Multilayered ZnO Nanosheets with 3D Porous Architectures: Synthesis

Multilayered ZnO Nanosheets with 3D Porous Architectures: Synthesis and Gas Sensing Application. Jin Li, Huiqing Fan* and Xiaohua Jia. State Key Labor...
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Multilayered ZnO Nanosheets with 3D Porous Architectures: Synthesis and Gas Sensing Application Jin Li, Huiqing Fan,* and Xiaohua Jia State Key Laboratory of Solidification Processing, School of Materials Science and Engineering, Northwestern Polytechnical UniVersity, Xi’an 710072, China ReceiVed: January 27, 2010; ReVised Manuscript ReceiVed: June 17, 2010

Multilayered ZnO nanosheets with three-dimensional (3D) porous architectures were synthesized by calcining a layered precursor of zinc hydroxide carbonate. The structural properties were investigated using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and selected-area electron diffraction techniques. It was observed that the concentration of the urea was the key parameter determining the final morphology. Room-temperature photoluminescence data showed interesting optical properties of the ZnO architectures. Gas sensing tests showed that these 3D porous ZnO architectures were highly promising for gas sensor applications, as the gas diffusion and mass transportation in sensing materials were significantly enhanced by their unique structures. Our results indicate that the 3D porous ZnO nanosheets have potential applications in fabricating optoelectrical devices and gas sensors. 1. Introduction In recent years, much attention has been paid to threedimensional (3D) and hierarchical nanostructures due to their various novel applications.1 Compared with low dimension (onedimensional and two-dimensional) structures, the 3D nanostructures can provide more opportunities for exploring novel properties and superior device performances. For example, the core/shell coaxial silicon nanowire architectures can be employed as solar cells.2 A hierarchical nanostructure based on Kevlar fibers coated with ZnO nanowires can serve as a nanogenerator.3 ZnO, as a functional n-type semiconductor, has recently attracted more and more attention due to its potential uses as room-temperature ultraviolet (UV) lasers,4 field-effect transistors,5 photodetectors,6 gas sensors,7 solar cells,8 piezoelectric nanogenerators,9 and so forth. ZnO is also a material that is biocompatible and biosafe for applications as implantable biosensors. While the synthesis of one-dimensional (1D) ZnO nanostructures has been widely explored, 3D ZnO superstructures have rarely been reported due to the difficulties in the rational control over the assembly of the primary particles into 3D superstructures.10,11 Mo et al.10 reported the self-assembly of ZnO nanorods and nanosheets into hollow microhemispheres and microspheres through the hydrothermal thermolysis of a zinc ethylenediaminederived complex precursor in the presence of a solution-soluble polymer. Bai and co-workers11 described the synthesis of clewlike ZnO superstructures in the presence of copolymer through a self-assembly method. More recently, Jing et al.12 reported the gas sensor properties of the 3D porous ZnO nanosheets mediated by microwave at 95 °C. Zhou and co-workers13-16 reported the synthesis of the 3D porous ZnO mediated by surfactant. There into, hierarchically 3D porous ZnO nanosheets were synthesized in the presence of cetyltrimethylammonium bromide (CTAB) with a reaction time of more than 8 h.16 From the viewpoint of gas sensors, porous or hollow sphere materials are promising candidates because their * Corresponding author. Phone: +86 29 88494463. Fax: +86 29 88492642. E-mail: [email protected].

