Acetone sensing of ZnO nanosheets synthesized using room-temperature precipitation

Accepted Manuscript Title: Acetone sensing of ZnO nanosheets synthesized using room-temperature precipitation Authors: Si-Meng Li, Le-Xi Zhang, Meng-Ya Zhu, Guo-Jin Ji, Li-Xin Zhao, Jing Yin, Li-Jian Bie PII: DOI: Reference:

S0925-4005(17)30607-X http://dx.doi.org/doi:10.1016/j.snb.2017.04.007 SNB 22093

To appear in:

Sensors and Actuators B

Received date: Revised date: Accepted date:

13-8-2016 19-3-2017 3-4-2017

Please cite this article as: Si-Meng Li, Le-Xi Zhang, Meng-Ya Zhu, Guo-Jin Ji, Li-Xin Zhao, Jing Yin, Li-Jian Bie, Acetone sensing of ZnO nanosheets synthesized using room-temperature precipitation, Sensors and Actuators B: Chemicalhttp://dx.doi.org/10.1016/j.snb.2017.04.007 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Acetone sensing of ZnO nanosheets synthesized using room-temperature precipitation

Si-Meng Li a, Le-Xi Zhang a, b*, Meng-Ya Zhu a, Guo-Jin Ji a, Li-Xin Zhao c, Jing Yin c, Li-Jian Bie a, b*

a

School of Materials Science and Engineering, Tianjin University of Technology,

Tianjin 300384, China b

Tianjin Key Lab for Photoelectric Materials and Devices, Tianjin University of

Technology, Tianjin 300384, China c

School of Environmental Science and Safety Engineering, Tianjin University of

Technology, Tianjin 300384, China

* Corresponding authors: Le-Xi Zhang, E–mail: [email protected] (L-X Zhang) Li-Jian Bie, E–mail: [email protected] (L-J Bie)

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Graphic abstract

Highlights: 1. Direct synthesis of ZnO nanosheets using facile precipitation at room temperature. 2. The nanosheets based sensor exhibits high response, fast response-recovery and good selectivity to acetone vapor. 3. The correlation between surface defect contents and sensor response was established: the more defects, the higher response.

Abstract Zinc oxide (ZnO) nanosheets were directly synthesized using a facile precipitation method at room temperature without any template, surfactant or organic solvent. X-ray diffraction (XRD) confirms that the ZnO nanosheets belong to hexagonal wurtzite structure. Scanning electron microscope (SEM) and transmission electron microscope (TEM) reveals the morphology and structure of the ZnO nanosheets, showing the predominantly exposed non-polar {100} planes and an average thickness of about 20 nm. In order to regulate and control the intrinsic surface defect 2

contents, improving the thermal stability, the samples were calcined at different temperatures (200°C, 400°C and 600°C respectively), showing that the sheet-like structures can be maintained below 400°C. Photoluminescence (PL) analysis shows that abundant intrinsic surface defects exist on the ZnO crystal surfaces. Gas sensors based on ZnO nanosheets calcinated at 200°C exhibits high response, fast response-recovery and good selectivity to 5-1000 ppm acetone vapor at 300°C. The response value to acetone vapor is correlated with the surface defect contents, namely, the more defects, the higher sensor response. Thus, it is considered that the improved acetone sensing property, especially enhanced response value, is mainly originated from the increased intrinsic defect content on the surface of ZnO nanosheets. Developed precipitation method is facile for synthesis of ZnO nanosheets, which demonstrate an effective strategy for surface defect engineering to improve the metal oxide semiconductor gas sensing performance. Keywords: Precipitation, ZnO, Nanosheet, Acetone, Gas sensor, Surface defect

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1. Introduction Metal oxide semiconductors have been widely used as gas sensing materials due to their low cost, high response value, fast response, and good selectivity. ZnO, as one of the earliest discovered important gas sensing materials, has revealed extensive application prospect in detection of flammable and poisonous gases [1]. Decreasing grain size not only ensures the contact with more gas molecules, but also provides more surface active sites, therefore nanomaterials, including one-dimensional (1D) nanowires [2], nanorods [3, 4], and nanobelts [5], two-dimensional (2D) nanosheets [6], and three-dimensional (3D) hierarchical structures [7-9], have been adopted to improve the gas sensing response. ZnO nanosheets showed superior properties in many areas, such as solar cell, catalysis and sensor devices [10-12] because of their high degree of crystallinity, large surface area to volume ratio, and an increased proportion of exposed active planes [6, 13-15], all of which can enhance the gas sensing properties. However, special equipment [16, 17], organic solvents [7], surfactants [18] or high temperature [19] are needed in most of the ZnO nanosheets synthesis to date, it is necessary to develop a facile, low cost, mass production and template-free method to synthesize ZnO nanosheets for practical applications. Strategies for improving ZnO gas sensing performance were also reported via doping noble metals [15], rare earth elements [20] and metal oxides [19]. Furthermore, it is another strategy to increase the ZnO response by regulating and controlling intrinsic surface defects. Previous reports based on ZnO nanorods showed that when the donor defect content is high, the sensor response is high [21-23]. Actually, these 4

