Controllable Synthesis of ZnO Nanoflakes with ... - ACS Publications

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Controllable Synthesis of ZnO Nanoflakes with Exposed (101̅0) for Enhanced Gas Sensing Performance Yusuf V. Kaneti, Jeffrey Yue, Xuchuan Jiang,* and Aibing Yu School of Materials Science and Engineering, The University of New South Wales, Sydney NSW 2052, Australia S Supporting Information *

ABSTRACT: This study reports a facile and efficient one-step hydrothermal method for the synthesis of zinc oxide (ZnO) nanoflakes with exposed ZnO(101̅0) surfaces. The as-prepared nanoflakes exhibit excellent sensitivity, selectivity, and stability toward volatile n-butanol gas at the optimized operating temperature of 330 °C. The gas-sensing results further indicate that the chemisorbed oxygen species on the surfaces of the ZnO nanoflakes are dominated by O2− rather than O− ions at 330 °C. The molecular dynamics (MD) method was also employed to understand the underlying fundamentals through simulating the adsorption of different gas molecules onto various ZnO crystal surfaces, such as (101̅0), (112̅0), and (0001). The simulation results confirm the enhancing effect of the exposed (101̅0) surfaces toward n-butanol gas molecules because of their lower diffusion coefficient on (101̅0) compared to those on (112̅0) and (0001) surfaces. The findings will provide new physical insights into the adsorption behaviors of volatile reducing gases on various ZnO surfaces under different temperature and humidity conditions and will be useful for the design and construction of gas-sensing materials with specifically exposed surfaces.

1. INTRODUCTION Volatile organic compounds (VOCs) such as alcohols and aromatic hydrocarbons are potentially hazardous to human health due to their capabilities to stimulate the mucous membranes and upper respiratory tracts.1 A number of VOCs such as formaldehyde (HCHO) are highly toxic even at low concentration. Therefore, it is important to develop a highly responsive and selective sensor for the detection of VOCs. Zinc oxide (ZnO) as an n-type semiconductor (3.37 eV band gap, 60 meV exciton binding energy)2 has attracted an enormous amount of interest because of its unique optical, electrical, and physicochemical properties, and been employed in numerous applications.3−7 It is well-known that the properties of nanostructures are strongly dependent upon particle size, morphology, and the exposed crystal surfaces. Many efforts have been dedicated to fabricating a variety of ZnO nanostructures with different dominant surfaces, including nanorods,8 nanowires,9 nanotubes,10 nanosheets,11 and hierarchical flowerlike nanostructures,4 by using various methods such as hydrothermal,4,8 solvothermal,12 vapor deposition,7 thermal decomposition,13 microemulsion,14 and electrospinning.15 Recently, two-dimensional (2D) ZnO nanostructures have gained significant interest due to the enhancement in photocatalytic and gas-sensing properties.5,12 For example, Zhang et al.5 synthesized hierarchically arranged porous ZnO nanosheets which display improved response to ethanol compared to ZnO nanorods and nanowires. Lu et al.12 fabricated porous hierarchical ZnO nanostructures assembled from densely built nanosheets, which showed a higher photodegradation rate for methyl orange than © XXXX American Chemical Society

commercial TiO2 P25 powders under UV irradiation. Despite some successes, limitations still exist in the fabrication of 2D ZnO nanostructures with desired crystal surfaces. Previous methods typically required multiple/complicated operation steps, high-temperature calcinations,4,16 and/or use of organic solvents and/or toxic reactants.4,12,17 Therefore, the development of a simple and efficient green method for the synthesis of ZnO nanostructures with easily scaled up production and controllable shape particularly with exposed surfaces for unique functionalities would be highly demanded. The sensing properties of ZnO-based sensors toward toxic and combustible VOCs have been examined to a good extent. For example, ZnO flowerlike nanostructures exhibited a moderate response with sensitivity (S = Ra/Rg), S = 25 toward 100 ppm of n-butanol at 320 °C, whereas ZnO nanotubes were rather insensitive to toxic formaldehyde (HCHO) with the response of S = 3 in 100 ppm HCHO at 190 °C.10,18 The reduced sensitivities of such sensing materials toward VOCs are usually attributed to the low reactivity of the exposed surface of the synthesized ZnO nanostructures or their aggregation, which limits the contact between the exposed reactive surfaces and the gas molecules.19,20 To improve the sensitivity and selectivity of the ZnO-based sensors for commercial purposes, the appropriate surface design and control are highly required. Many previous efforts mainly focus on the experimental evaluations of such materials for gas sensors and to date, Received: May 2, 2013 Revised: May 30, 2013