special structures can usually provide a large surface-to-volume ratio that can greatly facilitate gas diffusion and mass transport in sensor materials, thus improving sensor performance.17 The conventional methods for preparing porous or hollow materials usually require the use of templates or pore-directing reagents, which may suffer from contamination due to the uncompleted removal of the additives either by chemical etching or thermal treatment.18 In general, the above-mentioned methods usually involved a special polymer as the morphology-controlling agent and/or a complicated synthesis process with a unique precursor. Furthermore, the majority of the reaction temperatures were higher than 100 °C. Therefore, simple, effective, economical, and template-free approaches by using ordinary inorganic salts are strongly desirable for the fabrication of 3D porous ZnO superstructures. Here, we described a mild, low-cost, and environmentally benign solution-based self-assembly approach combined with subsequent thermal treatment to the synthesis of 3D porous ZnO architectures. First, a layered hydroxide zinc carbonate (ZHC), Zn4(CO3)(OH)6 · H2O, was prepared. Then, the ZHC precursor conveniently converted into the corresponding ZnO nanosheets with porous structures followed by a calcination process without collapse of the morphology. The high porosity of these hierarchical ZnO nanostructures provided great potential for gas sensing applications. A comparative gas sensing study between the as-prepared porous ZnO nanostructures and ZnO nanoparticles was performed to depict the superior sensing properties of the 3D porous ZnO material. In addition, the formation mechanism of this novel 3D porous ZnO architecture was also discussed. 2. Experimental Section Synthesis. All reagents were analytically pure, bought from Shanghai Chemical Corp., and used without further purification. In a typical synthesis, 50 mL of 0.2 M zinc acetate solution was added into 50 mL of 0.4 M urea solution drop by drop. The mixture was then refluxed in a three-necked flask with a capacity of 500 mL under vigorous stirring at 90 °C for 2 h. The resulting white precipitates were collected, washed with

10.1021/jp100792c  2010 American Chemical Society Published on Web 08/13/2010

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Figure 1. XRD pattern of the 3D porous ZnO architectures.

distilled water and ethanol several times, and then dried at 60 °C for 12 h in air. Finally, a 3D porous ZnO architecture was obtained by calcining the ZHC precursor at 400 °C for 2 h in air atmosphere. Characterization. X-ray diffraction (XRD) data of the products were obtained on an X’Pert MPD Philips diffractometer with Cu KR radiation at room temperature. The general morphology and energy-dispersive X-ray (EDS) spectrum of the sample were taken on a Zeiss Supra 55 field emission scanning electron microscopy (FE-SEM) operated at 20 kV. SEM samples were prepared by drying a dispersion of powder on a piece of Al foil. Transmission electron microscopy (TEM) and selected-area electron diffraction (SAED) were performed on a Tecnai F30 G2 apparatus with an acceleration voltage of 300 kV. Thermo-gravimetric (TG) analysis was performed on a Q600-SDT with a heating rate of 5 °C min-1 under a flow of air gas. The specific surface area was measured according to

J. Phys. Chem. C, Vol. 114, No. 35, 2010 14685 the Brunauer-Emmett-Teller (BET) method with a Coulter SA 3100. The pore size distribution was determined using the Barrett-Joyner-Halenda (BJH) method applied to the adsorption branch of adsorption-desorption isotherms. The sample was degassed at 200 °C for 1 h in a vacuum prior to measurements. The ultraviolet-visible (UV-vis) spectrum of the sample was recorded using a Shimadzu UV-3150 spectrophotometer. The photoluminescence (PL) spectrum was measured at room temperature by excitation with a He-Cd continuous wave laser emitted at 325 nm (20 mW). The FT-IR spectrum was recorded on a Nicolet iS10 Fourier transform infrared spectrometer at wavenumbers of 400-4000 cm-1 using KBr pellets. Sensor Fabrication and Test. Gas sensing measurements were performed on a computer controlled WS-30A system. The structure, fabrication, and testing principle of our gas sensors based on the as-prepared porous ZnO nanosheet is similar to that for Fe2O3 nanotubes.19 For comparison, the other gas sensor using the ZnO nanoparticles with a diameter ranging from 40 to 80 nm (Figure S1 of the Supporting Information), synthesized by a simple solvethermal route, similar to our previous report,20 were also fabricated and tested. The sensitivity (response magnitude), S, was determined as the ratio, Ra/Rg, where Ra is the resistance in ambient air and Rg is the resistance in tested gas atmosphere. 3. Results and Discussion 3.1. Crystalline Structure and Morphology. The 3D porous ZnO architectures were generated by calcining the ZHC precursor at 400 °C for 2 h in air atmosphere. After calcination at 400 °C, the ZHC precursor was converted to a pure hexagonal wurtzite phase (Figure 1) according to JCPDS card no. 36-1451, with space group P63mc and lattice parameters of a ) 3.25 Å and c ) 5.21 Å. The ZnO phase was well crystallized. No other

Figure 2. (a) SEM image of the 3D porous architectures obtained from calcinations of a ZHC precursor at 400 °C in air. (b) Magnified SEM image of 3D porous ZnO nanosheets. Inset: nanoparticles constituting the ZnO nanosheets. (c) Typical TEM image of an individual ZnO porous nanosheet. (d) Magnified TEM image obtained from the dash-marked fringe of the ZnO nanosheet. Inset: corresponding SAED pattern.