reports are rarely focused on pertinently controlling the defect content and studying the relation between the defect and the response values. Nevertheless, Sudip K. et al. referred that the response of ZnO nanorods can be improved significantly owing to the increase of the concentration of oxygen vacancies and other defects [24]. Zhao et al. mentioned that Li doped ZnO nanoparticles show higher response, which can be attributed to the effect of oxygen deficiency [25]. However, the similar report on 2D ZnO architectures is rather limited. Recently, Barnett et al reported the defects control by annealing ZnO nanosheets in vacuum in the processing stage [26], but no evident connection between defects and gas sensing properties was concluded. It is important to develop a simple and effective method to control the defect content of 2D ZnO nanostructures, and to understand their surface defect dependent performance, for example gas sensing. In this paper, a facile precipitation method for synthesis of ZnO nanosheets at room temperature is reported without the need of any template, surfactant or organic solvent. The obtained nanosheets were characterized in terms of structure, morphology, exposed planes, surface defects, specific surface area and chemisorbed oxygen species. The gas sensor fabricated from these ZnO nanosheets show excellent acetone vapor sensing property with high response value, fast response-recovery and good selectivity. Notably, the sensor response is correlated with the defect contents excluding the influence of exposed planes and specific surface area. Reasons for the enhanced acetone vapor response are also discussed, in particular from the perspective of intrinsic surface defects. 5

2. Experimental details 2.1 Synthesis of ZnO nanosheets All chemical reagents were of analytical grade and used without further purification. In a typical experimental process, ZnO nanosheets were synthesized as follows: 3.3 g zinc acetate (Zn(CH3COOH)2·2H2O) was dissolved in 75 ml distilled water, stirring for 5 min until the solution became clear, then 100 mL newly prepared sodium hydroxide (NaOH) solution (0.8 mol/l) was dropped into the zinc acetate solution. The resulted milky solution was stirred for another 30 min, aged for 1 h. The precipitates were collected by vacuum filtration, washed alternatively using distilled water and ethanol for 3 times, dried at 60°C, and finally white ZnO powders was obtained. In order to improve the crystallinity, thermal stability and regulate the intrinsic defects, the as-prepared ZnO were calcined at 200°C, 400°C and 600°C for 30 min, which are designated as ZnO-200, ZnO-400 and ZnO-600 respectively.

2.2 Characterization The crystal structure of the as-prepared samples were characterized by XRD on a Rigaku D/max-2500 X-ray diffractometer with monochromatized Cu Kα1 radiation (λ = 1.5418 Å) operated at 40 kV and 150 mA. SEM images of the samples were observed using a JEOL JSM-6700F field-emission SEM with an accelerating voltage of 10 kV. TEM images, high resolution transmission electron microscope (HRTEM) images and selected area electron diffraction (SAED) patterns were obtained on a JEOL JSM-2010 microscope with an accelerating voltage of 200 kV. The TEM 6

sample was prepared by dispersing ZnO in ethanol after ultrasonication for 10 min and dropped onto a carbon coated copper grid. PL emission spectra were recorded on a Hitachi F-4500 spectrophotometer by a 325 nm excitation from a 150 W Xenon lamp as the excitation source at room temperature. The specific surface areas were calculated based on the Brunauer-Emmett-Teller (BET) method using N2 adsorption-desorption at 77 K after treating the samples at 120°C and 10−4 Pa for 3 h using a Tristar II -3020 apparatus. The X-ray photoelectron spectroscopy (XPS) was performed by a Thermal Scientific ESCALAB 250 Xi XPS spectrometer, using a monochromated aluminum (Kα radiation: h = 1486.6 eV) anode operated at 15 kV and 12.8 mA with a resolution of 0.1 eV (beam spot size: 500 m2). In the XPS measurements, the as-prepared ZnO powder was ground and mounted on the sample holder with double-sided adhesive tape, then the spectra were taken under ultrahigh vacuum conditions (working pressure in the analysis chamber was maintained below 10−6 Pa) at room temperature. To eliminate the effect of surface contamination, the binding energy scale was calibrated by a XPS peak of C1s with a value of 284.6 eV.

2.3 Gas sensor fabrication and measurement Appropriate amount of ZnO sample was mixed with drops of deionized water to form pastes, which were then coated on an alumina ceramic tube, dried at 100°C for 2 h. The alumina ceramic tube with a length of 4 mm and a radial thickness of 0.4 mm was positioned with one Au electrode and two Pt wires on each side. A small Ni-Cr alloy coil was put inside the tube as a heater to tune the working temperature of the 7

gas sensor, as shown in Fig. 1(a). Four Pt wires and the heating coil were connected to the base of a sensor test unit to measure the gas sensing properties, as shown in Fig. 1(b). The sensors were heated at 120°C for 1 h and aged at 200°C for 48 h to improve the stability before the gas sensing measurement. The acetone sensing tests were conducted on a stationary NS-4000 Smart Sensor Analyzer (Beijing Zhongke Micro-Nano Networking Technology Co. Ltd., China). And this static gas system connected with a computer which was used to measure the resistances of the sensors. The relative humidity was about 40%. During test operation, 99.5% acetone liquid was injected onto a flat heater inside the closed chamber of 30 L in which sensors were installed and then immediately evaporated into gas to fill the whole chamber mixing with air. And the calculation method of acetone vapor concentration is defined by Eq. (1), where v, V, c, M, TR, d, p and TB denote the injected liquid volume (ml), chamber volume (ml), vapor concentration (ppm), molecular weight (g/mol), room temperature (°C), density (g/cm3), purity of liquid (%) and temperature of the chamber (°C), respectively. v = V*c*M*(273+TR)*10-9/[22.4*d*p*(273+TB)]

