Hierarchical Morphology-Dependent Gas-Sensing Performances of

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Hierarchical morphology-dependent gas-sensing performances of three-dimensional SnO2 nanostructures Yi-Xiang Li, Zheng Guo, Yao Su, Xiao-Bo Jin, Xianghu Tang, Jiarui Huang, Xing-Jiu Huang, Minqiang Li, and Jinhuai Liu ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.6b00597 • Publication Date (Web): 08 Dec 2016 Downloaded from http://pubs.acs.org on December 10, 2016

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Hierarchical performances

morphology-dependent of

gas-sensing

three-dimensional

SnO2

nanostructures Yi-Xiang Li,†,‡ Zheng Guo,†,‡,* Yao Su,†,‡ Xiao-Bo Jin,† Xiang-Hu Tang,† Jia-Rui Huang,§ Xing-Jiu Huang,†,‡ ,* Min-Qiang Li,†,‡ Jin-Huai Liu†,‡,*

†

Nanomaterials and Environmental Detection Laboratory, Institute of Intelligent

Machines, Chinese Academy of Sciences, Hefei 230031, PR China

‡

Department of Chemistry, University of Science and Technology of China, Hefei

230026, PR China

§

Department of Chemistry, Anhui Normal University, Wuhu 241000, PR China

*Correspondence should be addressed to Z. Guo, X.-J. Huang, J.-H. Liu. E-mail: [email protected] (Z.G.); [email protected] (X.J.H); [email protected] (J.H.L) Tel.: +86-551-5591167; fax: +86-551-5592420.

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Abstract Hierarchical

morphology-dependent

gas-sensing

performances

have

been

demonstrated for three-dimensional SnO2 nanostructures. First, hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets have been synthesized via a facile and one-step hydrothermal approach. Due to thermal instability of hierarchical nanosheets, they are gradually shrunk into cone-shaped nanostructures and finally deduced into rod-shaped ones under a thermal treatment. Given the intrinsic advantages of three-dimensional hierarchical nanostructures, their gas-sensing properties have been further explored. The results indicate that their sensing behaviors are greatly related with their hierarchical morphologies. Among the achieved hierarchical morphologies, three-dimensional cone-shaped hierarchical SnO2 nanostructures display the highest relative response up to about 175 toward 100 ppm of acetone as an example. Furthermore, they also exhibit good sensing responses toward other typical volatile organic compounds (VOCs). Microstructured analyses suggest that these results are mainly ascribed to the formation of more active surface defects and mismatches for the cone-shaped hierarchical nanostructures during the process of thermal recrystallization. Promisingly, this surface-engineering strategy can be extended to prepare other three-dimensional metal oxide hierarchical nanostructures with good gas-sensing performances.

KEYWORDS:

hierarchical nanostructure, gas-sensing performance, SnO2,

volatile organic compounds, surface-engineering strategy


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Due to the large active surface area, nanostructured semiconductor metal oxides have been received great attention in many fields, especially for gas sensors.1-3 Over the past several decades, considerable efforts have been devoted to preparing their various nanostructures, such as nanoparticles, nanowires, nanorods, nanobelts and nanotubes, etc.4-16 Employing these nanostructures as sensing units, indeed their gas-sensing performances have been greatly enhanced in contrast to the bulk structures. However, not all nanostructures can effectively contribute to the gas-sensing response among the sensing film composed of them. Owing to the natural reduction of the overall surface energy, these nanostructures are generally packed together. Undoubtedly such densely packed structures are detrimental for the diffuse of the detected gases into the surface of internal nanostructures, weakening their intrinsic sensing performances.17 Hence, it is a critical and hot topic for developing high-performance gas sensors to explore how to design nanostructures exposed with high active surfaces and make full use of the sensing activity of all nanostructures among the sensing film. Aiming to the above issue, various methods have been developed.18-21 Among them, an effective and promising approach is to assemble nanoparticles, nanorods, nanowires, nanosheets of metal oxides into three-dimensional hierarchical nanostructures.22-26 This special morphology can not only offer the large active surface area, but also form well-aligned porous structures.20 Clearly, the former will greatly enhance their relative response. Simultaneously, the latter is favorable for the diffuse of the detected gases into/out the sensing film, improving the response and recovery time. Initiated from this view, three-dimensional hierarchical nanostructured