A

dx.doi.org/10.1021/jp404329q | J. Phys. Chem. C XXXX, XXX, XXX−XXX

The Journal of Physical Chemistry C

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overnight under vacuum at 150 °C to vaporize water molecules adsorbed on the material. 2.4. Gas Sensor Fabrication and Measurements. The as-prepared ZnO nanoflakes were first mixed and ground with the binder polyvinylidene fluoride (PVDF) in agate mortar. Then, 1-methyl-2-pyrrolidone was added to the mixture to form a white slurry, which was then coated on a ceramic tube with previously printed Au electrodes and Pt conducting wires. The ceramic tube was subsequently sintered at 450 °C for 3 h to remove the binder and to improve the stability of the sensor. The gas-sensing properties of the as-synthesized ZnO nanoflakes were measured via a computer-controlled WS-30A gassensing measurement system, the setup of which is schematically shown in Figure S1a. Prior to the measurement, a Ni−Cr resistor was inserted into the ceramic tube as a heater, allowing for the control of working temperature by adjusting the heating voltage (Vheating). A reference resistor was placed in series with the sensor to form a complete measurement circuit. The probe gas such as ethanol was injected into the testing chamber with a microsyringe. The sensitivity (S) is defined as the ratio of the resistances measured in air (Ra) and in the tested gas atmosphere (Rg): S = Ra/Rg. The output voltage was set at 3 V and the gas-sensing measurements were carried out at a relative humidity of 40−50%, with a reference resistor of 1 MΩ. A digital photograph of the as-prepared sensor is provided in Figure S1b. 2.5. Numerical Analysis. The MD simulations were performed with use of the commercial software Material Studio (Version 4.3, Accelrys Inc., 2007) with the Discover module. The canonical ensemble (NVT) with the COMPASS (Condensed-phase Optimized Molecular Potentials for Atomistic Simulation Studies) force field was used to calculate the potential energy of the system considered, in which the parameters derived from ab initio data can be applied to predict the gas-phase and condensed-phase properties of organic and inorganic materials.23,24 The properties of the ZnO surface were cleaved according to previous studies and particularly chosen for their high stability and reactivity of the material.25 Other ZnO surfaces, i.e. (112̅0) and (0001), were also used to compare the reactive sites and cleaved according to the previous density functional theory (DFT) studies.25 The computational model shown in Figure 1

there are few reports on the fundamentals correlating the exposed crystal surface(s) of ZnO nanostructures to the sensitivity/selectivity toward reducing gases (e.g., VOCs).21,22 As such, there is a lack of understanding on their atomic/ molecular interactions with ZnO crystal surfaces during the gassensing process. Herein, we report a simple and effective hydrothermal method for the fabrication of ZnO nanoflakes with specifically exposed crystalline surfaces. The composition and morphology of such nanostructures were characterized with analytical techniques, such as transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer−Emmett−Teller (BET) surface area. The sensitivity, selectivity, and stability of the as-prepared ZnO nanoflakes toward a number of VOCs especially to n-butanol were measured and evaluated. Molecular dynamics (MD) simulations were conducted to understand the underlying fundamentals and to quantify the diffusivity, adsorption, and reaction capabilities of various VOCs on the ZnO (101̅0), (1120̅ ), and (0001) surfaces. The combination of experimental and theoretical studies can provide a comprehensive understanding of the enhanced gas-sensing activity of ZnO nanoflakes with exposed (101̅0) surfaces.