(1)

The sensor response (Sr) for reducing gases is defined as Eq. (2), where Ra and Rg are the resistances of the gas sensor in air and in the test gases, respectively. Sr = Ra/Rg

(2)

The response time, τres, is defined as the time taken by the resistor ranging from Ra to [Ra - 90% (Ra - Rg)] when the sensor is exposed to the target gas. And the recovery time, τrec, is defined as the time taken by the resistor changing from Rg to [Rg + 90% 8

(Ra - Rg)] when the sensor is retrieved from the target gas.

3. Results and discussion 3.1 Structure and morphology The XRD of the ZnO samples including ZnO, ZnO-200, ZnO-400 and ZnO-600 were shown in Fig. 2(a). All of the diffractions can be indexed to hexagonal wurtzite ZnO (JCPDS card No.75-0576) with lattice constants a = b = 3.243 Å and c = 5.195 Å. No impurity can be observed before or after the calcination. The diffraction intensities of the calcined samples become stronger than that of the directly obtained ZnO sample, and the full width at half maximum (FWHM) get narrower simultaneously. Moreover, in the temperature range from 200°C to 600°C, the higher the calcination temperature, the stronger the peak intensity, and the narrower the FWHM, manifesting that better ZnO crystallinity can be achieved by increasing calcination temperature, whereas their crystal size becomes larger gradually due to fusion and growth between adjacent crystalline grains. Beyond that, the position of the diffractions of the samples after calcination are shifted to a lower angle, as shown in Fig. 2(b), demonstrating increased crystal lattice constants and interplanar spacing (d) because of heat-treatment induced stress relaxation, as shown in Table 1. The grain size (D) was calculated using the Scherrer equation [27], D = 0.89λ/(βcosθ), where λ is the X-ray wave length (CuKα1, 1.5418 Å), β is the FWHM of the peak and θ is the corresponding Bragg diffraction angle. As listed in Table 1, based on the calculation from the three strong lines corresponding to (100), (002) and (101) planes, the 9

crystalline grain size gets larger with the increase of calcination temperatures, such as the (100) plane (20.7 nm < 22.0 nm < 22.3 nm < 32.3 nm) and the (002) plane (31.5 nm < 36.4 nm < 37.5 nm < 38.1 nm). The grain sizes calculated from (100) and (101) planes are almost the same for each of the sample, but they are smaller than that calculated from the (002) plane, implying that all the ZnO samples grow preferentially along the [001] direction (c-axis of hexagonal wurtzite ZnO). And with the increase of temperature, the lattice parameters of ZnO, ZnO-200 and ZnO-400 increased (a = b: 3.245 Å < 3.251 Å < 3.261 Å; c: 5.198 Å < 5.204 Å < 5.219 Å), indicating that the unit cell is larger than before, showing that higher temperature resulted in larger grains. However, the unit cell parameters of ZnO-600 did not exhibit the same trend as it lost sheet-like morphology. Fig. 3 is the SEM images of samples. As can be seen from Fig. 3(a), the as-synthesized ZnO are well dispersed sheet-like nanostructures, showing scattered and irregularly shape with rough edge as well as surface. The nanosheets are 0.4-0.8 m in length and about 20 nm in thickness, which are in good agreement with the XRD results in Fig. 2 and Table 1. That is to say, ZnO nanosheets are directly synthesized via a really facile precipitation method at room temperature, which is low cost, mass production and environment-friendly without using any template, surfactant, organic solvent or special equipment. Fig. 3(b-d) show the SEM images of the samples after calcination at 200°C, 400°C and 600°C for 30 min, respectively. It is found that as the temperature increases, the surface and edge of ZnO nanosheets get smooth, but the thickness and overall shape don’t change apparently below 400°C. 10

Compared with Fig. 3(a), the ZnO nanosheets in Fig. 3(b) and Fig. 3(c) show a tendency to reunite and stack together so as to reduce surface energy. Unfortunately, the sheet morphology is almost completely destroyed and aggregated particles emerge as can be seen in Fig. 3(d), indicating that the ZnO nanosheets can’t endure a calcination temperature as high as 600°C. Detailed structure of ZnO nanosheets (e. g. ZnO-200) was characterized using TEM and SAED, as shown in Fig. 4. The panoramic TEM image in Fig. 4(a) confirms the sheet-like morphology of the ZnO sample, showing that the sheets are thin and uniform in thickness. Shallow pits distributed on the ZnO-200 nanosheets surface can be recognized from Fig. 4(b), which may increase the specific surface area and facilitate gas absorption. The HRTEM image of a single nanosheet in Fig. 4(c) displays clear lattice fringes, confirming the good crystallinity which is consistent with the XRD results in Fig. 2. The spacing between the adjacent lattice fringes is about 0.256 nm, corresponding to the interplanar distance of the (002) crystal planes of the wurtzite ZnO [28]. These results also confirm that the samples grow preferentially along the [001] crystallographic direction, indicting the exposed {100} planes of the nanosheets [29, 30]. For the typical wurtzite ZnO crystal, the (001) and {101} planes are polar surfaces with high surface energy [31, 32], while the {100} planes are electrically neutral and thus nonpolar ones with relatively low surface energy. According to the Bravais Rule [33], the overwhelming majority of exposed surfaces of ZnO nanosheets are sandwiched by {100} planes via the room temperature precipitation. The SAED patterns of ZnO-200 nanosheets in Fig. 4(d) 11