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metal oxides have been intensively prepared and used to fabricate gas sensors. For instance, Wu et al. have demonstrated that hierarchical SnO2 nanostructures assembled with intermingled ultrathin nanosheets presented the tremendous gas sensing performances toward ethanol.27 The nanosheet-assembled hierarchical flower-like ZnO nanostructures showed excellent gas sensing properties towards acetone.28 In2O3 hierarchical microspheres consisted of irregular nanorods exhibited high response and good selectivity to NO2 at low working temperature.29 Hierarchical Cu2O hollow microspheres organized by nanocrystals displayed higher sensitivity towards ethanol in contrast to nanocrystallites and solid microspheres under the same working conditions.30 Additionally, three-dimensional WO3 nanowire networks as a high-surface area sensing materials have been shown high sensitivity and selectivity towards NO2 with a detection limit of 50 ppb.31 Evidently, these aforementioned hierarchical nanostructures have well supported their intrinsic advantages as gas-sensing materials. However, previous reports are mainly confined in the preparation of their novel hierarchical nanostructures and characterization of their gas-sensing properties. To date, few reports have been involved to manipulating the hierarchical morphology of three-dimensional nanostructured metal oxides and further improving their gas sensing performances. As is well-known, the gas sensing responses of semiconductor metal oxides arise from the chemical and physical interaction between the detected gases and their exposed surfaces.32-35 Apart from preparing metal oxides with the large surface area and porosity to enhance their gas-sensing performances, to design them with high


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active exposed surfaces have been gradually involved into the scope of scientist’s research interests. For example, Xie and coworkers controllably synthesized SnO2 octahedral nanoparticles with exposed high-energy {211} facets, realizing the great enhancement of gas-sensing performance over ethanol.36 Kim et al irradiated SnO2 nanowires with He ions to generate surface defects comprised of Sn interstitials, successfully achieving the selective improvement of NO2 gas sensing behavior.37 High active surfaces (high-energy facets and surface defects, etc) facilitate the adsorption of the detected gases, which is crucial in enhancing the sensing behavior.38 Inspired by the above strategy and the intrinsic advantages of hierarchical nanostructures, herein an alternative route has been offered to develop high-performance gas sensors. That is to manipulate the hierarchical morphology with high sensing activity for three-dimensional hierarchical nanostructures. First, three-dimensional SnO2 hierarchical nanostructures assembled with ultrathin shuttle-shaped nanosheets have been synthesized as a representative gas-sensing nanomaterial. Through a facial strategy of the thermal treatment, the instable ultrathin shuttle-shaped nanosheets can be deduced into cone-shaped and rod-shaped nanostructures due to their further recrystallization. Corresponding to the morphological evolution of their hierarchical nanostructures, the hierarchical morphology-dependent gas-sensing behaviors have been demonstrated. Annealed at about 500 ºC, the obtained three-dimensional cone-shaped hierarchical SnO2 nanostructures presents the best gas-sensing responses with a good stability and repeatability toward acetone, ethanol, and isopropanol, etc. To illuminate the native


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mechanism, microstructured analyses have been preformed for their hierarchical nanostructures, indicating that it is mainly attributed to the formation of crystal defects and mismatches. Expectedly, this surface-engineering strategy can be extended to prepare other hierarchical metal oxide nanostructures with excellent gas sensing performances.

Experimental section Preparation of three-dimensional hierarchical SnO2 nanostructures. Typically, three-dimensional hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets were synthesized as follows. First, SnCl2·2H2O powders (0.282 g) were dissolved into an aqueous solution (35 ml) containing PEG-200 (3 ml) with magnetic stirring for about 30 min. Then an aqueous solution (5 ml) containing NaOH (0.3 g) was dropped into the above prepared homogeneous solution under vigorous magnetic stirring at room temperature. After continuously stirred for about 60 min, the achieved suspension was transferred into a Teflon-lined stainless steel autoclave (50 ml). Afterward the sealed autoclave was put into an oven at 160 ºC for 24 h. Finally, the weak yellow products of hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets were obtained by centrifugation, followed by washing with distilled water and ethanol for several times. Subsequently, the hierarchical morphology evolutions were investigated for the achieved three-dimensional SnO2 nanostructures under the thermal treatment. At the annealing