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Figure 3. Typical nitrogen adsorption-desorption isotherm and BJH pore-size distribution curve (inset) of the 3D porous ZnO architectures.

diffraction peaks were detected, indicating that no impurity existed and the precursor had completely transformed into the ZnO phase. Furthermore, the grain size can be obtained using the Scherrer equation, β cos θ ) (Kλ/D), where β is the full width at half-maximum (fwhm) in radians, D is the average crystallite size, λ is the X-ray wavelength (Cu KR ) 0.154 nm), θ is the Bragg diffraction angle, and K is a correction factor which is taken as 1. The estimated average grain size was around 20 nm via the Scherrer equation. Figure 2a and b shows the typical SEM images of the ZnO nanostructures. It can be seen that the sample had a 3D morphology that was assembled by 2D nanosheets. The highmagnification SEM image shown in Figure 3b revealed the thin ZnO nanosheets with a thickness of about 20-40 nm, which consisted of irregular ZnO primary nanoparticles with a small bridge. The ZnO nanoparticles had small sizes with a diameter of about 20 nm. Unlike the results reported by Zhang et al.,17 the pore structures in present ZnO nanosheets were visible from SEM images (inset of Figure 3b). This was probably due to the larger pore of present nanosheets compared with their pore diameter of only ∼7 nm. Considering the high porosity, these

Li et al. porous ZnO nanostructures are highly favorable to be applied in photocatalysis. Further detailed structural analysis of the porous nanosheets was carried out using TEM and SAED. Figure 2c clearly displayed the porous structure of the ZnO nanosheets. Figure 2d shows the magnified TEM image obtained from the marked fringe of the ZnO nanosheets in Figure 2c. The mesopores with irregular shape and an estimated size of ∼25 nm were clearly observed in the area of the white circle. A SAED pattern taken from an individual nanosheet was shown in the inset of Figure 2d. All diffraction rings on this pattern can be attributed to hexagonal ZnO, suggesting a polycrystalline nature. To obtain further information about the pores in the nanosheet, BET N2 adsorption-desorption analysis was performed. The adsorption-desorption isotherm and the corresponding BJH pore size distribution plot (inset) of the porous sheets are shown in Figure 3. According to the IUPAC classification, the loop observed is ascribed to type H3 loops, indicating the existence of abundant mesopores (pores 2-50 nm in diameter) in the material. The size of mesopores in the architecture was not uniform, which fitted well with the TEM results. Most of the pores fall into a size range from 20 to 80 nm. The BET surface area of the material was calculated to be 23 m2 · g-1, which was a little larger than the ZnO nanoplates (15.9 m2 · g-1) reported by Jing et al.,12 while Polarz et al.21 had obtained the ordered mesoporous ZnO with a high surface area of up to 200 m2 · g-1 based on the mesoporous carbon matrix. The surface area was not greatly improved as expected in present work, which was obviously related to the fact that the ZnO nanosheet building block is a special lamellar structure, and pores embedded in the nanoscale thin layer do not have too much inner surface area. To understand the key parameters determining the morphology, the effect of synthesis recipes on the final morphology was investigated by using the FE-SEM technique. Figure 4 displays the morphologies of the synthesized ZnO samples with different molar ratios. All samples were annealed in air at 400 °C for 2 h. It indicated that the urea plays an important role in controlling the final morphology. When the urea/Zn(CH3COO)2

Figure 4. SEM images of the samples prepared with different urea contents, molar ratio urea/Zn(CH3COO)2 ) 1/1 (a), 4/1 (b), 8/1 (c), and 16/1 (d).