shows a single crystal structure of hexagonal wurtzite ZnO in this region, which can be indexed as the [001] direction, consistent with the results of XRD and HRTEM. The specific surface area and porous feature of the ZnO nanosheets were investigated using N2 adsorption–desorption measurement. The calculated pore size distribution for the adsorption branch of the N2 isotherm using the BJH (Barrett-Joyner-Halenda) method indicates that there is no distribution of mesopores in the as-prepared ZnO samples, which is consistent with the result of TEM in Fig. 4. The specific surface areas calculated using the BET method are 23.88 m2/g, 21.22 m2/g and 8.42 m2/g for ZnO-200, ZnO-400 and ZnO-600, respectively. The formula for the adsorption of multi-molecules on the basis of the classical statistical theory was proposed by Brunauer, Emmett and Teller, known as BET equation, which is now considered as the standard for measuring the specific surface area of solids. The BET surface specific area is defined by Eq. (3), where Vm, A and σm denote the monomolecular layer saturated adsorption capacity (mol/g), Avogadro constant (6.02*1023/mol) and adsorbate molecular cross-sectional area (N2: 16.2*10-20 m2). The specific surface area refers to the total area of the unit mass material, which is an important parameter to evaluate the property of catalyst, adsorbent and other porous substances. Large specific surface area is usually favorable for gas adsorption, suggesting that ZnO-200 may have better response than ZnO-400 and ZnO-600. SBET = Vm*A*σm

3.2 Optical characterization 12

(3)

Except for surface area, it has been proved that the gas sensing performance of metal oxide semiconductor is strongly affected by surface defects, including both species and contents [13, 34, 35]. In order to characterize intrinsic defects, the PL of ZnO nanosheets was measured using 325 nm excitation at room temperature (Fig. 5). Shapes of the three spectra are similar, implying the same kind intrinsic defect species with different contents. Weak ultraviolet (UV) emission (< 400 nm) and strong visible emission (400–800 nm) were observed in the emission spectra. The UV emission is attributed to the recombination of free excitons between the valence band (VB) and conduction band (CB), while the visible emission is usually caused by impurity and intrinsic defects (obviously the latter ones in this work). The strong visible emission suggests abundant structure defects on the surface of ZnO nanosheets [36]. As can be seen, the intensity of ZnO-200 in visible region is higher than ZnO-400 and ZnO-600, normalized corresponding integrated peak area decreases in the order of ZnO-200 (100%) > ZnO-400 (72.65%) > ZnO-600 (57.59%). Combined the PL result and BET analysis, it is estimated that ZnO-200 may have the highest response value among the three samples. ZnO nanosheets synthesized at room temperature possess rich surface intrinsic defects, so it is reasonable that the calcination in air can reduce and eliminate some defects [21], e.g. VO˙˙ (oxygen vacancy: the origin of n-type semiconducting behavior for ZnO), see Eq. (4) as follows, resulting in crystal quality improvement confirmed by the XRD results in Fig 2. Therefore, the intrinsic surface defects can be well adjusted by controlling the calcination temperatures in order to enhance the sensor response further. 13

VO˙˙ +1/2 O2 + 2 e- + ZnZn → ZnO

(4)

Generally speaking, gas sensing behavior depends on the redox reaction between the chemical adsorbed oxygen species and target gases on the metal oxide semiconductor surface. Previous reports indicate that the surface defects can improve the gas response values greatly, including both impurity [37, 38] and intrinsic defects, because more oxygen molecules could be adsorbed [39] and then ionized [21] onto the semiconductor surface. XPS analysis was carried out to examine the composition and surface structure of the ZnO nanosheets as shown in Fig. 6(a). The similar shape of the survey scan XPS spectra reveals that the three samples are only composed of Zn, O and C, no other elements can be found. The C peak is mainly originated from hydrocarbon contaminant; this phenomenon often exists in XPS spectra of ZnO crystals [40]. Fig. 6 (b) to (d) exhibited the narrow scan XPS spectra of O1s, showing an asymmetric curvilinear shape, which can be deconvoluted into three Gaussian sub-peaks according to their own positions [13, 22]. The lower binding energy peak at ~ 530.00 eV corresponds to the lattice oxygen (OL), which can be assigned to O2- ions in ZnO lattice. The peak located at ~531.00 eV namely defective oxygen (OV) belongs to the oxygen defects caused in the condition of the oxygen deficiency [41, 42]. The peak at ~532.00 eV represents the hydroxy species (OH) or chemisorbed and dissociated oxygen species (OC) on the surface of ZnO [42-44]. Actually, the more content of OC, the more oxidant in the redox reaction, hence more reducing gas molecules could be adsorbed and oxidized, resulting in the higher sensor response values. As can be seen from insets of Fig. 6 (b) to (d), the OC content of ZnO-200 14

(27.11%) is higher than that of ZnO-400 (22.38%) and ZnO-600 (21.50%), which means that the ZnO-200 gas sensor should display the highest response value in the three samples. That is to say, the existence of surface defects makes ZnO adsorb and ionize more oxygen, leading to significant enhancement of the sensor response.