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temperature of 500 ºC and 600 ºC, they were transformed into three-dimensional cone-shaped and rod-shaped hierarchical nanostructures, respectively. Characterization of as-prepared samples. The morphologies and microstructures of as-prepared samples were examined with a Quanta 200 FEG scanning electron microscope (SEM), and their transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) analyses were performed using a JEOL-2010 transmission electron microscope with selected area electron diffraction (SAED) and an attached EDX system. X-ray diffraction (XRD) patterns of all samples were taken on a Philips X’pert diffractometer (X’Pert Pro MPD) with Cu Kα radiation (1.5418 Å). Fabrication and measurements of gas-sensing devices. To fabricate gas-sensing devices, alumina ceramic tubes (1 mm in length and 4 mm in diameter) were employed as substrates. On its outer surface, two interdigital Au electrodes fabricated by screen-printing are used for measuring the electrical characters of the sensing film. A Ni–Cr resistor is employed as a heater to provide the working temperature in the inner alumina ceramic tube. The whole fabrication process is shown in Figure S1 (Seen from supporting information). First, as-prepared three-dimensional hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets were dispersed into an appropriate amount of ethanol under ultrasonication. Then the achieved suspension solution was coated on the outer surface of the alumina ceramic tube and dried in air, forming a sensing film. Afterward three-dimensional hierarchical SnO2 nanostructures were in-situ calcined on the fabricated sensing devices at


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different temperatures for 60 min in air. To investigate their gas-sensing performances, a Keithley 6487 picoameter/voltage sourcemeter was served as both voltage source and current reader. All gas sensing measurements were performed in the dry air by our previously reported setup and program.11, 19, 39 The concentrated saturated organic vapours corresponding to different VOCs were introduced by an injection needle into the testing chamber. As is well-known, their concentrations of saturated organic vapours are known under a standard atmospheric pressure at the specific temperature. So a relatively precise concentration of VOCs can be obtained in the testing chamber through manipulating the volume of their injected saturated vapours. After measurements, all fabricated sensors were also kept in the dry air. The relative response was defined as S = Ra/Rg, where, Ra is the resistance in dry air and Rg is that in the dry air mixed with detected gases. The results of the gas-sensing properties were obtained from the repeated measurements of three or more sensors of each type, which were shown in the form of Error bars standing for standard deviation.

Results and discussion Based on the described synthetic approach in the experimental section, three-dimensional SnO2 hierarchical nanostructures have been prepared. From a low magnified SEM image shown in Figure 1a, it can be seen that as-prepared samples are all with flower-like nanostructures, which is relatively uniform in their diameters of about 500-800 nm. High magnified SEM image presented in Figure 1b reveals that they are assembled with numerous nanosheets. SEM image of individual hierarchical


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nanostructure further confirms this special morphology, displayed in the inset of Figure 1b. Seen from a typical TEM image in Figure 1c, the above same results are also well supported. Clearly, the achieved hierarchical structures are all shuttle-shaped nanosheets, which is randomly assembled together to form flower-like morphology. To obtain more information, high magnified flat and cross sectional TEM images of individual hierarchical nanostructure, corresponding to two selected areas in Figure 1c, are performed and displayed in Figure 1d and Figure 1e, respectively. Clearly the shuttle-shaped nanosheet is about 200 nm in length and 80 nm in half-width. Its thickness is ultrathin about 8 nm. Notably, the formed hierarchical shuttle-shaped nanosheet is single crystalline, which can be inferred from their SEAD patterns shown in the insets of Figure 1d and Figure 1e. Moreover, the preferred formation directions are both same for two randomly selected hierarchical nanostructures. As shown in Figure 1f, the elemental composition is analyzed by EDX spectrum, suggesting that the strong peaks of O and Sn come from as-prepared three-dimensional hierarchical nanostructures besides the weak peak of Si arising from Si substrate. XRD pattern in Figure 1g demonstrates that all emerged diffraction peaks of as-prepared samples are completely indexed to a tetragonal rutile structure of SnO2 (JCPDS: 41-1445) without observing any other diffraction peaks, indicating the high purity of as-prepared products is achieved. Before measuring the gas-sensing properties, an approach of thermal treatment is often performed to activate semiconductor metal oxide nanomaterials, satisfying the requirement of crystalline and structural stability.40-41 Similarly, the same approach