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Figure 5. (a) XRD pattern of the ZHC precursor. (b-d) SEM images with different magnifications of ZHC precursor.

molar ratio was 1, 3D architectures and prism-like crystals were formed. Once the urea/Zn(CH3COO)2 molar ratio was increased to 2, fewer prism-like crystals could be seen and the 3D architectures were the main product, as illustrated in Figure 2a. When the urea/Zn(CH3COO)2 molar ratio was 4, a large amount of dumbbell-like microcystals were produced. As the molar ratio of urea increased to 8, a beaded nanochain-like morphology was formed. Then, these nanochains assembled into 3D structures, as the molar ratio increased to 16. The magnified FE-SEM images revealed ZnO nanochains with a diameter of about 50 nm and a length of over 200 nm, which consisted of hexagonal ZnO nanoparticles with a small bridge. The reason that the 3D architectures can only be obtained in a narrow urea/ Zn(CH3COO)2 molar ratio was due to the fact that the urea concentration determines the precipitation speed of the Zn species. When the urea/Zn(CH3COO)2 molar ratio was 2, the precipitation speed was appropriate, that nanosheet can be obtained and then assembled into 3D architectures. When the urea/Zn(CH3COO)2 molar ratio was above 8, the precipitation speed was so high that numerous nanosheets may had formed initially, which are thermodynamically unstable and then would have been converted to the small diameter nanorods through the dissolution-reprecipitation process. 3.2. Growth Mechanisms. Figure 5a shows the XRD pattern of the ZHC precursor. According JCPDS card no. 19-1458, the crystal phase of the ZHC precursor can be indexed as a monoclinic zinc carbonate hydroxide phase [Zn4(CO3)(OH)6 · H2O], though some unknown phase exists in the precursor. The existence of the unknown phase may be attributed to the low reaction temperature. The ZHC precursor can transform into a pure Zn4(CO3)(OH)6 · H2O phase at 100-150 °C.16 Zn4(CO3)(OH)6 · H2O is a typical metal hydroxide salt (MHS), which is a kind of lamellar structure compound. Figure 5b-d reveals that the detailed morphology of the ZHC precursor is a flowerlike 3D morphology, assembled by many densely arranged nanosheets as “petals”. A close-up view of the nanosheet-built flower-like microstructures in Figure 5d reveals the nanosheets with a thickness of about 30-50 nm and a smooth surface. Moreover, from the SEM investigation, the sheet-like morphol-

ogy was also maintained after heat treatment. Thermal treatment only induced ZHC into ZnO and formed porous structures. Consequently, it is reasonable that MHS compounds can be converted to the corresponding multilayered metal oxides (LMO) without collapse of the structure. The obtained ZHC nanosheets were further characterized by TEM. Figure 6a-c shows typical TEM images of the product, confirming that the as-synthesized sample is dominated by sheetlike nanostructures. Figure 6d is a typical high-resolution TEM (HRTEM) image of a single nanosheet. The clear lattice fringes show that the nanosheets are well crystallized. The inset in Figure 6d shows a SAED pattern that was recorded from the corresponding nanosheet. It gives a pattern of diffraction rings, suggesting a polycrystalline nature. In addition, the TEM and HRTEM images indicate that the precursor nanosheets do not contain nanoholes. It is well known that the conversion from ZHC precursor to ZnO by release of H2O and CO2 with elevating temperature can be described by the following equation.

Zn4(CO3)(OH)6 · H2O f 4ZnO + 4H2O + CO2 The mass loss was further confirmed by TG analysis (Figure 7), which shows a three-step weight loss. The total weight loss was about 29.3%, which was a little larger than the theoretical value of 26.3%. It may be caused by the existence of the unknown phase. On the TG curve, the first weight loss, of 4.9% between 36 and 100 °C, corresponds to the removal of the water weakly adsorbed to the surface of the hydrozincite nanosheets. The second weight loss step, of 19.01% occurring between 100 and 225 °C, was assigned to the release of carbon dioxide and crystalline water from the thermal decomposition of the precursor. The third weight loss, of 3.3% up to 390 °C, was attributed to the complete desorption of the remaining acetate anions and water. The TG analysis indicated that ZHC precursor can evolve to ZnO absolutely at 400 °C in air. The EDS (Figure S2 of the Supporting Information) results further confirmed that the pure ZnO phase was obtained after calcining the ZHC precursor at 400 °C.

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Figure 6. (a-c) TEM and (d) HRTEM images (inset: corresponding SAED pattern) of the ZCH nanosheets.

Figure 7. TGA curve of the ZHC precursor. Figure 8. FT-IR data of (a) ZHC precursor and (b) corresponding calcined ZnO product.