3.3 Gas sensing properties As one of the typical volatile organic compounds (VOCs), acetone vapor is commonly used as industrial solvent and raw material for production of methyl methacrylate and bisphenol A. However, acetone is a colorless, volatile, flammable liquid at room temperature, acetone vapor may damage human health and lead to explosion even at low concentration in air [45], possessing a pungent, irritating odor and wide range of flammable limits in air (standard condition for temperature and pressure): 2.6–12.8% (V/V). Therefore, developing an effective and convenient device for low concentration acetone vapor detection becomes important to guarantee the safety in laboratory, industries and residential buildings [14, 46]. Acetone gas sensor based on Ni doped SnO2 [47] and Cu doped WO3 [48] have been reported, sensing materials were synthesized using electrospinning method, and working temperature to acetone is about 300°C. It should be pointed out that relative high humidity will reduce the response values due to the competitive adsorption of target gas and water vapor [49-51]. If the gas sensing test is conducted in higher humidity air, the response value may be lower than the present results, but the structure of ZnO nanosheet (including intrinsic surface 15

defects) does not change. In this work, gas sensors were fabricated using the 2D ZnO nanosheets composed samples. Fig. 7 shows the sensor response to 200 ppm acetone vapor at different temperature, and the ZnO-200 sample shows the highest response. Clearly, with the increase of the operating temperature, the response value increases accordingly and reaches the maximum at 300°C and then decreases rapidly with further increment in temperature, which is due to the competing desorption of the chemisorbed oxygen [52]. Therefore, 300°C is chosen as the optimum operating temperature (OOT) for the ZnO gas sensors, which is far lower than the autoignition temperature of acetone vapor (465°C). As enough energy is needed to overcome the activation barrier, the amount of chemical adsorption gas increases along with the increase of operating temperature, meanwhile the gas response values increase [53]. When the amount of adsorbed gases reaches maximum at OOT, the gas sensing response value gets maximum as well [54]. The maximum response value to 200 ppm acetone vapor is as high as 106.1 for ZnO-200, which is higher than reports based on 2D ZnO hierarchical structures [8, 14, 45, 55]. Fig. 8 shows the gas sensing performance of the response vs. concentration. The response values increase rapidly with the increase of acetone vapor concentration in the range from 5 ppm to 1000 ppm, indicating that the sensors do not saturate less than 1000 ppm. The ZnO-200 sensor displays much higher response values to different acetone vapor concentration than that of ZnO-400 and ZnO-600, which agree well with the results of PL spectra and BET analysis. Additionally, the detection 16

limit (Sr ≥ 3) of ZnO-200 (0.81 ppm) is lower than that of ZnO-400 (1.12 ppm) and ZnO-600 (4.56 ppm), as shown in Fig. S1 of Supplemental file. Fig. 9(a) reveals the dynamic response of the ZnO samples with different acetone vapor concentration at 300°C. Obviously, the ZnO-200 nanosheet sensor presents the best response and recovery property to acetone vapor. And Fig. 10 displayed the zoom out region of pulses for 5 ppm and 10 ppm. It is worth to note that the response to 5 ppm acetone vapor achieves 6.7, showing practical application potential for low concentration acetone vapor detection. The response and recovery time of the ZnO-200 sensor toward 5-1000 ppm acetone vapor are calculated as shown in Fig. 9(b). Evidently, the overall trend is that with the increase of acetone vapor concentration, both response time and recovery time are gradually decreased. Especially in the range of acetone vapor concentration higher than 10 ppm, shorter response and recovery time less than 60 s are needed, which can well satisfy the requirement of commercial metal oxide semiconductor gas sensors. It is reported that the dominated oxygen species is O2− above 300°C on ZnO surface, so abundant O2− species adsorbed on the surface of ZnO-200. But O2− is very unstable and more active than the other ones (O2, O2− and O−), which will promote the adsorption and reaction of acetone vapor, while simultaneously accelerating desorption of reaction products. Obviously, as the acetone vapor concentration increases, the number of acetone vapor molecules in a specific volume will increase, the sensor will respond quickly, so does the recovery time. Repeatability test result of ZnO-200 toward 200 ppm acetone vapor at 300°C is 17

given in Fig. 11, the sensor response almost remains upon four successive sensing tests cycles to 200 ppm acetone vapor, showing good repeatability. The sensor response of ZnO-200 to different gases at 300°C is shown in Fig. 12. The response to acetone vapor is the highest compared with gases such as formaldehyde, ethanol, benzene, toluene, xylene and methylamine (MA), indicating good selectivity to acetone vapor. In principle, the sensor response is related to the adsorption and reaction of the detected gases on the surface of materials, and the adsorption of the detected gases depends greatly on their intrinsic property, such as polarity, molecular weight, gas molecule structures and the corresponding bond energy [22, 56]. As we all know, gas sensing mechanism of ZnO-based sensors belongs to surface-controlled type, the resistance change is caused by the redox reaction between the oxygen species and target gas molecules on ZnO surface. In this work, the selectivity means the ZnO nanosheet sensor presents higher response value to acetone vapor than other gases. The good selectivity might be contributed to the large dipole moment [57] of acetone vapor, as the dipole moment of acetone vapor is 2.88 D (Debye: the unit of dipole moment), larger than other gases, such as formaldehyde (2.33 D), ethanol (1.69 D), benzene (0 D), toluene (0.38 D), xylene (< 0.62 D) and methylamine (1.31 D) [58]. As a consequence, the interaction between the {100} facet of ZnO nanosheets and acetone vapor molecules is considerably stronger than other gases, benefiting the good selectivity to acetone vapor detection. As a comparison, acetone sensing properties of metal oxide semiconductor nanostructures synthesized with different methods were summarized in Table 2. 18