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has been also employed to treat as-prepared three-dimensional hierarchical nanostructured SnO2. Interestingly, the evolutions of their hierarchical nanostructures have been observed with the annealed temperatures in air, which has not been reported in the previous reports. Figure 2a shows the whole schematic process of their morphological evolutions. With the increase of annealed temperatures in air, initial hierarchical shuttle-shaped nanosheets are gradually deduced into cone-shaped hierarchical nanostructures and even to nanorods. This result can be concluded from the morphology of individual three-dimensional SnO2 hierarchical nanostructure annealed at different temperatures, as show in Figure 2b-2i. Their corresponding low magnified SEM images are shown in Figure S2 (Seen from supporting information). At low annealed temperatures of 300 оC, 350 оC and 400 оC, the initial morphologies of hierarchical nanostructures described in Figure 2b are fundamentally retained, as shown in Figure 2c, 2d and 2e, respectively. When the annealed temperature increases to 450 оC, it can be seen from Figure 2f that their morphologies are gradually changed. Up to 500 оC, Figure 2g shows that they are fundamentally transformed into cone-shaped ones. Continuously increasing to 550 оC in Figure 2h, they are gradually deduced into rod-shaped hierarchical nanostructures. As it is up to 600 оC, hierarchical nanorods are completely formed, which can be observed in Figure 2i. This phenomenon of the above hierarchical morphological evolution is attributed to their thermal recrystallization because of instability of ultrathin shuttle-shaped nanosheet. Based on their XRD patterns shown in Figure S3 (Seen from supporting information), all diffraction peaks of SnO2 are gradually strengthened


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with the continuous increase of the annealed temperature. It means that as-prepared samples are recrystallized via a thermal treatment, leading to the morphological evolutions without the change of composition. Inspired by the intrinsic advantages of three-dimensional hierarchical nanostructures, their gas-sensing performances have been investigated. First, the working temperature as a critical effect on gas-sensing performances is optimized through employing acetone (100 ppm) as a representative one of typical harmful VOCs. Figure S4 (Seen from supporting information) displays the corresponding plot of relative response toward 100 ppm of acetone as a function of working temperature for three-dimensional cone-shaped hierarchical SnO2 nanostructures. It can be found that the maximum response value is achieved at the working temperature of about 325 оC. Thus, we choose 325 оC as the optimal working temperature for the subsequent gas-sensing measurements. As is well-known, gas-sensing properties greatly depend on the morphologies of metal oxide semiconductors. Combined with the morphological evolution of their hierarchical structures, a series of samples achieved at different annealed temperatures have been employed to fabricate gas-sensing devices. The measured results clearly demonstrate the hierarchical nanostructured morphology-dependent gas-sensing behaviors. As can be seen from Figure 3a, with the increase of the annealed temperature from room temperature to 500 оC, the relative responses of the achieved samples greatly increase from 60 up to about 175 toward 100 ppm of acetone with the morphological evolution from shuttle-shaped nanosheets to cone-shaped ones. However, annealed at higher temperature than 500


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о

C, their relative responses rapidly decrease. Up to 600 оC, it is down to about 32,

corresponding to rod-shaped hierarchical nanostructures. Obviously the cone-shaped hierarchical nanostructures obtained at the annealed temperature of 500 оC exhibit the best sensing response. Subsequently, the sensing responses of SnO2 with the above three typical hierarchical nanostructures have been explored toward different concentrations of acetone at the optimal working temperature. According to the relationships between response and concentration of acetone presented in Figure 3b, it can be obviously observed that the relative response of cone-shaped hierarchical nanostructured SnO2 significantly increases with the increase of the concentration of acetone. Compared with initial shuttle-shaped and rod-shaped morphology, the incensement of their response to concentration is higher, meaning that it shows a highest gas-sensing response. It further supports the above results shown in Figure 3a. For cone-shaped hierarchical SnO2 nanostructures, their real-time response curves toward different concentration of acetone presented in Figure 4. For shuttle-shaped and rod-shaped ones, their curves are displayed in Figure S5a and S5b (Seen from supporting information), respectively. As described in Figure 4a, it can be seen that all of them exhibit fast response and recovery. Of particular importance, three-dimensional SnO2 cone-shaped hierarchical nanostructures also shows good response to low concentration of acetone in the range from 50 ppb to 2.5 ppm, which can be observed from Figure 4b. These results should be ascribed to the intrinsic advantages of three-dimensional hierarchical nanostructures. As described in the inset of Figure 4b, their special morphology is favorable for the diffusion of acetone