FT-IR spectra can further support this evolving process. Figure 8 shows the FT-IR spectra of the ZHC precursor and 3D ZnO architectures. As for the FT-IR spectrum of the ZHC precursor, the strong and broad band appearing at 3320 cm32was due to the hydroxyl groups and water molecules, where the broadening of this band was due to hydrogen bond formation between water molecules and CO32- in the interlayer. The strong peaks at 1510, 1390, 832, and 706 cm-1 corresponded to the bending vibration of CO32-.17,22 An expected band arising from the bending mode δH2O of the water molecules was observed by an obvious shoulder at 1629 cm-1, which was more remarkable than a previous report.16 The presence of the rocking mode of the methyl (-CH3) group23 indicated that residual acetate was absorbed on the surface of ZHC, which can be detected at 1046 cm-1. In comparison, the bending vibrations of CO32- in ZnO nanosheets were greatly weakened or disappeared, indicating complete decomposition of ZHC and formation of ZnO nanosheets. Moreover, the peak at 3425 cm-1

related to hydroxyl groups and water molecules was also greatly weakened after calcination. Hence, on the basis of the TG and FT-IR analysis, it was concluded that the organic components in the ZHC precursor had been completely decomposed by the thermal treatment in air at 400 °C for 2 h. In other words, the formation of a ZnO porous structure was due to the decomposition of organic components during the annealing process. The decomposition of organic components would lead to the distortion of the crystal lattice. Subsequently, considerable tensile stress was formed and this would be released through the cracking of the crystal lattice. As a result, accompanying the continuous breaking process, the porous 3D structure of ZnO architectures was formed. Previous studies11,12,16 indicated that urea plays an important role during the formation of ZHC precursor. It was used as a dual-role agent, not only as a provider of carbonate but also as

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Figure 9. Schematic illustrating the formation mechanism of these porous architectures.

a slow-released pH adjusting agent. The reaction in the solution process can be simply formulated as follows:

CO(NH2)2 + 3H2O f 2NH3 · H2O + CO2

(1)

NH3 · H2O f NH4+ + OH-

(2)

2NH3 · H2O + CO2 f 2NH4+ + CO32- + OH-

(3)

Figure 10. Room-temperature PL spectrum of the 3D porous ZnO. The inset shows the UV-vis absorption spectrum of as-prepared ZnO.

4Zn2+ + 6OH- + CO32- + H2O f Zn4(CO3)(OH)6 · H2O (4) Initially, the aqueous solution was a neutral environment, and then, it slowly turned to weak alkaline with increasing hydroxyl, owing to hydrolysis of the urea. Zinc salt solution reacted with OH- and CO32- to form the ZHC precursor. On the basis of the above discussion, we proposed a plausible mechanism for the porous ZnO nanosheets, as schematically illustrated in Figure 9. First, the nucleation of ZHC started, accompanied with the progressive hydrolysis of urea. Then, these primary nanoparticles further aggregated into nanosheets. As the reaction proceeded, the ZHC nanosheets gradually evolved into spherical structures through an oriented attachment. As the reaction further progressed, more and more ZHC assembled and eventually formed a flower-like morphology (Figure 5b). The formation of this novel structure is due to the two different surfaces of ZHC. Hosono et al.24 had proposed that ZHC grows along the hydrophilic lateral sides, whereas the surface is hydrophobic. In this case, the ZHC nanosheets only grew into multilayered structures. Pure ZnO with the wurtzite structure was obtained by calcinations of precursor ZHC without deformation in structures. The thermal decomposition of ZHC and the release of gas in confined space during the thermal process lead to formation of the porous structure. 3.3. Optical Properties. The UV-vis absorption spectrum of the as-prepared ZnO products is shown in Figure 10. For the UV-vis absorption measurement, the as-grown ZnO products were ultrasonically dispersed in ethanol before examination, using ethanol as the reference. It exhibited a strong excitonic absorption feature at 362 nm with a calculated band gap of 3.425 eV, which showed a blue shift of about 13 nm with respect to the bulk ZnO absorption of 375 nm.25 Here, a quantum size effect was unlikely because of the dimension of the nanoparticles constituting these 3D ZnO architectures with an average diameter of about 20 nm, larger than 10 nm, the Bohr radius of ZnO. The blue shift was likely associated with the very thin bridge between the nanoparticles, some of which