Room-temperature precipitation adopted in this paper is a typical aqueous solution approach, having the advantage of facile synthesis at low temperature with mass production and environmental friendly process, compared with other methods operated with higher temperature [6, 19, 46], expensive noble metal [59], necessary organic solvents, special equipment [55] or multi-step procedures [19]. As to acetone sensing properties, the OOT of as-synthesized ZnO-200 is lower than that of most reports in Table 2 [6, 45, 46]; this is beneficial for energy consumption reduction used as the gas sensor. Low OOT could also avoid the growth of crystallite, which will prolong the sensor lifetime, favorable for practical gas sensor application. Additionally, the as-prepared ZnO-200 gas sensor exhibits much higher response to acetone vapor than pure ZnO nanosheets [60], 3D hollow-Si nano- and microstructures [61], nanosheet-assembled 3D structures [6] and even CuO doped ZnO [19], comparable to Pd-ZnO nanosheets [46], but lower than Au modified 3D In2O3 inverse opals [62]. Moreover, the high response, fast response–recovery characteristic and good selectivity make ZnO-200 nanosheets a good candidate for fabricating acetone vapor sensors. The BET, PL and XPS results after measurement were considered also. The specific surface area of ZnO-200, ZnO-400 and ZnO-600 are 15.25, 10.73 and 5.31 m2/g, respectively. And the decreased PL intensity is presented as Fig. 13. XPS of O1s is shown in the insets of Fig. 14, in which the OC content of ZnO-200 (10.58%) is still higher than that of ZnO-400 (10.37%) and ZnO-600 (9.61%). Although response degradation may exist in the heat treatment and gas sensing test, resulted in the 19

decreased defects amount, hence decrease the OC content, the ZnO-200 is still the best one among these samples. The long-term stability of the gas sensor of ZnO-200 was exhibited in Fig. 15. It is obvious that the change of the response is not great toward 200 ppm acetone vapor at 300°C in 40 days, except for a little deterioration (~5.71%) after the first 72 h, showing that the ZnO-200 nanosheet sensor has good stability. All of these results indicate that ZnO-200 can be used as an excellent candidate for acetone vapor detection.

3.4 Gas sensing mechanism As a typical n-type semiconductor, the gas sensing mechanism of ZnO nanosheets is schematic illustrated in Fig. 16(a). When ZnO nanosheets are exposed in the air, oxygen molecules will be adsorbed on the surface, capturing free electrons from conduction band to form negative oxygen species, such as O2-, O- and O2-, resulting in an electron depletion layer (LD) and higher resistance, as illustrated on top of Fig. 16(a). As reductive gases such as acetone vapor get to the sensor, it will react with the oxygen species on the ZnO surface, the trapped electrons can be released to the conduction band, leading to a resistance decrease as shown on bottom of Fig. 16(a). Compared with other reports listed in Table 2, it can be concluded that the enhanced response to acetone vapor is mainly attributed to large specific surface area, small thickness and abundant intrinsic defects. First of all, due to the large specific surface area, ZnO nanosheets could adsorb 20

more molecules for redox reaction of oxygen and acetone vapor [63]. Thus, more electrons are captured or released, inducing sensor response improvement. Furthermore, the higher specific surface area provides more active sites for sensing reactions [64]. The ZnO-200 sample has the larger specific surface area, hence the higher response value [65]. Secondly, the grain size also plays an important role in the gas sensing response enhancement, based on the grain-control model [66]. The characteristic thickness of ZnO nanosheets is about 20 nm confirmed by SEM and TEM, which is comparable to their corresponding 2LD (approximately 15 nm at 325°C for ZnO [67]). This means that the nanosheet is nearly completely depleted, which is almost at the optimum thickness [64]. Last but not least, the high acetone vapor response may be attributed to the surface defects. Based on the definition of sensor response, since more oxygen species are absorbed on metal oxide surface induced by abundant intrinsic defects in this work (established by PL and XPS analysis), more free electrons can be captured from ZnO conduction band, leading to a larger LD and thus Ra [68], as presented on top of Fig. 16(b). It also means that more acetone vapor molecules can be oxidized and more electrons are released to the conduction band, leading to a smaller LD and then Rg, exhibiting an enhancement of sensor response at last, as illustrated on bottom of Fig. 16(b). Previous results revealed the fact that high content of surface defects leads to increased sensor response, however the other influencing factors, such as morphology, grain size, specific surface area, exposed planes and even different doping ions [38], 21

