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Tuning SnO2 architectures with unitary or composite microstructure for the application of gas sensors
Journal of Colloid and Interface Science 462 (2016) 140–147
Contents lists available at ScienceDirect
Journal of Colloid and Interface Science journal homepage: www.elsevier.com/locate/jcis
Tuning SnO2 architectures with unitary or composite microstructure for the application of gas sensors Fuchao Yang a,c, Zhiguang Guo a,b,⇑ a
State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, People’s Republic of China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei University, Wuhan 430062, People’s Republic of China c University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China b
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
SnO2 architectures with unitary or
Different SnO2 architectures with unitary or binary structure were successfully assembled utilizing the assistance of polyvinyl pyrrolidone.
binary structure were tuned by a facile approach. The samples of S1 and S2 with the specific surface area being 10.48 and 18.46 m2/g. Both these two sensors exhibit good selectivity and high sensitiveness. The response time of S2 sensor are both sub-20 s to 100 and 250 ppm ethanol.
a r t i c l e
i n f o
Article history: Received 30 July 2015 Accepted 30 September 2015
Keywords: Polyvinyl pyrrolidone SnO2 Solvothermal process Morphology Gas sensors
a b s t r a c t Different SnO2 architectures with unitary or binary structure were successfully assembled utilizing the assistance of Polyvinyl pyrrolidone (PVP). The microstructure, surface topography, specific surface area and gas sensing property were investigated with X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Brunauer–Emmett–Teller (BET) and WS-60A gas sensing apparatus, respectively. The sensing amplitude, selectivity, response time and recovery time were carefully studied. The possible mechanism of crystallization and gas sensing behavior were also discussed. The present study could be potentially applied to the ethanol or acetone detection and referenced by other researchers and engineers. Ó 2015 Elsevier Inc. All rights reserved.
1. Introduction ⇑ Corresponding author at: State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, People’s Republic of China. Tel.: +86 931 4968105; fax: +86 931 8277088. E-mail address: [email protected] (Z. Guo). http://dx.doi.org/10.1016/j.jcis.2015.09.074 0021-9797/Ó 2015 Elsevier Inc. All rights reserved.
Gas sensors are interesting as they can provide information about the composition of their ambient atmosphere and can detect low concentrations of volatile organic compounds on platforms tiny enough to be used on a microchip [1–3]. Gas sensors made
F. Yang, Z. Guo / Journal of Colloid and Interface Science 462 (2016) 140–147
from metal oxide semiconductors have been fabricated widely owing to the changes in its electrical conductivity under exposure to the test gases. Among plentiful metal oxide semiconductors, the SnO2 (tin dioxide), an important n-type oxide and wide band gap (3.6 eV, at 300 K) semiconductor with high exciton binding energy of 130 meV, is an attractive choice as it shows excellent electrochemical and catalytic activation properties [4–6]. The sensing performance of SnO2 gas sensors are manifestly influenced by size distribution, microstructure, exposed facets and surface state (surface defects and surface adsorption) [5,7]. As the particles size decrease, the fraction of atoms at the surface and surface-to-volume ratio increase. The SnO2 with higher surface-to-volume ratios can make its electrical properties more sensitive to surface-adsorbed target analytes. So the capabilities to control over the morphology and surface state are the key to achieve desirable gas sensors. There are many approaches we can choose to rational design and construct the morphology and surface state. Various techniques have been developed for the controlled synthesis of functional materials with special morphology, such as hydrothermal method [8,9], electrochemical method [10], template method [11] and magnetron sputtering method [12]. Materials with special morphology can also be achieved by tuning the reaction condition, i.e., the concentration of precursors [8,13], reaction temperature [9] and reaction time [14]. The surfacecapped agent also plays an important role in the appearances of final products [15,16]. Leu et al. introduce polyvinyl pyrrolidone (PVP) to the photochemical deposition process for resolving the problem of nanoparticle agglomeration [17]. Zhang et al. have demonstrated that PVP played a crucial role both in stabilizing Pd nanoparticles and in anchoring Pd nanoparticles onto the surfaces of ZnO nanowires [18]. These excellent works inspire us to use PVP directly as structure directing agent which can be assisted in generating the specific microstructure. In addition, the high temperature and high pressure of solvothermal condition influence the ostwald ripening process and the driving force for nucleation, crystal growth, coagulation, and flocculation [19,20]. So the PVP assisted synthesis of SnO2 with or without solvothermal process were studied in a comparative view. 2. Materials and method 2.1. Synthesis of SnO2 architectures The synthesis method of PVP assisted SnO2 was briefly given as follows. All chemicals used in the synthesized and gas sensing measurement process were analytic grade reagents without further purification. The 5 mmol SnCl2 (free of crystal water) and 0.05 mmol Polyvinyl pyrrolidone (PVP, Mr = 10,000, 0.5 g) were dissolved in 10 ml ethanol. Then the 1 ml ammonia water was added dropwise into the above solution during stirring. Subsequently, the mixed solution was continually stirred at room temperature for 2 h. The SnO2 product marked as S1 was obtained by annealing in a furnace at 600 °C for 2 h. For the SnO2 product marked as S2, the mixed solution after abundant mixing was transferred to the polytetrafluoroethylene-lined stainless autoclave. The autoclave was sealed and maintained at 200 °C for 6 h and then cooled down to room temperature naturally. The S2 product was washed by ethanol, dried at 60 °C, and then calcined at 600 °C for 2 h in air.