Figure 11. Responses of the 3D porous ZnO architectures and the ZnO nanoparticles to various gases (the concentration of all gases was 100 ppm).

had a diameter of less than 10 nm. A similar result had been reported by Bai.11 As shown in Figure 10, the room-temperature PL spectrum of the 3D porous ZnO architectures only exhibited an intense ultraviolet emission (UV) centered at about 389.5 nm due to near band-edge emission, whereas the defect-related emission (green or yellow emission) is not observed. The accurate peak energy of UV emission was extracted from Gaussian fitting. In addition, the strong UV emission exhibited by these novel porous ZnO nanostructures indicated that the material can be potentially used as a high-performance ultraviolet emitter.26 3.4. Gas Sensing Properties. Because surface defects in nanostructures can dramatically change the optical, electrical, and physical properties,27,28 it was expected that such a unique structure of ZnO might bring about more efficient gas sensing compared to analogous bulk materials and conventionally fabricated ZnO nanoparticles. Two gas sensors were fabricated from the as-prepared porous ZnO nanosheets and ZnO nanoparticles for comparison. Figure 11 shows the sensitivity of these sensors to the examined gases, such as acetone, ammonia, ethanol, 90# gasoline, methanol, and toluene. All of the gases were tested at an operating temperature of 400 °C with a concentration of 100 ppm. As expected, the sensor based on porous nanosheets exhibited enhanced responses for each gas compared with that based on ZnO nanoparticles. These results strongly prove that the as-prepared 3D porous ZnO architectures are promising candidates for gas sensing applications. In

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Figure 12. (a) Typical response curve and variations of the sensitivity of 3D porous ZnO sensors exposed to acetone at concentrations ranging from 5 to 500 ppm and measured at 400 °C. (b) Dilogarithm fit curve of the sensitivity of the sensors to the concentration of acetone. Inset: sensitivities of the gas sensor versus various acetone concentrations.

Figure 13. Schematic diagram of the proposed reaction mechanism of a 3D porous ZnO-based sensor to acetone: (a) in air; (b) in acetone.

addition, the sensor based on 3D porous architectures showed high response detection to acetone. Figure 12a shows the response as a function of acetone concentration for the porous ZnO nanosheets operated at 400 °C. It was obvious that the sensor had a wide detection range for acetone from 5 to 500 ppm. The response for different ethanol concentrations was also tested. When exposed to 5 ppm acetone, the sensitivity was as high as 8.76. With increasing concentration of acetone, the sensitivities greatly increase (inset of Figure 12b). The sensitivity of the semiconductor oxide gas sensor can be empirically represented as S ) 1 + Ag(Pg)β, where Pg is the target gas partial pressure, which is directly proportional to the gas concentration, Ag is a prefactor, and β is the exponent on Pg.29-31 Generally, the exponent β has an ideal value of either 0.5 or 1, which is derived from the surface interaction between chemisorbed oxygen and reducing gas to the n-type semiconductor. Figure 12b displays a chart of the logarithm of the response of the sensor versus the logarithm of acetone concentration (C). The linear fitting was quite good, and the correlation coefficient R of the sensor fit curve is 0.9991. The result shows the sensor match with dilogarithm amplifying circuits for practical application in the detection range 5-500 ppm acetone vapor. The value of β was about 0.424, determined by the fit shown as the solid line in Figure 12b. The deviation from the ideal value of 0.5 was probably due to the agglomeration of nanostructures or less sensitive areas existing in the sample.29,31 Response and recovery times are also important parameters in a gas sensor, which were defined here as the time to reach 90% of the final equilibrium value. The sensor immediately responded when 100 ppm acetone was introduced. The response and recovery times of the sensor were 5 and 28 s, respectively. The other concentrations also showed the same behavior. For