2. EXPERIMENTAL SECTION 2.1. Chemicals. Zinc chloride (ZnCl2, 99%), sodium hydroxide (NaOH, 99%), cethyltetraethylammonium bromide (CTAB, 99%), formaldehyde (HCHO, 37 wt % in H2O), acetone (C3H6O, 99%), n-butanol (C4H10O, 99%), ethanol (C2H6O, 99%), and methanol (CH4O, 99%) were purchased from Sigma Aldrich and used as received without further purification. All the chemicals were of analytical grade. Ultrapure water was used throughout the experiments. 2.2. Synthesis of ZnO Nanoflakes. In a typical procedure, a mixture was first prepared by mixing a 40 mL solution of 0.15 M sodium hydroxide (NaOH) and a 2 mL solution of 0.3 M ZnCl2. Then, 2 mmol of CTAB powder was added into the mixture to form a white suspension. The suspension was subsequently transferred into a 50 mL Teflon-lined stainlesssteel autoclave and heated at 150 °C for 16 h and allowed to cool to room temperature naturally. Finally, the white precipitate was collected by centrifugation, washed with deionized water and ethanol several times, and finally dried at 60 °C for further characterizations. 2.3. Characterizations. The phase composition and purity of the synthesized ZnO nanoflakes were examined with use of a Phillips X’pert Multipurpose X-ray Diffraction System (MPD) equipped with graphite monochromatized Cu Kα radiation (λ = 1.54 Ǻ ) in the 2θ range of 20−70°. The morphological observations of the as-prepared ZnO nanoflakes were performed on a FEI Nova NanoSEM 230 field emission scanning electron microscope (SEM). TEM images were recorded with a Tecnai G2 20 transmission electron microscope (TEM) operating at an accelerating voltage of 200 kV. Highresolution transmission electron microscopy (HRTEM) images were recorded on a Phillips CM200 field emission gun transmission electron microscope with an accelerating voltage of 200 kV. The Brunauer−Emmett−Teller (BET) surface area and pore size distribution of the product were obtained from nitrogen physisorption isotherms (adsorption−desorption branches) at 77 K on a Micromeritics Tristar 3000 instrument. Prior to the BET measurement, the sample was degassed

Figure 1. Schematic illustration (side and top view) of the slab surface models of (a) ZnO(1010̅ ), (b) ZnO(1120̅ ), and (c) ZnO(0001), and (d) schematic diagram of the crystal faces in ZnO nanoflakes.

consists of a 30 × 30 Å slab and thickness of 12 Å, consisting of 10 gas molecules (e.g., methanol, ethanol), 10 water molecules, and 10 oxygen molecules placed randomly at a distance from the surface, and the simulation was run for 200 ps. The motion of the molecules became stable within 100 ps, which was used to calculate the diffusivity by measuring the slope from the plot of the mean squared displacement (MSD) B



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against time. The diffusivity, Dα, is given by the following equation: Dα =

1 d lim 6Nα t →∞ dt

Nα

∑ ⟨[ri(t ) − ri(0)]2 ⟩ i=1

where N is the number of diffusive atoms, and r is the position vector of the atom in the system. Since the MSD value can be averaged over the number of atoms, the equation simplifies to Dα = a/6. Details of the simulations can be found in our recent study.26 The data for the concentration profiles were collected from the stabilized system between 180 and 200 ps for statistical and structural analysis.

3. RESULTS AND DISCUSSION 3.1. Morphology and Composition. The phase composition of the product obtained following the completion of the hydrothermal treatment at 150 °C was characterized by using XRD, as shown in Figure 2. All of the diffraction peaks can be Figure 3. (a) Low and (b) high magnification SEM images of the asprepared ZnO nanoflakes; (c) TEM image of an individual ZnO nanoflake; and (d) the corresponding HRTEM image with labeled lattice spacing and crystal planes.

To obtain information about the specific surface area and pore size distribution of the ZnO nanoflakes, full N 2 adsorption−desorption isotherm measurements were carried out. From the representative N2 adsorption−desorption isotherm (Figure S2a) and the corresponding Barrett−Joyner−Halenda (BJH) pore distribution plot (Figure S2b), it can be observed that a molecular monolayer is formed in the low pressure region (P/P0 < 0.22), while the multilayer adsorption occurs with increasing pressure. At high relative pressures (P/P0 > 0.4), significant increase in adsorption volume is observed and desorption occurs in the reduced pressure range from 0.4 to 0.9. This suggests that the condensation of nitrogen occurs inside the pores within this narrow pressure range.12 The BET surface area of the as-synthesized ZnO nanoflakes was determined to be ∼21 m2/g. This is comparable to the surface areas of ZnO nanoplates (19 m2/g) and porous ZnO nanosheets (25 m2/g) reported previously.30,31 In terms of the reaction process, the formation of the ZnO nanoflakes originates from the initial formation of zinc hydroxide provided by the hydrolysis of Zn+ and OH− in water (eq 1). As more NaOH is added, the Zn(OH)2 precipitate dissolves to generate a homogeneous solution containing Zn(OH)42− ions, as described by eq 2. Upon hydrothermal treatment, ZnO nuclei were formed from the dehydration of Zn(OH)42− ions, according to eq 3, followed by crystal growth:

Figure 2. XRD pattern of the as-synthesized ZnO nanoflakes.

well indexed to hexagonal wurtzite ZnO (JCPDS No. 36− 1451) with lattice constants of a = b = 3.25 Å and c = 5.2 Å. No diffraction peaks from any other impurities are identified, indicating the high purity of the product. Additionally, the sharp peaks suggest that the as-prepared ZnO nanoflakes are highly crystalline under the reported conditions. The general morphology of the ZnO product was investigated by using FESEM. Panels a and b of Figure 3 show the SEM images of the synthesized ZnO nanoflakes at different magnifications. The edge lengths of the nanoflakes vary from 200 to 400 nm, with the thickness ranging from 20 to 35 nm. No other morphologies can be identified in the product. To gain further insights into the structural features and crystallography of the nanoflakes, TEM and HRTEM techniques were employed. Based on the HRTEM image shown in Figure 3d, two different lattice fringes can be observed. The spacings are calculated to be 2.6 and 2.8 Å, corresponding to the interplanar spacing of the (0001) and (101̅0) planes, respectively, of hexagonal wurtzite ZnO. In addition, the angle between these two planes is determined to be ∼90°, which is in good agreement with the angle between ZnO(0001) and ZnO(101̅0) planes.27 Moreover, these planes also correspond to the [001] and [100] vector directions, which creates the surface of the nanoflakes, and therefore the upward direction must be [010]. Since ZnO is symmetrical along the x and y lattice (i.e., [010] ≡ [100]), the exposed top surface is also the (101̅0) plane, as schematically represented in Figure 1d.28,29

Zn 2 + + 2OH− → Zn(OH)2

(1)

Zn(OH)2 + 2OH− → [Zn(OH)4 ]2 −

(2)

[Zn(OH)4 ]2 − → ZnO + 2H 2O + 2OH−

(3)

It has been shown that the shape control of ZnO nanocrystals can be achieved by manipulating the growth kinetics, and the final morphology is usually determined by the inherent crystal structure and the chemical potential in the solution.21,32 From eq 1, it is clear that the growth of ZnO C



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crystals is highly dependent on Zn2+ and OH− concentrations and/or the molar ratio of Zn2+/ OH−. As the molar ratio of Zn2+/OH− = 2, the high Zn2+ concentration promotes the fast formation of ZnO nuclei and the subsequent aggregation to form small particles, followed by their assembly into nanosheets through oriented growth, as schematically illustrated in Figure 4.32 Upon hydrothermal treatment at 150 °C, the nanosheets

Due to the relatively low NaOH concentration used during the synthesis process, no hierarchical arrangement of the nanoflakes is observed. This differs from that reported by Sinhamahapatra et al.,16 where the high concentration of the basic reactant, ammonium carbonate, led to the assembly of the porous ZnO nanoflakes into a hierarchical 3D structure. Furthermore, we have prepared the ZnO nanoflakes in a single step, unlike the two-step methods demonstrated in previous studies.16,30,34,35 Their approaches typically involve the initial formation of hydrozincite precursor, Zn 5 (CO 3 ) 2 (OH) 6, through the hydrothermal treatment of a zinc salt and a carbonate-containing reactant, followed by the subsequent calcination at a high temperature of 400 °C to transform this particular precursor to ZnO. 3.2. Gas-Sensing Performance. Two-dimensional metal oxide nanostructures have been shown to be promising materials for gas sensor applications.4,30 As such, it would be interesting to investigate the sensing performance of the assynthesized ZnO nanoflakes toward VOCs. In this study, the sensitivity of the as-prepared ZnO nanoflakes was evaluated toward gas species including n-butanol, ethanol, acetone, methanol, and formaldehyde. It is well established that the response of a semiconducting oxide gas sensor is highly affected by the operating temperature.21 Therefore, to find the optimum detection temperature, the responses of the sensor based on the ZnO nanoflakes toward 100 ppm of various gas species were tested as a function of operating temperature, as shown in Figure 5a. It can be observed from this figure that the response of the sensor toward n-butanol sharply increases with increasing temperature up to a value of 54.4 at an optimized working temperature of 330 °C. Further increase in temperature (>330 °C), however, results in a gradual reduction in the sensitivity of the sensor to n-butanol. Similar trends are also observed for other gases and will be further explained in the MD simulation