of 20–90° (2h). The sample’s morphological characteristics were investigated by Field emission scanning electron microscopy (FESEM, JSM-6701F) and transmission electron microscopy (TEM, FEI TEVNAI G2 TF20). TEM samples were prepared by dropping SnO2 suspensions on a copper TEM grid which was deposited by a thin amorphous carbon film. The specific surface area were characterized by the single point Brunauer–Emmet–Teller (BET) method through N2 adsorption/desorption using ASAP 2010, USA Micromeritics. The UV–vis absorbance spectrum was measured at room temperature employing a UV–vis spectrophotometer (Agilent, Cary 60). 2.3. Fabrication of gas sensors and the sensing measurements The as-prepared SnO2 powder was mixed with droplets of deionized water to form paste and then coated onto the surface of a ceramic tube on which a pair of gold electrodes was previously printed. The sensor elements were aged at 60 °C for a week and at operating temperature (about 300 °C) for 1 h to improve its stability. Then a Ni–Cr heating coil was inserted through the ceramic tube to provide a side-heated gas sensor. These are also iconically shown by Fig. 1. The working temperatures can be adjusted by tuning the heating voltage. Further details about the basic testing electrical circuit can be found in our previous work [21]. Gas sensing apparatus applied in our experiment is WS-60A, as shown in Fig. S1. (Resolution ratio: 1 mV, Wei Sheng Electronics Science and Technology Co., Ltd.). The gas response value is defined as Ra/Rg where Ra and Rg are the resistance in air and in target gases, respectively. The response or recovery time, indicating the adhesion degree of gas molecules on the SnO2 sensing material, are abbreviated as TRes and TRec and can be defined as 90% saturation after injecting or removing the target gas [22–24].
3. Results and discussion In Fig. 2, the crystal structure of SnO2 investigated by XRD was present. All diffraction peaks can be well indexed to the tetragonal rutile SnO2 phase (JCPDS No. 41-1445, a = b = 4.738 Å and c = 3.187 Å). The highest diffraction peak at 26.58° is indexed to the (1 1 0) crystal orientation, which indicates the (1 1 0) plane preferred orientation. The relative intensity of (1 0 1) diffraction peak with 2h located at 33.96° was enhanced by the solvothermal process. The dominated (1 1 0) and (1 0 1) diffraction peaks of both
2.2. Characterization The powder X-ray diffraction (XRD) patterns of the SnO2 samples were recorded by the X’PERT PRO diffractometer with Cu Ka radiation (k = 1.5418 Å). The patterns were recorded at the range
141
Fig. 1. Photographs and schematic illustrations of gas sensor element.
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S1 and S2 samples show strong and narrow shape, which reveals the good crystallinity of the SnO2 nanostructure [25]. Fig. 3a and b shows the FESEM images of the intermedium (homogeneous polysolute system after sufficient blending) before annealing process with a different magnification. It can be seen that the nanoparticles with the diameter of about 20–100 nm are packed compactly. Fig. 3c and d shows the final product of PVP assisted SnO2 without (S1: c) or with (S2: d) solvothermal process. It is clear seen that there are lots of pore spaces in both S1 and S2 samples after the annealing procedure. The S1 sample exhibit the unitary microstructure: the accumulation of nanoparticles while the S2 sample show the composite architectures: the aggregation of nanoparticles and the smooth micro-sheets. The above observation was further confirmed by the following TEM characterization, as shown in Fig. 4. For the S1, the corallike nanoparticles with an average diameter of 20–60 nm were observed in Fig. 4a. As that for S2, the typical micro-sheets with different thickness and sizes were found in Fig. 4b. The high resolution TEM (HRTEM) images show the difference between S1 and S2: the interplanar distance of S1 can be indistinctly seen while that of S2 is clear enough. The bottom right corner of Fig. 4d shows the ten times lattice distance (3.393 nm), corresponding to the (1 1 0) planes of tetragonal rutile SnO2. The standard value of ten times (1 1 0) interplanar distance is 3.347 nm (JCPDS No. 411445) as a comparison to our experimental result. The electron diffraction pattern of S2 sample was given in Fig. S2 (ESI). For the plausible formation mechanism of SnO2 with unitary or binary microstructure, the roles of PVP and solvothermal process have been taken into account as illustrated in Fig. 5. For the purpose of contrast, the FESEM images of SnO2 synthetized without using any surface-capped agent were given in Fig. S3 (ESI). The effect of other structure directing agent (cetyltrimethyl ammonium bromide, CTAB) on the morphology of the SnO2 was also investigated, shown in Fig. S4 (ESI). On account of the difference in morphology between these reaction conditions, we propose that the polymer, PVP with a backbone of polyvinyl as hydrophobic groups and several pendants of pyrrolidone as hydrophilic groups, provides interaction with solvent and favorable sites for particulate assemblies [4,17]. When the PVP was added into the pristine precursor ethanol solution, the SnCl2 molecule would be scattered and decorated on the polymer chain. Plus, the viscosity of the precursor solution increases and this will retard the subsequent diffusion rate of NH3H2O and the reaction rate with Sn2+. This is beneficial to growing into the spherical nanoparticles owing to the sufficient growth time. While the solution consisting of the precursor nuclei [Sn(OH)4]2 endure the solvothermal process, the high temperature and high press facilitate the collision of nuclei, accelerate
Fig. 2. XRD patterns of PVP assisted synthesis SnO2 without (S1) or with solvothermal process (S2).