100 ppm ethanol, the response and recovery times were 6 and 23 s, respectively. The response for ethanol was much quicker than the sensor reported by Jing et al.,12 and the recovery time was comparable. In addition, the sensor also exhibited satisfactory sensing properties at low temperature (280 °C). For 100 ppm ethanol (Figure S3 of the Supporting Information), the sensitivity was 8.79, which was about 3-fold higher than the sensor reported previously.17 For ZnO-based sensors, the change of resistance is mainly caused by the adsorption and desorption of gas molecules on the surface of the sensing structure. The mechanism of sensing of 3D porous ZnO sensors can be explained by the modulation model of the depletion layer,32 as shown in Figure 13.20 The potential barriers of the contact between the nanosheets reduce the carrier mobility. When the sensor is exposed to air, oxygen species can adsorb on the surface of ZnO nanosheets and form O2-, O2-, and O- ions by capturing electrons from the conduction band. These lead to the formation of a thick spacecharge layer which increases the potential barrier, and thus results in a higher resistance. When the sensor is exposed to reductive gas, for instance, acetone or ethanol, the gas will react with adsorbed oxygen species on the ZnO surface to form CO2 and H2O, and release the trapped electrons back to the conduction band. This leads to an increasing carrier concentration of the sample and decreasing resistances of sensors. It should be noted that the chemisorbed oxygen species depend strongly on temperature. Since the sensor was operated at 400 °C, the O- species were more important than other oxygen adsorbates.33,34 On the basis of the discussion, this mechanism can be explained as follows:

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O2(gas) f O2(ads) O2(ads) + e- f O2-(ads) O2-(ads) + e- f 2O-(ads)

Supporting Information Available: Figures showing XRD and SEM of the ZnO nanoparticles (Figure S1), an EDS curve of the ZHC precursor after calnicaion at 400 °C (Figure S2), and enlarged response and recovery processes when exposed to 100 ppm ethanol at 280 °C (Figure S3). This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes

CH3COCH3(gas) f CH3COCH3(ads) CH3COCH3(ads) + 8O-(ads) f 3CO2(gas) + 3H2O(gas) + 8eThe enhancement in gas sensing property on porous ZnO architectures can be explained by the following reasons. For the sensor based on ZnO nanoparticles, the surface-to-volume ratio was relatively low as a result of larger grain sizes (∼50 nm versus ∼20 nm). Furthermore, only a thin layer of the film close to the surface can be activated during gas detection due to the dense structure of a compact film. In comparison, there exists a network of interconnected pores in sensor films based on 3D porous ZnO, where these 3D porous architectures provided a large surface-to-volume ration; additionally, these 3D architectures were randomly oriented to generate a more highly porous structure. This network of pores enables both the analyte and the background gas to access all of the surfaces of particles contained in the sensing unit. 4. Conclusions In summary, a template-free solution-based method combined with a subsequent annealing process was demonstrated for the synthesis of 3D porous ZnO architectures, which were composed of interconnected ZnO nanosheets with high porosity. Comparative gas sensing tests between gas sensors based on 3D porous ZnO architectures and ZnO nanoparticles clearly showed that the former exhibits more excellent sensing performances, implying a good potential of the porous ZnO nanostructures for sensor applications. The enhanced sensing performances were attributed to the high porosity and 3D morphology, which can significantly facilitate gas diffusion and mass transportation in sensing materials. The as-synthesized 3D porous ZnO architectures were also expected to be useful for other applications such as photoluminescence and photocatalysts. Moreover, this work further hints that this facile and economical approach can be extended to synthesize other porous metal oxide materials with a unique morphology or shape. Acknowledgment. This work has been supported by the National Nature Science Foundation (50672075), the 111 Program (B08040) of MOE, the Xi’an Science and Technology Foundation (XA-AM-200905 and XA-AM-200906), the Fundamental Research Foundation (NPU-FFR-200703) of NPU, and the SKLSP Research Fund (40-QZ-2009) of China.