have not been excluded simultaneously. In this work, the calcined ZnO products provide ideal samples for comparing the effect of intrinsic surface defects on their sensor response, especially for ZnO-200 and ZnO-400 with practically the same morphology, grain size, characteristic thickness and exposed planes. Nevertheless, the effect of the specific surface area should be ruled out at first, and the normalized response is exhibited in Fig. 17(a). Normalized response is defined as the ratio of response value to the specific surface area of the material (Sr/SBET). It is gratifying that the high and low order of normalized response in the test concentration range (5-1000 ppm) is the same as that presented in Fig. 8, that is, the gas response of ZnO-200 is still the highest one, followed by ZnO-400 and ZnO-600. This result suggests that the intrinsic surface defects surely play a key role in the response enhancement in this work. As is known to all, gas sensing properties, particularly response value, are closely related to the chemisorbed oxygen species [30], which react as the oxidant in the surface redox reaction. If there is a larger number of adsorbed oxygen, the gas response will be enhanced significantly. As shown in Fig. 17(b), the normalized defect content (from PL spectra in Fig. 5), the oxygen species content (from XPS results in Fig. 6) and the normalized response (take 200 ppm as an example) are all decreased with the increasing of calcination temperatures. Since ZnO nanosheets synthesized at room temperature possess rich surface intrinsic defects, which is the origin of n-type semiconducting behavior for ZnO, it is reasonable that the heat treatment in air can reduce and eliminate some of the defects, see Eq. (4), resulting in improvement of crystal quality just as shown in Fig 2. Therefore, it is 22

reasonable to observe the decreased surface defect content, then diminished chemisorbed oxygen species, and reduced sensor response at last. In future work, to adjust the intrinsic surface defects by controlling the calcination temperature or using reduction atmosphere might be a possible way to enhance the gas sensing response [21, 69, 70]. As the characterization was performed before deposition of ZnO nanosheets on ceramic tube, the BET, PL and XPS results after deposition were given in Fig. S2-S3 of Supplemental files, where similar trend can be observed.

4. Conclusions In summary, ZnO nanosheets were directly synthesized by a facile, low cost and template-free precipitation method at room temperature. The calcined nanosheets were characterized in terms of structure, morphology, specific surface area, surface defects and chemisorbed oxygen species, respectively. ZnO-200 exhibits the best gas sensing properties (high response value and good selectivity) to acetone vapor at the optimum working temperature of 300°C. Even as low as 5 ppm acetone vapor can be responded well (Sr = 6.7), implying potential application at lower working temperature toward low concentration acetone vapor. Furthermore, the correlation was established between the surface defect content and the corresponding sensor response, bridging by chemisorbed oxygen species on ZnO surface, while excluding the effect of specific surface area. From the Oc content of ZnO-200 (27.11%) > ZnO-400 (22.38%) > ZnO-600 (21.50%), it can be concluded that the more defects, the better response values. In conclusion, the facile precipitation method can be used 23

for synthesis of other 2D metal oxide semiconductor nanostructures. Introducing more surface defects has been proved as a promising way to enhance response values of metal oxide semiconductor nanostructures in both the synthesis and post heat treatment process.

Acknowledgements This work was financially supported by the National Natural Science Foundation of China (NSFC Grant No. 21271139 and No. 21401139) and Tianjin Natural Science Council (Grant No. 15JCQNJC02900).

24

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34

Biographies

Si-Meng Li is currently a candidate for her Master’s degree in materials science and engineering at Tianjin University of Technology. Her research is focused on synthesis and gas sensing properties of metal oxide semiconductor nanostructures. Le-Xi Zhang received his Ph.D. degree in materialogy in 2012 from Institute of Coal Chemistry, Chinese Academy of Sciences (ICC, CAS). His current research is focused on synthesis of semiconductor nanostructures and their gas sensing applications. Meng-Ya Zhu is currently a candidate for her Ph.D. degree in materials science and engineering at Tianjin University of Technology. Her research is focused on synthesis and structure of organic-inorganic layered perovskite compounds. Guo-Jin Ji is currently a candidate for his Master’s degree in materials science and engineering at Tianjin University of Technology. His research is focused on synthesis and structure of layered perovskite materials. Li-Xin Zhao received his Ph.D. degree in 2011 from Institute of Process Engineering, Chinese Academy of Sciences (IPE, CAS). His research interests are preparation and application of water treatment materials. Jing Yin graduated from Liaocheng University and received her B.Sc. degree in 1989. Her research interests are in the growth of functional crystal materials and the preparation of nano-materials. Li-Jian Bie obtained his Master’s degree in inorganic chemistry from University of Science and Technology of China in 1991, and Ph.D. degree in inorganic chemistry 35

from Peking University in 2002. He is now a professor in Tianjin University of Technology, leading a group in research for the synthesis and property of nanomaterials and perovskite-related materials, including their application in sensors.