the chemical reaction rate and boost these atoms aggregate and the formation of sheets. During the sintered process at 600 °C for 2 h, kinds of gas in limited space, such as NH3, HCl, CH3CH2OH and H2O, were released, resulting in the formation of porous structure [26]. After the sintered procedure, the organic impurity of PVP is removed and the crystallization of our SnO2 samples is promoted [27]. Large specific surface area and well-defined pore can provide enough active sites and are also beneficial to the mass transportation of target analytes on the surface of gas sensors [28–30]. To gather BET surface area regarding on the S1 and S2 samples, the N2 adsorption and desorption isotherms and pore size distribution measurements are conducted. As shown in Fig. 6a and b, hysteresis loops of S1 at the p/p0 ranges of 0.75–0.98 and S2 at the p/p0 ranges of 0.70–0.99 are associated with the filling and emptying of the mesopores by capillary condensation [29]. The increase in adsorbed volume at higher relative pressures indicates interparticle porosity [31]. These shapes of curves display type IV isotherms according to the IUPAC classification, which is the characteristic isotherm of mesoporous materials [28,29]. The results reveal that the surface area of S1 and S2 are 10.48 and 18.46 m2/g, correspondingly. The pore size distribution of the S1 and S2 shows that two peaks appear in pore size region of 7.2–30.5 nm and 14.9–30.3 nm. Fig. 6c shows the UV–vis absorption spectra of as-synthesized S1 and S2 using ethanol as the medium, which illustrate that the sample S2 possessing a higher absorbance than S1 at the ultraviolet and most visible light region (220–600 nm). The absorption spectrum of the S1 and S2 suspension displays an absorption peak at 249.9 nm, suggesting that quantum confinement effect present in SnO2 [32]. Based on the data point of absorption spectrum, the optical band gap of S1 and S2 are found to be around 3.20 and 3.12 eV, as shown in Fig. S5 (ESI). Moreover, the energy dispersive spectroscopy (EDS) was employed for embarking the presence of Sn and O components and confirming the purity of final product of SnO2 sample, as shown in Fig. 6d [33]. The gas sensing performances of the as-prepared S1 and S2 samples were conducted. Fig. 7a shows the effect of different operating temperature on response behaviors of S1 and S2 sensors to 100 ppm ethanol. The results show that the highest response value can be obtained at 340 °C for S1 and 370 °C for S2. The dynamic resistance change of S1 sensor (or S2 sensor) is shown in Fig. 7b (or Fig. 7c) when exposed to ethanol target gas at the concentration of 100 and 250 ppm with the working temperature of 360 °C. The process of response is dyed into blue region while the process of recovery is colored by green region. The TRes and TRec are important characteristics for evaluating the performance of practicable gas sensors [34,35]. As for S1 sensor, the TRes and TRec are 10.2 and 24.0s to 100 ppm ethanol, and are 15.4 and 31.4s to 250 ppm ethanol. As for S2 sensor, the TRes and TRec are 19.3 and 76.0 s to 100 ppm ethanol, and are 18.7 and 122.4s to 250 ppm ethanol. The selectivity of these sensors was also demonstrated by exposing these sensors to 100 ppm of six different kinds of gases (ethanol, acetone, benzene, benzaldehyde, benzyl alcohol and toluene) at 260 °C, as shown in Fig. 7d. The sensitivity of S1 to ethanol (5.55) is 3.96 times as to toluene (1.40). The sensitivity of S2 to ethanol (6.19) is 4.24 times as to toluene (1.46). The response state of S1 sensor (or S2 sensor) is shown in Fig. 7e (or Fig. 7f) when the sensors exposed to ethanol gas at the concentration of 100 and 250 ppm, and at the working temperature of 360 °C. According to these two graphs, the response values of S1 are 11.4–100 ppm ethanol and 28.9–250 ppm ethanol while that of S2 are 14.2– 100 ppm ethanol and 42.5–250 ppm ethanol. Acetone is high volatile and common in laboratory and workplace. Unfortunately, it has anesthetic effects on the central nervous system and may damage the liver, kidney and pancreas
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Fig. 3. FESEM images of the intermedium before annealing process (a), (b) in a different magnification and the final product of S1 (c) and S2 (d).
Fig. 4. TEM and HRTEM morphologies of PVP assisted synthesis SnO2 without solvothermal process (a) and (c); or with solvothermal process (b) and (d).
[36]. So the study on acetone sensor is of great importance. Fig. 8 shows the typical dynamic response curves of the S1 and S2 sensors to acetone as a function of concentration varying from 10 to 2000 ppm at 260 °C. It is represented that the response values rise periodically and sharply with the injecting and increasing of the acetone concentration. For 10 ppm acetone gas, the response value of S1 is 1.42 and the response value of S2 is 1.51. For 600 ppm acetone gas, the response value of S1 is 3.96 and the response value of S2 is 5.4. As the concentration of acetone gas increasing to 2000 ppm, the response value of S1 is 6.94 and the response value of S2 is 8.4. It also returns to the baseline at regular intervals
indicating the acetone exhaust out. This reversible response is of great concern in practical application [37,38]. We also investigate the gas sensing properties of SnO2 with unitary or binary microstructures for detecting toluene at different concentration, as shown in Fig. 9 and Table S1 (ESI). As the concentration of toluene increase from 10 to 2000 ppm, the response value of both S1 and S2 sensors increase very slowly (S1: 1.23–1.53 and S2: 1.29–1.75). Some fluctuation can also be found in this graph. In general, oxide semiconductor sensors often show relatively low responses to benzene, toluene, and aromatic hydrocarbons with benzene rings [39]. This is because the break
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Fig. 5. Schematic diagrams for the potential growth mechanism of S1 and S2.