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molecules to effectively interact with all SnO2 nanostructures, leading to greatly improve its relative response. Notably, when the concentration of acetone is down to 50 ppb, it still shows an obvious relative response. Therefore, it can be expectedly applied for noninvasive diagnosis of human type-I diabetes, considering acetone as one of its generally accepted biomarkers with low concentration.42 To illuminate the intrinsic reason of the above hierarchical nanostructured morphology-dependent gas-sensing behaviors, detailed analyses of microstructures have been systematically performed for the morphological evolutions of hierarchical nanostructures. In Figure 5a-5c, TEM images of three typical morphologies of hierarchical SnO2 nanostructures have been displayed, corresponding to as-prepared samples and annealed at 500 оC and 600 оC, respectively. The evolution of hierarchical nanostructures is well consistent with the results observed from their corresponding SEM images. In Figure 5d-5f, high magnified TEM images of their individual hierarchical nanostructure have also been presented. Clearly they evolved from shuttled-shaped nanosheets to cone-shaped ones and to nanorods, analogous to the scheme in their corresponding insets. From their HRTEM images shown in Figure 5g and 5i, single crystalline structures with well regular crystal lattice are demonstrated for as-prepared SnO2 with shuttled-shaped nanosheets and the obtained nanorods annealed at 600 °C. Notably, for the cone-shaped hierarchical nanostructures achieved at the annealing temperature of 500 °C, defects and mismatches are formed on their surfaces, as indicated by the white dotted line in Figure 5h. Previous theoretical and experimental reports have demonstrated that metal oxide surface with


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defects and mismatches is more active than regular one.43-46 Accordingly, VOCs molecules are easily absorbed, activated and reacted on their surfaces. Inferred from the above analysis, it can be concluded that defects and mismatches of the cone-shaped hierarchical structures are critical for enhancing their sensing performances. Besides acetone, other VOCs species have also been investigated such as ethanol, isopropanol and formaldehyde, etc. The response curves toward a series of concentrations for them are displayed in Figure 6. It can be found that the sensing response increases fast and reaches almost its equilibrium value when it is exposed to a certain concentration of all investigated VOCs in each dynamic cycle. In addition, once disengaging from the atmosphere of the detected gases, the sensing response decreases rapidly to the baseline, presenting a good reversibility. Their relationships between the relative response and concentration of the detected VOCs have been shown in Figure 7a. Evidently the cone-shaped hierarchical SnO2 nanostructures also show good sensing responses to ethanol, isopropanol and methanol besides acetone. As listed in Table 1 (Seen from supporting information), they presented the best sensing performances toward typical VOCs in contrast to previous reported researches. These results are mainly attributed to the novel cone-shaped hierarchical nanostructures. Hierarchical nanostructures are favorable for the sufficient diffuse of the detected gases among the sensing film. More importantly, the cone-shaped hierarchical structures with numerous surface defects and mismatches present a higher activity in contrast to others. Based on the relative responses toward all investigated


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VOCs with 100 ppm in Figure 7b, it can be found that weaker responses are displayed for benzene and its deviates. Clearly the cone-shaped hierarchical SnO2 nanostructures show the highest sensing performances toward acetone. This result may be ascribed that acetone molecules are more easily adsorbed and reacted on the surface of cone-shaped hierarchical structures with defects and mismatches in contrast to other investigated VOCs, leading to greatly release electrons to the conduction band of cone-shaped hierarchical nanostructured SnO2 and increase the electrical conductance of their sensing film. The gas sensors for practical applications are not only required with a good response, but also with a good stability and repeatability toward the detected gases. Figure 8 displays the relative response of cone-shaped hierarchical nanostructured SnO2 toward different concentrations of acetone at optimal working temperature of 325 °C before and after four months. Evidently it exhibits good stability, the response only declines to about 15% after four months. The real-time response curves are shown in Figure S6 (Seen from supporting information). Additionally, a good sensing repeatability is also demonstrated in Figure S7. During the sensing process of five cycles toward 50 ppm acetone, it can be observed that the same response value is reached for every time. And with the detected gases pumped out, the sensing response recovers rapidly to the baseline. This good stability and repeatability may be attributed to two aspects. One lies in the stability of the cone-shaped hierarchical SnO2 nanostructures. The reason is that the annealed temperature of 500 оC corresponding to their formation is higher than their working temperature of 325 оC as