Figure 4. Schematic illustration of the formation process of the asprepared ZnO nanoflakes.

became gradually thicker, eventually formed flake-like structures. The oriented growth into nanosheets is possibly induced by the reorientation of the formed ZnO aggregates composed of numerous atoms/clusters, with the assistance of the OH− ions, in order to minimize the total energy of the reaction system. A similar phenomenon has been reported in the formation of vaterite (CaCO3) nanostructures, in which the vaterite nanocrystalline aggregates can reorient themselves into well-faceted hexagonal crystals to seek lower energy in the presence of gelatin molecules for stabilizing the vaterite polymorph and promoting oriented attachment of the vaterite nanocrystals.33

Figure 5. (a) Responses of the as-prepared ZnO nanoflakes toward 100 ppm of various VOCs as a function of operating temperatures; (b) response and recovery curves of the ZnO nanoflakes on exposure to various concentrations of n-butanol at the optimized working temperature of 330 °C; (c) comparison of the responses of the sensor to the tested VOCs at 330 °C; and (d) stability test of the as-prepared ZnO nanoflakes toward 200 ppm of n-butanol over a period of 2 months. D



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to those of ln2O3 microtubules45 and porous SnO2 nanospheres.46 Table 1 compares the sensing performance of our ZnO nanoflakes against previously reported ZnO nanostructures

section. In comparison, the responses of the sensor toward methanol and acetone reach maximum values at a higher optimum operating temperature of 360 °C, followed by a decrease in sensitivity with further rise in temperature. As shown in Figure 5a, the synthesized ZnO nanoflakes exhibit the highest sensitivity to n-butanol at all the tested temperatures. Therefore, we have selected n-butanol as the main probe gas and 330 °C as the optimal working temperature. n-Butanol is a common ingredient found in many alcoholic beverages, wines, perfumes, repellents, and cleaning products and it is often used as a solvent for paints, coatings, and natural and synthetic resins. In terms of health effects, n-butanol is readily absorbed through the skin, intestinal tract, and lungs and can act as a depressant to the central nervous system at high exposure level.36 Furthermore, the toxicity of n-butanol is identified to be approximately 6 times that of ethanol. As such, it may be of interest to develop gas sensor materials with high sensitivity and selectivity to n-butanol for potential applications in breathalyzer and in alcohol, food, or wine analysis (e.g., for discriminating the type of alcohol in red and white wines).37−39 Figure 5b shows the typical response−recovery curves of the sensor device made from the as-synthesized ZnO nanoflakes on exposure to various concentrations of n-butanol at 330 °C. It can be observed that the output voltage value increases upon injection of n-butanol and decreases upon the release of nbutanol. Accordingly, the resistance of the sensor undergoes a decrease as it is exposed to n-butanol and an increase as air is introduced back into the testing chamber, based on Ohm’s law.40 This is consistent with the sensing behavior of an n-type semiconductor sensor. Upon further inspection, it can be seen that the increase in the output voltage of the sensor largely depends on the n-butanol concentration. It is obvious that the sensor based on the as-prepared ZnO nanoflakes is able to detect a wide range of n-butanol concentrations, with probable detection limit in ppb levels as the response toward 10 ppm of n-butanol is still as high as 17, indicating its excellent sensitivity. Figure 5c presents the responses of the sensors made from the ZnO nanoflakes to a wide range of concentration of VOCs at 330 °C. It is evident that for all the tested gases, the response always increases with increasing gas concentration, eventually reaching saturation at a high gas concentration. The asprepared ZnO nanoflakes display the highest response to nbutanol with S = 87 on exposure to 500 ppm of n-butanol, whereas the lowest response is for methanol with S = 20 toward 500 ppm of methanol. Selectivity is another important factor that needs to be considered when designing gas sensors. It can be seen that the sensitivity of the ZnO nanoflakes to n-butanol is approximately 3 times higher compared to the other gases. As such, it can be said to be “selective” to n-butanol rather than the other tested gases. Furthermore, we have also evaluated the stability of sensor based on the synthesized ZnO nanoflakes toward 200 ppm of n-butanol over a period of 60 days, as shown in Figure 5d. After 30 days, the response of the sensor only slightly decreases from 64.7 to 63 and to 60.9 after 60 days, suggesting a good stability of the sensing materials originating from the as-prepared ZnO nanoflakes. Besides showing a higher sensitivity toward n-butanol, the fabricated ZnO nanoflakes also display a high sensitivity toward toxic formaldehyde (HCHO) gas with S = 17 at a concentration of 100 ppm. This particular response is higher than those reported by using ZnO nanotubes,10 porous ZnO nanosheets,41 porous In2O3 microspheres,42 SnO2 nanosheets,43 and hollow α-Fe2O3 microspheres44 and comparable