Fig. 6. Typical N2 adsorption–desorption isotherm and BJH pore size distribution curves of S1 (a) and S2 (b). (c) UV–visible absorption spectra and photographs of S1 and S2 dispersed in ethanol. (d) The spectrum of energy dispersive spectrometer indicating the detectable elements of S1 and S2.
of well-ordered benzene ring usually requires more activation energy. There is another way of looking the low response to benzene, which offer low cross-responses to detect ethanol or acetone. The response of S1 and S2 gas sensors can be understood by the following potential mechanism as shown in Fig. 10. When the sensors are heated at working temperature, more electrons of SnO2 sensor will jump to the conduction band (Ec) from valence band (Ev) with the assistance of energy originating from thermal vibration. When our SnO2 sensors are exposed to the air, these electrons are transferred from the SnO2 sensor to the physisorbed oxygen resulting in the formation of adsorbed oxygen ions which are charged and electrostatically stabilized on the SnO2 surface. The following simplified reactions have been suggested for the forma 2 tion of chemisorbed oxygen ions (O ) [40–42]. 2 , O and O
O2 þ eCB ! O2
ð1Þ
O2 þ 2eCB ! 2O
ð2Þ
O2 þ 4eCB ! 2O2
ð3Þ
These adsorbed ions would scatter electrons within the Debye length [43], result in widening space-charge layer with reduced electron mobility and evolve the high-impedance-state of sensors since the conductivity of SnO2 is largely dependent on the concentration of electrons, as a typical n-type semiconductor. When our SnO2 sensors are exposed to the reducing gas, such as ethanol, acetone, benzene, benzaldehyde, benzyl alcohol and toluene, the radical ions (O and O2) would facilitate the oxidization of 2, O organic molecules adsorbed on the surface of sensors, accompanying with feeding back the electrons into the conduction band [16,44]. Take the ethanol and O2 for example, this process can be understood as follow:
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Fig. 7. (a) Response of gas sensors made from S1 and S2 to 100 ppm ethanol at different operating temperatures. The dynamic resistance change and response-recovery curves of S1 sensor (b) and S2 sensor (c) to 100 and 250 ppm ethanol at 360 °C. (d) Response of SnO2 sensors to different tested gases at 260 °C. The response status of S1 sensor (e) and S2 sensor (f) to different concentrations ethanol at 360 °C.
Fig. 8. The typical dynamic response curves of S1 and S2 sensors to different concentrations of acetone at the operating temperature of 260 °C.
Fig. 9. The variation tendency of response values of S1 and S2 sensors versus different concentrations of toluene at the operating temperature of 260 °C.
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Fig. 10. Schematic diagram for gas sensing mechanism of the as-synthesized SnO2 gas sensors.
CH3 CH2 OH þ 6O2 ! 2CO2 þ 3H2 O þ 12eCB
Appendix A. Supplementary material
This shows that there are appreciable increases of electron density in conduction band, and so we observed the decrease of resistance and the response status. On the base of the previous analysis, we explore the reason for the difference of response amplitude between S1 and S2 sensors. The amplitude of response is decided by the species and amount of adsorbed oxygen ions undergone the chemical reactions. The 2 kinds of adsorbed oxygen ions, O , largely depend on 2 , O or O the operating temperature [43,45]. When the S1 and S2 sensors detect the same target analyte at the fixed working temperature, the quantities of adsorbed oxygen ion are the key factor. The binary composite microstructure consisting of nanoparticles and microsheets is more favorable to the formation of step sites, in which activated oxygen ions would like to reside [46]. Moreover, the S2 sample possesses higher surface area and porosity, which are conducive to the diffusion, adsorption and desorption of target gas molecules. So we observe a higher sensitivity values form S2 than that of S1 sensor.
Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jcis.2015.09.074.
4. Conclusion In summary, we report a simple one-step solution route combined with a subsequent calcining process for the preparation of unitary SnO2 nanoparticles with the surface area being 10.48 m2/g. While the additional solvothermal process is scheduled before calcination, the SnO2 with composite morphology consisting of nanoparticles and micro-sheets was constructed and its BET surface area was 18.46 m2/g. The gas sensing measurement results show that the highest response value (14.7 for S1 and 15.6 for S2) to 100 ppm ethanol can be obtained at 340 °C and 370 °C. When exposed to 100 ppm ethanol at 360 °C, the TRes and TRec of S1 sensor are 10.2 and 24.0 s, and the TRes and TRec of S2 sensor are 19.3 and 76 s. The sensitivity of S1 to ethanol is 3.96 times as to toluene while that of S2 to ethanol is 4.24 times as to toluene. The reducing analytes are sensed by monitoring the electrical conductance variations, attributing to the adsorbing or desorbing electron-trapping oxygen species.
Acknowledgements This work is supported by the National Nature Science Foundation of China (Nos. 51522510 and 21203217), the ‘‘Funds for Distinguished Young Scientists” of Hubei Province (No. 2012FFA002), the Co-joint Project of Chinese Academy of Sciences, the ‘‘Top Hundred Talents” Program of Chinese Academy of Sciences and the National 973 Project (2013CB632300) for financial support.