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sensors. Accordingly, they fundamentally remain their native structure during their sensing measurements at the working temperature of 325 оC or keeping at room temperature for a long time in the dry air. The other is deviated from the recrystallization of the physically contacted hierarchical structures among three-dimensional SnO2 nanostructures after in-situ thermal treatment. It makes these three-dimensional SnO2 nanostructures closely interconnect together through numerous cone-shaped hierarchical structures with active defects and mismatches and form an electrically stable sensing film.

Conclusions Three-dimensional hierarchical SnO2 nanostructures assembled with numerous ultrathin shuttle-shaped nanosheets have been successfully synthesized through a facile hydrothermal approach. Via a controlled calcination in air, the evolution of their hierarchical nanostructures has been demonstrated from initial shuttle-shaped nanosheets to cone-shaped and rod-shaped hierarchical nanostructures. Inspired by the intrinsic

advantages

of

three-dimensional

hierarchical

nanostructures,

their

gas-sensing properties have been further investigated. Interestingly, their gas sensing performances are closely depended on hierarchical nanostructured morphologies. Among the achieved hierarchical morphologies, cone-shaped hierarchical SnO2 nanostructures obtained at the annealing temperature of 500 ºC present the highest relative response with a good stability and repeatability toward acetone, ethanol, isopropanol, methanol, etc. Further microstructured analysis indicates that their good sensing performances are mainly attributed to the formation of more active surface


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defects and mismatches during the process of thermal recrystallization. We believe that this surface-engineering strategy can be potentially extended to fabricate other three-dimensional metal oxide hierarchical nanostructures with good gas-sensing and catalytic performances.

Associated Content Supporting Information Supporting Information Available: The following files are available free of charge. Fabrication process of gas-sensing devices; SEM images and XRD patterns at different calcined temperatures; Optimization of working temperature; Real-time response curves; Relative response in comparison with previous reports; Stability of relative response; Repeatability of relative response.

Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 61474122, 61573334, 31571567 and 61106012), the National Key Scientific Program-Nanoscience and Nanotechnology (2013CB934300).


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Figure captions Figure 1. As-prepared three-dimensional SnO2 hierarchical nanostructures assembled with shuttle-shaped nanosheets: (a) and (b) SEM images of low and high magnification, respectively. The inset corresponding to individual SnO2 hierarchical nanostructure. (c) TEM image of SnO2 hierarchical nanostructures. (d) and (e) TEM images of flat and cross sectional individual nanosheet. The insets corresponding to SAED patterns. (f) EDX spectrum, and (g) XRD pattern.

Figure 2. (a) Scheme of hierarchical morphological evolutions of three-dimensional SnO2 nanostructures from as-prepared shuttle-shaped nanosheets to cone-shaped and rod-shaped hierarchical nanostructures via a thermal treatment. The morphology of individual three-dimensional SnO2 hierarchical nanostructure annealed at different temperatures in air: (b) untreated, (c) 300 оC, (d) 350 оC, (e) 400 оC, (f) 450 оC, (g) 500 оC, (h) 550 оC, and (i) 600 оC.

Figure 3. (a) Relative responses toward 100 ppm acetone for three-dimensional SnO2 hierarchical nanostructures achieved at different annealed temperatures. (b) The relationships between the relative response and concentration of acetone for three typical hierarchical morphologies of three-dimensional SnO2 nanostructures.

Figure 4. Real-time response curves of cone-shaped hierarchical SnO2 nanostructures towards acetone at the optimal working temperature of 325°C. (a) High


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concentrations in the range from 5 ppm to 200 ppm, and (b) low concentrations in the range from 50 ppb to 2 ppm, the inset corresponding to the sensing schematic model.