36

Figure Captions Fig. 1. (a) Scheme of the gas sensor structure. (b) The measuring electric circuit. The inset illustrates a photograph of a sensor. Fig. 2. XRD patterns of the as-prepared ZnO sample and the ZnO nanosheets calcinated at 200°C, 400°C and 600°C in the 2range of (a) 20°-80° and (b) 30°-40°. Fig. 3. Representative SEM images of (a) the as-prepared ZnO and ZnO nanosheets calcinated at (b) 200°C, (c) 400°C and (d) 600°C, respectively. Fig. 4. (a and b) Panoramic TEM images, (c) HRTEM image and (d) corresponding SEAD pattern of the ZnO nanosheets calcinated at 200°C. Fig. 5. Room temperature photoluminescence spectra of the ZnO nanosheets calcinated at 200°C, 400 °C and 600°C, respectively. Fig. 6. (a) Survey scan XPS spectrum of the ZnO nanosheets calcinated at 200°C, 400°C and 600°C, respectively. (b), (c) and (d) are the corresponding narrow scan XPS spectra of O1s. Inset: binding energy positions and percentages of three peaks (OL, OV and OC) separated from O1s. Fig. 7. Gas sensing response of the gas sensors based on ZnO nanosheets calcinated at 200°C, 400°C and 600°C to 200 ppm acetone vapor at different operating temperatures. Fig. 8. The response curves of the gas sensors based on ZnO nanosheets calcinated at 200°C, 400°C and 600°C to acetone vapor in the range of 5-1000 ppm at 300°C. Fig. 9. (a) Dynamic response of the gas sensors based on ZnO nanosheets calcinated at 200°C, 400°C and 600°C to 5-1000 ppm acetone vapor at 300°C. (b) Response and 37

recovery times of the ZnO nanosheets calcinated at 200°C to acetone vapor in the range of 5-1000 ppm at 300°C. (c) The response and recovery times of ZnO nanosheets calcinated at 200°C toward 200 ppm acetone vapor at 300°C. Fig. 10. Focus of 5 to 10 ppm in the dynamic response with acetone vapor concentration of 5 - 1000 ppm at 300°C. Fig. 11. The repeatability of the ZnO nanosheets calcinated at 200°C to 200 ppm acetone vapor at 300ºC. Fig. 12. Gas sensing selectivity of the ZnO nanosheets calcinated at 200°C to 200 ppm different gas at 300°C. Fig. 13. Room temperature PL spectra of the ZnO nanosheets calcinated at 200°C, 400°C and 600°C after measurement. Fig. 14. (a) Survey scan XPS spectrum of the ZnO nanosheets calcinated at 200°C, 400°C and 600°C after measurement. (b), (c) and (d) are the corresponding narrow scan XPS spectra of O1s. Inset: binding energy positions and percentages of three peaks (OL, OV and OC) separated from O1s. Fig. 15. Long-term stability of the ZnO nanosheets calcinated at 200°C to 200 ppm acetone vapor at 300ºC. Fig. 16. Schematic illustration of the contact potential barrier under the electron transfer between two neighboring ZnO nanosheets viewed from the side (a) with less and (b) more defects. Fig. 17. (a) Normalized response of the ZnO nanosheets calcinated at 200°C, 400°C and 600°C to 5-1000 ppm acetone vapor at 300°C. (b) The normalized defect content, 38

the oxygen species content and the normalized response to 200 ppm acetone vapor at 300°C. Table Captions Table 1. Crystal parameters of the ZnO samples. Table 2. Synthesis conditions of various metal oxide semiconductor nanostructures and their acetone sensing properties.

39

Fig. 1.

42

Fig. 2.

43

Fig. 3.

44

Fig. 4.

45

Fig. 5.

46

Fig. 6.

47

Fig. 7.

48

Fig. 8.

49

Fig. 9.

50

Fig. 10.

51

Fig. 11.

52

Fig. 12.

53

Fig. 13.

54

Fig. 14.

55

Fig. 15.

56

Fig. 16.

57

Fig. 17.

58

Table 1. Crystal parameter of the ZnO samples. D (nm)

Lattice parameter

Sample (100)

(002)

(101)

a = b (Å)

c (Å)

ZnO

20.7

31.5

21.3

3.245

5.198

ZnO-200

22.0

36.4

21.7

3.251

5.204

ZnO-400

22.3

37.5

23.1

3.261

5.219

ZnO-600

32.3

38.1

32.7

3.256

5.213

40

Table 2. Synthesis conditions of various metal oxide semiconductor nanostructures and their acetone sensing properties. Synthesis condition

OOT

Material Method

T (°C)

ZnO nanosheets (this work)

Direct precipitation method/Calcination

Flower-like ZnO microspheres [45] ZnO nanosheets [57] Flowerlike ZnO [52] ZnO multi-layer architectures [1]

Hydrothermal method and decomposition Hydrothermal method Oil bath

3D porous ZnO [6] Porous flower-like CuO/ZnO [19] Single crystalline ZnO nanosheets [46] Single crystalline Pd-ZnO nanosheets [46] Ni-doped SnO2 hollow nanofibers [47] Cu-doped WO3 hollow fibers [48] 3D hollow-Si nano- and microstructures [58] Au modified 3D In2O3 inverse opals [59]

Hydrothermal method Aqueous solution method with calcination Chemical solution method with calcination

ppm

Sr 10.7 36.4 67.1

(°C)

RT/200

300

10 50 100

120/300

350

50

7

120 50

220 320

100 100

24.9 14

180

150

10

4.8

RT/300

320

100

31.6

95/450

220

100

20

420

100

40

340

100

75

Solvothermal method with annealing

140/400

Electrospinning

50/600

340

100

64.9

Electrospinning

80/500

300

20

6.43

200/RT

200

100

26

120/600

340

5

42.4

Sacrificial template approach Sacrificial template method

41