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Tuning SnO2 architectures with unitary or composite microstructure for the application of gas sensors Fuchao Yang a,c, Zhiguang Guo a,b,⇑ a
State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, People’s Republic of China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials, Hubei University, Wuhan 430062, People’s Republic of China c University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China b
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
SnO2 architectures with unitary or
Different SnO2 architectures with unitary or binary structure were successfully assembled utilizing the assistance of polyvinyl pyrrolidone.
binary structure were tuned by a facile approach. The samples of S1 and S2 with the specific surface area being 10.48 and 18.46 m2/g. Both these two sensors exhibit good selectivity and high sensitiveness. The response time of S2 sensor are both sub-20 s to 100 and 250 ppm ethanol.
a r t i c l e
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Article history: Received 30 July 2015 Accepted 30 September 2015
Keywords: Polyvinyl pyrrolidone SnO2 Solvothermal process Morphology Gas sensors
a b s t r a c t Different SnO2 architectures with unitary or binary structure were successfully assembled utilizing the assistance of Polyvinyl pyrrolidone (PVP). The microstructure, surface topography, specific surface area and gas sensing property were investigated with X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Brunauer–Emmett–Teller (BET) and WS-60A gas sensing apparatus, respectively. The sensing amplitude, selectivity, response time and recovery time were carefully studied. The possible mechanism of crystallization and gas sensing behavior were also discussed. The present study could be potentially applied to the ethanol or acetone detection and referenced by other researchers and engineers. Ó 2015 Elsevier Inc. All rights reserved.
1. Introduction ⇑ Corresponding author at: State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, People’s Republic of China. Tel.: +86 931 4968105; fax: +86 931 8277088. E-mail address: [email protected] (Z. Guo). http://dx.doi.org/10.1016/j.jcis.2015.09.074 0021-9797/Ó 2015 Elsevier Inc. All rights reserved.
Gas sensors are interesting as they can provide information about the composition of their ambient atmosphere and can detect low concentrations of volatile organic compounds on platforms tiny enough to be used on a microchip [1–3]. Gas sensors made
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from metal oxide semiconductors have been fabricated widely owing to the changes in its electrical conductivity under exposure to the test gases. Among plentiful metal oxide semiconductors, the SnO2 (tin dioxide), an important n-type oxide and wide band gap (3.6 eV, at 300 K) semiconductor with high exciton binding energy of 130 meV, is an attractive choice as it shows excellent electrochemical and catalytic activation properties [4–6]. The sensing performance of SnO2 gas sensors are manifestly influenced by size distribution, microstructure, exposed facets and surface state (surface defects and surface adsorption) [5,7]. As the particles size decrease, the fraction of atoms at the surface and surface-to-volume ratio increase. The SnO2 with higher surface-to-volume ratios can make its electrical properties more sensitive to surface-adsorbed target analytes. So the capabilities to control over the morphology and surface state are the key to achieve desirable gas sensors. There are many approaches we can choose to rational design and construct the morphology and surface state. Various techniques have been developed for the controlled synthesis of functional materials with special morphology, such as hydrothermal method [8,9], electrochemical method [10], template method [11] and magnetron sputtering method [12]. Materials with special morphology can also be achieved by tuning the reaction condition, i.e., the concentration of precursors [8,13], reaction temperature [9] and reaction time [14]. The surfacecapped agent also plays an important role in the appearances of final products [15,16]. Leu et al. introduce polyvinyl pyrrolidone (PVP) to the photochemical deposition process for resolving the problem of nanoparticle agglomeration [17]. Zhang et al. have demonstrated that PVP played a crucial role both in stabilizing Pd nanoparticles and in anchoring Pd nanoparticles onto the surfaces of ZnO nanowires [18]. These excellent works inspire us to use PVP directly as structure directing agent which can be assisted in generating the specific microstructure. In addition, the high temperature and high pressure of solvothermal condition influence the ostwald ripening process and the driving force for nucleation, crystal growth, coagulation, and flocculation [19,20]. So the PVP assisted synthesis of SnO2 with or without solvothermal process were studied in a comparative view. 2. Materials and method 2.1. Synthesis of SnO2 architectures The synthesis method of PVP assisted SnO2 was briefly given as follows. All chemicals used in the synthesized and gas sensing measurement process were analytic grade reagents without further purification. The 5 mmol SnCl2 (free of crystal water) and 0.05 mmol Polyvinyl pyrrolidone (PVP, Mr = 10,000, 0.5 g) were dissolved in 10 ml ethanol. Then the 1 ml ammonia water was added dropwise into the above solution during stirring. Subsequently, the mixed solution was continually stirred at room temperature for 2 h. The SnO2 product marked as S1 was obtained by annealing in a furnace at 600 °C for 2 h. For the SnO2 product marked as S2, the mixed solution after abundant mixing was transferred to the polytetrafluoroethylene-lined stainless autoclave. The autoclave was sealed and maintained at 200 °C for 6 h and then cooled down to room temperature naturally. The S2 product was washed by ethanol, dried at 60 °C, and then calcined at 600 °C for 2 h in air.