Figure 5. TEM images of as-prepared SnO2 with (a) shuttle-shaped hierarchical nanostructures, (b) cone-shaped hierarchical nanostructures and (c) rod-shaped hierarchical nanostructures; (d), (e) and (f) high magnified TEM images corresponding to their individual hierarchical nanostructures, the insets corresponding to their schematic morphologies; (g), (h) and (i) HRTEM images corresponding to their individual hierarchical nanostructures, the defects and mismatches are marked by the white dotted line in (h) for the cone-shaped hierarchical structures.

Figure 6. Real-time response curves of cone-shaped hierarchical SnO2 nanostructures towards different concentration of (a) ethanol, (b) isopropanol, and (c) formaldehyde at the optimal working temperature of 325 °C.

Figure 7. (a) Relationship between the relative response and concentration of the detected VOCs (acetone, ethanol, isopropanol, and formaldehyde), and (b) the relative response of cone-shaped hierarchical SnO2 nanostructures towards all investigated VOCs (100 ppm) at the optimal working temperature of 325 °C.


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Figure 8. Stability of cone-shaped hierarchical SnO2 nanostructures toward different concentrations of acetone at the optimal working temperature of 325 °C before and after four months.


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Figure 1. As-prepared three-dimensional SnO2 hierarchical nanostructures assembled with shuttle-shaped nanosheets: (a) and (b) SEM images of low and high magnification, respectively. The inset corresponding to individual SnO2 hierarchical nanostructure. (c) TEM image of SnO2 hierarchical nanostructures. (d) and (e) TEM images of flat and cross sectional individual nanosheet. The insets corresponding to SAED patterns. (f) EDX spectrum, and (g) XRD pattern.


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Figure 2. (a) Scheme of hierarchical morphological evolutions of three-dimensional SnO2 nanostructures from as-prepared shuttle-shaped nanosheets to cone-shaped and rod-shaped hierarchical nanostructures via a thermal treatment. The morphology of individual three-dimensional SnO2 hierarchical nanostructure annealed at different temperatures in air: (b) untreated, (c) 300 оC, (d) 350 оC, (e) 400 оC, (f) 450 оC, (g) 500 оC, (h) 550 оC, and (i) 600 оC.


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Figure 3. (a) Relative responses toward 100 ppm acetone for three-dimensional SnO2 hierarchical nanostructures achieved at different annealed temperatures. (b) The relationships between the relative response and concentration of acetone for three typical hierarchical morphologies of three-dimensional SnO2 nanostructures.


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Figure 4. Real-time response curves of cone-shaped hierarchical SnO2 nanostructures towards acetone at the optimal working temperature of 325°C. (a) High concentrations in the range from 5 ppm to 200 ppm, and (b) low concentrations in the range from 50 ppb to 2 ppm, the inset corresponding to the sensing schematic model.


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Figure 5. TEM images of as-prepared SnO2 with (a) shuttle-shaped hierarchical nanostructures, (b) cone-shaped hierarchical nanostructures and (c) rod-shaped hierarchical nanostructures; (d), (e) and (f) high magnified TEM images corresponding to their individual hierarchical nanostructures, the insets corresponding to their schematic morphologies; (g), (h) and (i) HRTEM images corresponding to their individual hierarchical nanostructures, the defects and mismatches are marked by the white dotted line in (h) for the cone-shaped hierarchical structures.


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Figure 6. Real-time response curves of cone-shaped hierarchical SnO2 nanostructures towards different concentration of (a) ethanol, (b) isopropanol, and (c) formaldehyde at the optimal working temperature of 325 °C.


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Figure 7. (a) Relationship between the relative response and concentration of the detected VOCs (acetone, ethanol, isopropanol, and formaldehyde), and (b) the relative response of cone-shaped hierarchical SnO2 nanostructures towards all investigated VOCs (100 ppm) at the optimal working temperature of 325 °C.


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Figure 8. Stability of cone-shaped hierarchical SnO2 nanostructures toward different concentrations of acetone at the optimal working temperature of 325 °C before and after four months.


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for TOC only


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