kawi, MCM-41 modified SnO2 gas sensors: sensitivity and selectivity properties, Sens. Actuators B: Chem. 59 (1999) 1–8. [18] J. Yang, K. Hidajat, S. Kawi, Synthesis, characterization and sensing properties of nano-SnO2 supported on SBA-15 as highly sensitive semiconductor gas sensors, J. Mater. Chem. 19 (2009) 292–298. [19] N.S. Ramgir, Y.K. Hwang, S.H. Jhung, I.S. Mulla, J.-S. Chang, Effect of Pt concentration on the physicochemical properties and CO sensing activity of mesostructured SnO2 , Sens. Actuators B: Chem. 114 (2006) 275–282. [20] M. Hayashi, T. Hyodo, Y. Shimizu, M. Egashira, Effects of microstructure of mesoporous SnO2 powders on their H2 sensing properties, Sens. Actuators B: Chem. 141 (2009) 465–470. [21] Y. Kuang, G. Chen, X. Lei, L. Luo, X. Sun, Mesoporous assembled SnO2 nanospheres: controlled synthesis, structural analysis and ethanol sensing investigation, Sens. Actuators B: Chem. 181 (2013) 629–636. [22] E. Ramasamy, J. Lee, Ordered mesoporous SnO2 -based photoanodes for high-performance dye-sensitized solar cells, J. Phys. Chem. C 114 (2010) 22032–22037. [23] J.K. Shon, S.S. Kong, Y.S. Kim, J.-H. Lee, W.K. Park, S.C. Park, J.M. Kim, Solvent-free infiltration method for mesoporous SnO2 using mesoporous silica templates, Microporous Mesoporous Mater. 120 (2009) 441–446. [24] J. Zhao, W. Wang, Y. Liu, J. Ma, X. Li, Y. Du, G. Lu, Ordered mesoporous Pd/SnO2 synthesized by a nanocasting route for high hydrogen sensing performance, Sens. Actuators B: Chem. 160 (2011) 604–608. [25] L. Li, H. Lin, F. Qu, Synthesis of mesoporous SnO2 nanomaterials with selective gas-sensing properties, J. Sol–Gel Sci. Technol. 67 (2013) 545–555. [26] E.J.W. Grossland, N. Noel, V. Sivaram, T. Leijtens, J.A. Alexander-Webber, H.J. Snaith, Mesoporous TiO2 single crystals delivering enhanced mobility and optoelectronic device performance, Nature 495 (2013) 215–219.
S. Liu et al. / Sensors and Actuators B 210 (2015) 700–705 [27] W. Jiao, Y. Xie, R. Chen, C. Zhen, G. Liu, X. Ma, H.-M. Cheng, Synthesis of mesoporous single crystal rutile TiO2 with improved photocatalytic and photoelectrochemical activities, Chem. Commun. 49 (2013) 11770–11772. [28] X. Zheng, Q. Kuang, K. Yan, Y. Qiu, J. Qiu, S. Yang, Mesoporous TiO2 single crystals: facile shape-, size-, and phase-controlled growth and efficient photocatalytic performance, ACS Appl. Mater. Interfaces 5 (2013) 11249–11257. [29] T. Tokoi, Y. Sakamoto, O. Terasaki, Y. Kubota, T. Okubo, T. Tatsumi, Periodic arrangement of silica nanospheres assisted by amino acids, J. Am. Chem. Soc. 128 (2006) 13664–13665. [30] J. Cao, T. Zhang, F. Li, H. Yang, S. Liu, Enhanced ethanol sensing of SnO2 hollow micro/nanofibers fabricated by coaxial electrospinning, New J. Chem. 37 (2013) 2031–2036. [31] Q. Qi, T. Zhang, L. Liu, X. Zheng, G. Lu, Improved NH3 , C2 H5 OH, and CH3 COCH3 sensing properties of SnO2 nanofibers by adding block copolymer P123, Sens. Actuators B: Chem. 141 (2009) 174–178. [32] L. Wang, S. Wang, Y. Wang, H. Zhang, Y. Kang, W. Huang, Synthesis of hierarchical SnO2 nanostructures assembled with nanosheets and their improved gas sensing properties, Sens. Actuators B: Chem. 188 (2013) 85–93. [33] L. Mei, J. Deng, X. Yin, M. Zhang, Q. Li, E. Zhang, Z. Xu, L. Chen, T. Wang, Ultrasensitive ethanol sensor based on 3D aloe-like SnO2 , Sens. Actuators B: Chem. 166–167 (2012) 7–11. [34] B. Liu, L. Zhang, H. Zhao, Y. Chen, H. Yang, Synthesis and sensing properties of spherical flowerlike architectures assembled with SnO2 submicron rods, Sens. Actuators B: Chem. 173 (2012) 643–651. [35] W. Tang, J. Wang, P. Yao, X. Li, Hollow hierarchical SnO2 –ZnO composite nanofibers with heterostructure based on electrospinning method for detecting methanol, Sens. Actuators B: Chem. 192 (2014) 543–549.
Biographies Sen Liu received his BS degree in 2005 in chemistry and PhD degree in 2010 in inorganic chemistry from Jilin University. During the period of 2010–2012, he worked in Prof. Xuping Sun’s group as a postdoctoral research associate in State Key Lab
705
of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. He joined in College of Electronic Science and Engineering at Jilin University in 2012. Now he is an associate professor in Jilin University and his current research is focused on the nano/micro functional materials and chemical sensors. Yong Zhang received his BS degree from the College of Science, Changchun University of Science and Technology, China in 2011. He received his MS degree from the College of Science, Changchun University of Science and Technology, China in 2014. During MS course, he took part in the joint training program for two years in Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. He entered the PhD course in 2014, majoring in microelectronics and solid-state electronics. His research focuses on the preparation of electrochemical sensor based on nano-micron functional materials. Bo Yu received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2012. As an MS student, his research interests include sensing functional materials and devices. Ziying Wang received her BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2011. He entered the MS course in 2011, majoring in microelectronics and solid-state electronics. She is studying the preparation of gas sensors and flexible strain sensors. Hongran Zhao received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2013. He entered the MS course in 2013, majoring in microelectronics and solid-state electronics. He is studying the humidity-sensitive properties of mesoporous silica composites. Nan Zhou received his BS degree from the College of Electronics Science and Engineering, Jilin University, China in 2014. His research interests include sensing functional materials for gas sensors. Tong Zhang completed her MS degree in semiconductor materials in 1992 and her PhD in the field of microelectronics and solid-state electronics in 2001 from Jilin University. She was appointed as a full-time professor in the College of Electronics Science and Engineering, Jilin University in 2001. Her research interests are sensing functional materials, gas sensors, and humidity sensors.