of 20–90° (2h). The sample’s morphological characteristics were investigated by Field emission scanning electron microscopy (FESEM, JSM-6701F) and transmission electron microscopy (TEM, FEI TEVNAI G2 TF20). TEM samples were prepared by dropping SnO2 suspensions on a copper TEM grid which was deposited by a thin amorphous carbon film. The specific surface area were characterized by the single point Brunauer–Emmet–Teller (BET) method through N2 adsorption/desorption using ASAP 2010, USA Micromeritics. The UV–vis absorbance spectrum was measured at room temperature employing a UV–vis spectrophotometer (Agilent, Cary 60). 2.3. Fabrication of gas sensors and the sensing measurements The as-prepared SnO2 powder was mixed with droplets of deionized water to form paste and then coated onto the surface of a ceramic tube on which a pair of gold electrodes was previously printed. The sensor elements were aged at 60 °C for a week and at operating temperature (about 300 °C) for 1 h to improve its stability. Then a Ni–Cr heating coil was inserted through the ceramic tube to provide a side-heated gas sensor. These are also iconically shown by Fig. 1. The working temperatures can be adjusted by tuning the heating voltage. Further details about the basic testing electrical circuit can be found in our previous work [21]. Gas sensing apparatus applied in our experiment is WS-60A, as shown in Fig. S1. (Resolution ratio: 1 mV, Wei Sheng Electronics Science and Technology Co., Ltd.). The gas response value is defined as Ra/Rg where Ra and Rg are the resistance in air and in target gases, respectively. The response or recovery time, indicating the adhesion degree of gas molecules on the SnO2 sensing material, are abbreviated as TRes and TRec and can be defined as 90% saturation after injecting or removing the target gas [22–24].
3. Results and discussion In Fig. 2, the crystal structure of SnO2 investigated by XRD was present. All diffraction peaks can be well indexed to the tetragonal rutile SnO2 phase (JCPDS No. 41-1445, a = b = 4.738 Å and c = 3.187 Å). The highest diffraction peak at 26.58° is indexed to the (1 1 0) crystal orientation, which indicates the (1 1 0) plane preferred orientation. The relative intensity of (1 0 1) diffraction peak with 2h located at 33.96° was enhanced by the solvothermal process. The dominated (1 1 0) and (1 0 1) diffraction peaks of both
2.2. Characterization The powder X-ray diffraction (XRD) patterns of the SnO2 samples were recorded by the X’PERT PRO diffractometer with Cu Ka radiation (k = 1.5418 Å). The patterns were recorded at the range
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Fig. 1. Photographs and schematic illustrations of gas sensor element.
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S1 and S2 samples show strong and narrow shape, which reveals the good crystallinity of the SnO2 nanostructure [25]. Fig. 3a and b shows the FESEM images of the intermedium (homogeneous polysolute system after sufficient blending) before annealing process with a different magnification. It can be seen that the nanoparticles with the diameter of about 20–100 nm are packed compactly. Fig. 3c and d shows the final product of PVP assisted SnO2 without (S1: c) or with (S2: d) solvothermal process. It is clear seen that there are lots of pore spaces in both S1 and S2 samples after the annealing procedure. The S1 sample exhibit the unitary microstructure: the accumulation of nanoparticles while the S2 sample show the composite architectures: the aggregation of nanoparticles and the smooth micro-sheets. The above observation was further confirmed by the following TEM characterization, as shown in Fig. 4. For the S1, the corallike nanoparticles with an average diameter of 20–60 nm were observed in Fig. 4a. As that for S2, the typical micro-sheets with different thickness and sizes were found in Fig. 4b. The high resolution TEM (HRTEM) images show the difference between S1 and S2: the interplanar distance of S1 can be indistinctly seen while that of S2 is clear enough. The bottom right corner of Fig. 4d shows the ten times lattice distance (3.393 nm), corresponding to the (1 1 0) planes of tetragonal rutile SnO2. The standard value of ten times (1 1 0) interplanar distance is 3.347 nm (JCPDS No. 411445) as a comparison to our experimental result. The electron diffraction pattern of S2 sample was given in Fig. S2 (ESI). For the plausible formation mechanism of SnO2 with unitary or binary microstructure, the roles of PVP and solvothermal process have been taken into account as illustrated in Fig. 5. For the purpose of contrast, the FESEM images of SnO2 synthetized without using any surface-capped agent were given in Fig. S3 (ESI). The effect of other structure directing agent (cetyltrimethyl ammonium bromide, CTAB) on the morphology of the SnO2 was also investigated, shown in Fig. S4 (ESI). On account of the difference in morphology between these reaction conditions, we propose that the polymer, PVP with a backbone of polyvinyl as hydrophobic groups and several pendants of pyrrolidone as hydrophilic groups, provides interaction with solvent and favorable sites for particulate assemblies [4,17]. When the PVP was added into the pristine precursor ethanol solution, the SnCl2 molecule would be scattered and decorated on the polymer chain. Plus, the viscosity of the precursor solution increases and this will retard the subsequent diffusion rate of NH3H2O and the reaction rate with Sn2+. This is beneficial to growing into the spherical nanoparticles owing to the sufficient growth time. While the solution consisting of the precursor nuclei [Sn(OH)4]2 endure the solvothermal process, the high temperature and high press facilitate the collision of nuclei, accelerate
Fig. 2. XRD patterns of PVP assisted synthesis SnO2 without (S1) or with solvothermal process (S2).