(1) Hu, J. S.; Zhong, L. S.; Song, W. G.; Wan, L. J. AdV. Mater. 2008, 20, 2977. (2) Lauhon, L. J.; Gudiksen, M. S.; Wang, D.; Lieber, C. M. Nature 2002, 420, 57. (3) Qin, Y.; Wang, X. D.; Wang, Z. L. Nature 2008, 451, 809. (4) Huang, M. H.; Mao, S.; Feick, H.; Yan, H. Q.; Wu, Y. Y.; Kind, H.; Weber, E.; Russo, R.; Yang, P. D. Science 2001, 292, 1897. (5) Goldberger, J.; Sirbuly, D. J.; Law, M.; Yang, P. D. J. Phys. Chem. B 2005, 109, 9. (6) Kind, H.; Yan, H.; Messer, B.; Law, M.; Yang, P. D. AdV. Mater. 2002, 14, 158. (7) Dai, Z. R.; Pan, Z. W.; Wang, Z. L. AdV. Funct. Mater. 2003, 13, 9. (8) Law, M.; Greene, L. E.; Johnson, J. C.; Saykally, R.; Yang, P. D. Nat. Mater. 2005, 4, 455. (9) Wang, Z. L.; Song, J. H. Science 2006, 14, 242. (10) Mo, M.; Yu, J. C.; Zhang, L.; Li, S. A. AdV. Mater. 2005, 17, 756. (11) Bai, P.; Wu, P.; Yan, Z.; Zhou, J.; Zhao, X. S. J. Phys. Chem. C 2007, 111, 9729. (12) Jing, Z.; Zhan, J. AdV. Mater. 2008, 20, 1. (13) Zhou, X.; Hu, Z.; Chen, Y.; Shang, H. Appl. Surf. Sci. 2008, 255, 3371. (14) Zhou, X.; Guo, X.; Ding, W.; Chen, Y. Mater. Res. Bull. 2008, 43, 2790. (15) Li, B.; Cui, Y.; Liu, L.; Chen, J.; Zhu, Q.; Zhou, X. Chin. J. Inorg. Chem. 2009, 25, 2077. (16) Zhou, X.; Hu, Z.; Fan, Y.; Chen, S.; Ding, W.; Xu, N. J. Phys. Chem. C 2008, 112, 11722. (17) Zhang, J.; Wang, S.; Xu, M.; Wang, Y.; Zhu, B.; Zhang, S.; Huang, W.; Wu, S. Cryst. Growth Des. 2009, 9, 3532. (18) Lou, X.; Archer, L. A.; Yang, Z. AdV. Mater. 2008, 20, 3987. (19) Gurlo, A.; Riedel, R. Angew. Chem., Int. Ed. 2007, 46, 3826. (20) Li, J.; Fan, H. Q.; Jia, X. H.; Yang, W. W.; Fang, P. Y. Appl. Phys. A 2010, 98, 537. (21) Polarz, S.; Orlov, A. V.; Schuth, F.; Lu, A. H. Chem.sEur. J. 2007, 13, 592. (22) Liu, Z.; Ma, R.; Osada, M.; Iyi, N.; Ebina, Y.; Takada, K.; Sasaki, T. J. Am. Chem. Soc. 2006, 128, 4872. (23) Song, R. Q.; Xu, A. W.; Deng, B.; Li, Q.; Chen, G. AdV. Funct. Mater. 2007, 17, 296. (24) Hosono, E.; Fujihara, S.; Honma, I.; Zhou, H. S. AdV. Mater. 2005, 17, 2091. (25) Srikant, V.; Clarke, D. R. J. Appl. Phys. 1998, 83, 5447. (26) Djurisˇic´, A. B.; Leung, Y. H. Small 2006, 2, 944. (27) Zeng, X. Y.; Yuan, J. L.; Wang, Z. Y.; Zhang, L. D. AdV. Mater. 2007, 19, 4510. (28) Halperin, W. P. ReV. Mod. Phys. 1986, 58, 533. (29) Scott, R. W. J.; Yang, S. M.; Chabanis, G.; Coombs, N.; Willams, D. E.; Ozin, G. A. AdV. Mater. 2001, 13, 1468. (30) Kim, I.; Rothschild, A.; Hyodo, T.; Tuller, H. L. Nano Lett. 2006, 6, 193. (31) Wang, J. X.; Sun, X. W.; Yang, Y.; Huang, H.; Lee, Y. C.; Tan, O. K.; Vayssieres, L. Nanotechnology 2006, 17, 4995. (32) Gergintschew, Z.; Fo¨rster, H.; Kositza, J.; Schipanski, D. Sens. Actuators, B 1995, 26, 170. (33) Zhang, Y.; Xu, J. Q.; Xiang, Q.; Li, H.; Pan, Q. Y.; Xu, P. C. J. Phys. Chem. C 2009, 113, 3430. (34) Belmonte, J. C.; Manzano, J.; Arbiol, J.; Cirera, A.; Puigcorbe´, J.; Vila`, A.; Sabate´, N.; Gra`cia, I.; Cane´, C.; Morante, J. R. Sens. Actuators, B 2006, 114, 881.

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