the chemical reaction rate and boost these atoms aggregate and the formation of sheets. During the sintered process at 600 °C for 2 h, kinds of gas in limited space, such as NH3, HCl, CH3CH2OH and H2O, were released, resulting in the formation of porous structure [26]. After the sintered procedure, the organic impurity of PVP is removed and the crystallization of our SnO2 samples is promoted [27]. Large specific surface area and well-defined pore can provide enough active sites and are also beneficial to the mass transportation of target analytes on the surface of gas sensors [28–30]. To gather BET surface area regarding on the S1 and S2 samples, the N2 adsorption and desorption isotherms and pore size distribution measurements are conducted. As shown in Fig. 6a and b, hysteresis loops of S1 at the p/p0 ranges of 0.75–0.98 and S2 at the p/p0 ranges of 0.70–0.99 are associated with the filling and emptying of the mesopores by capillary condensation [29]. The increase in adsorbed volume at higher relative pressures indicates interparticle porosity [31]. These shapes of curves display type IV isotherms according to the IUPAC classification, which is the characteristic isotherm of mesoporous materials [28,29]. The results reveal that the surface area of S1 and S2 are 10.48 and 18.46 m2/g, correspondingly. The pore size distribution of the S1 and S2 shows that two peaks appear in pore size region of 7.2–30.5 nm and 14.9–30.3 nm. Fig. 6c shows the UV–vis absorption spectra of as-synthesized S1 and S2 using ethanol as the medium, which illustrate that the sample S2 possessing a higher absorbance than S1 at the ultraviolet and most visible light region (220–600 nm). The absorption spectrum of the S1 and S2 suspension displays an absorption peak at 249.9 nm, suggesting that quantum confinement effect present in SnO2 [32]. Based on the data point of absorption spectrum, the optical band gap of S1 and S2 are found to be around 3.20 and 3.12 eV, as shown in Fig. S5 (ESI). Moreover, the energy dispersive spectroscopy (EDS) was employed for embarking the presence of Sn and O components and confirming the purity of final product of SnO2 sample, as shown in Fig. 6d [33]. The gas sensing performances of the as-prepared S1 and S2 samples were conducted. Fig. 7a shows the effect of different operating temperature on response behaviors of S1 and S2 sensors to 100 ppm ethanol. The results show that the highest response value can be obtained at 340 °C for S1 and 370 °C for S2. The dynamic resistance change of S1 sensor (or S2 sensor) is shown in Fig. 7b (or Fig. 7c) when exposed to ethanol target gas at the concentration of 100 and 250 ppm with the working temperature of 360 °C. The process of response is dyed into blue region while the process of recovery is colored by green region. The TRes and TRec are important characteristics for evaluating the performance of practicable gas sensors [34,35]. As for S1 sensor, the TRes and TRec are 10.2 and 24.0s to 100 ppm ethanol, and are 15.4 and 31.4s to 250 ppm ethanol. As for S2 sensor, the TRes and TRec are 19.3 and 76.0 s to 100 ppm ethanol, and are 18.7 and 122.4s to 250 ppm ethanol. The selectivity of these sensors was also demonstrated by exposing these sensors to 100 ppm of six different kinds of gases (ethanol, acetone, benzene, benzaldehyde, benzyl alcohol and toluene) at 260 °C, as shown in Fig. 7d. The sensitivity of S1 to ethanol (5.55) is 3.96 times as to toluene (1.40). The sensitivity of S2 to ethanol (6.19) is 4.24 times as to toluene (1.46). The response state of S1 sensor (or S2 sensor) is shown in Fig. 7e (or Fig. 7f) when the sensors exposed to ethanol gas at the concentration of 100 and 250 ppm, and at the working temperature of 360 °C. According to these two graphs, the response values of S1 are 11.4–100 ppm ethanol and 28.9–250 ppm ethanol while that of S2 are 14.2– 100 ppm ethanol and 42.5–250 ppm ethanol. Acetone is high volatile and common in laboratory and workplace. Unfortunately, it has anesthetic effects on the central nervous system and may damage the liver, kidney and pancreas
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Fig. 3. FESEM images of the intermedium before annealing process (a), (b) in a different magnification and the final product of S1 (c) and S2 (d).
Fig. 4. TEM and HRTEM morphologies of PVP assisted synthesis SnO2 without solvothermal process (a) and (c); or with solvothermal process (b) and (d).
[36]. So the study on acetone sensor is of great importance. Fig. 8 shows the typical dynamic response curves of the S1 and S2 sensors to acetone as a function of concentration varying from 10 to 2000 ppm at 260 °C. It is represented that the response values rise periodically and sharply with the injecting and increasing of the acetone concentration. For 10 ppm acetone gas, the response value of S1 is 1.42 and the response value of S2 is 1.51. For 600 ppm acetone gas, the response value of S1 is 3.96 and the response value of S2 is 5.4. As the concentration of acetone gas increasing to 2000 ppm, the response value of S1 is 6.94 and the response value of S2 is 8.4. It also returns to the baseline at regular intervals
indicating the acetone exhaust out. This reversible response is of great concern in practical application [37,38]. We also investigate the gas sensing properties of SnO2 with unitary or binary microstructures for detecting toluene at different concentration, as shown in Fig. 9 and Table S1 (ESI). As the concentration of toluene increase from 10 to 2000 ppm, the response value of both S1 and S2 sensors increase very slowly (S1: 1.23–1.53 and S2: 1.29–1.75). Some fluctuation can also be found in this graph. In general, oxide semiconductor sensors often show relatively low responses to benzene, toluene, and aromatic hydrocarbons with benzene rings [39]. This is because the break
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Fig. 5. Schematic diagrams for the potential growth mechanism of S1 and S2.
Fig. 6. Typical N2 adsorption–desorption isotherm and BJH pore size distribution curves of S1 (a) and S2 (b). (c) UV–visible absorption spectra and photographs of S1 and S2 dispersed in ethanol. (d) The spectrum of energy dispersive spectrometer indicating the detectable elements of S1 and S2.
of well-ordered benzene ring usually requires more activation energy. There is another way of looking the low response to benzene, which offer low cross-responses to detect ethanol or acetone. The response of S1 and S2 gas sensors can be understood by the following potential mechanism as shown in Fig. 10. When the sensors are heated at working temperature, more electrons of SnO2 sensor will jump to the conduction band (Ec) from valence band (Ev) with the assistance of energy originating from thermal vibration. When our SnO2 sensors are exposed to the air, these electrons are transferred from the SnO2 sensor to the physisorbed oxygen resulting in the formation of adsorbed oxygen ions which are charged and electrostatically stabilized on the SnO2 surface. The following simplified reactions have been suggested for the forma 2 tion of chemisorbed oxygen ions (O ) [40–42]. 2 , O and O
O2 þ eCB ! O2
ð1Þ
O2 þ 2eCB ! 2O
ð2Þ
O2 þ 4eCB ! 2O2
ð3Þ
These adsorbed ions would scatter electrons within the Debye length [43], result in widening space-charge layer with reduced electron mobility and evolve the high-impedance-state of sensors since the conductivity of SnO2 is largely dependent on the concentration of electrons, as a typical n-type semiconductor. When our SnO2 sensors are exposed to the reducing gas, such as ethanol, acetone, benzene, benzaldehyde, benzyl alcohol and toluene, the radical ions (O and O2) would facilitate the oxidization of 2, O organic molecules adsorbed on the surface of sensors, accompanying with feeding back the electrons into the conduction band [16,44]. Take the ethanol and O2 for example, this process can be understood as follow:
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Fig. 7. (a) Response of gas sensors made from S1 and S2 to 100 ppm ethanol at different operating temperatures. The dynamic resistance change and response-recovery curves of S1 sensor (b) and S2 sensor (c) to 100 and 250 ppm ethanol at 360 °C. (d) Response of SnO2 sensors to different tested gases at 260 °C. The response status of S1 sensor (e) and S2 sensor (f) to different concentrations ethanol at 360 °C.
Fig. 8. The typical dynamic response curves of S1 and S2 sensors to different concentrations of acetone at the operating temperature of 260 °C.
Fig. 9. The variation tendency of response values of S1 and S2 sensors versus different concentrations of toluene at the operating temperature of 260 °C.
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Fig. 10. Schematic diagram for gas sensing mechanism of the as-synthesized SnO2 gas sensors.
CH3 CH2 OH þ 6O2 ! 2CO2 þ 3H2 O þ 12eCB
Appendix A. Supplementary material
This shows that there are appreciable increases of electron density in conduction band, and so we observed the decrease of resistance and the response status. On the base of the previous analysis, we explore the reason for the difference of response amplitude between S1 and S2 sensors. The amplitude of response is decided by the species and amount of adsorbed oxygen ions undergone the chemical reactions. The 2 kinds of adsorbed oxygen ions, O , largely depend on 2 , O or O the operating temperature [43,45]. When the S1 and S2 sensors detect the same target analyte at the fixed working temperature, the quantities of adsorbed oxygen ion are the key factor. The binary composite microstructure consisting of nanoparticles and microsheets is more favorable to the formation of step sites, in which activated oxygen ions would like to reside [46]. Moreover, the S2 sample possesses higher surface area and porosity, which are conducive to the diffusion, adsorption and desorption of target gas molecules. So we observe a higher sensitivity values form S2 than that of S1 sensor.
Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jcis.2015.09.074.
4. Conclusion In summary, we report a simple one-step solution route combined with a subsequent calcining process for the preparation of unitary SnO2 nanoparticles with the surface area being 10.48 m2/g. While the additional solvothermal process is scheduled before calcination, the SnO2 with composite morphology consisting of nanoparticles and micro-sheets was constructed and its BET surface area was 18.46 m2/g. The gas sensing measurement results show that the highest response value (14.7 for S1 and 15.6 for S2) to 100 ppm ethanol can be obtained at 340 °C and 370 °C. When exposed to 100 ppm ethanol at 360 °C, the TRes and TRec of S1 sensor are 10.2 and 24.0 s, and the TRes and TRec of S2 sensor are 19.3 and 76 s. The sensitivity of S1 to ethanol is 3.96 times as to toluene while that of S2 to ethanol is 4.24 times as to toluene. The reducing analytes are sensed by monitoring the electrical conductance variations, attributing to the adsorbing or desorbing electron-trapping oxygen species.
Acknowledgements This work is supported by the National Nature Science Foundation of China (Nos. 51522510 and 21203217), the ‘‘Funds for Distinguished Young Scientists” of Hubei Province (No. 2012FFA002), the Co-joint Project of Chinese Academy of Sciences, the ‘‘Top Hundred Talents” Program of Chinese Academy of Sciences and the National 973 Project (2013CB632300) for financial support.
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