Table 1. Comparison of the Sensing Performances of Various Metal Oxide Nanostructure-Based Sensors Toward 100 ppm of n-Butanol materials porous ZnO nanoflakes porous ZnO hierarchical flower SnO2 nanospheres porous ZnO nanoflowers α-Fe2O3 hollow spindles ZnSnO3 nanocubes WO3 nanoflowers NiO hollow spheres

n-butanol concn (ppm)

operating temp (°C)

sensitivity (S = Ra/Rg)

100

330

54.4

100

220

49

this work 4

100 100

120 320

32 25

47 18

100

180

14

48

100 100 100

300 320 250

9 7 2

49 50 51

ref

toward 100 ppm of n-butanol. As shown in this table, the sensor fabricated from porous ZnO nanoflowers assembled of 2D nanosheets displays a good response of 25 toward 100 ppm of n-butanol at an optimized working temperature of 320 °C, while porous 3D ZnO flowerlike hierarchical nanostructures exhibit a response of 49 at 220 °C.4,9 In comparison, our ZnO nanoflakes display a higher response of 54.4 at 330 °C. The sensitivity of a gas sensor is usually influenced by the surface area of the sensor material and a larger surface area typically leads to higher sensitivity. In this study, the surface area of the as-prepared nanoflakes is not very large (∼20 m2/g). As such, the enhancement in the gas-sensing performance is attributed to the nonaggregation of the as-prepared nanoflakes and largely the exposed (101̅0) surface. This is very similar to that observed in a previous study by Han et al.29 where SnO2 octahedral particles with a small BET surface area of 11.0 m2/g showed five times higher sensitivity toward ethanol at 350 °C compared to SnO2 lance-shaped nanoparticles with a four times higher BET surface area of 41.5 m2/g due to the exposed {221} facets, which are more sensitive to ethanol compared to {110} facets. Recent studies have shown the benefits of exposing the reactive surfaces of metal oxide nanostructures for improving the gas-sensing performance.45,52 For example, Wang et al.45 demonstrated the synthesis of SnO2 nanoparticles enclosed by high-energy facets such as {221} or {111} facets with enhanced response to ethanol compared to rodlike SnO2 with exposed low energy {110} facets. Similarly, Han et al.52 reported that triclinic WO3 nanoparticles with exposed (010) facets displayed a higher sensitivity to 1-butylamine compared to those with exposed (100) or (001) facets. To understand the enhancing effect of the exposed ZnO(101̅0) surface on the gas-sensing properties, the diffusivity, adsorption, and reaction capabilities of various VOCs on the ZnO (101̅0), (112̅0), and (0001) surfaces were calculated by using the MD method discussed in Section 3.4. 3.3. Sensing Mechanism. One of the most commonly accepted models to explain the sensing mechanism of metal oxide-based sensor is the modulation model of depletion layer by oxygen adsorption.53−55 As shown in Figure 6a, when the E



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Figure 6. Schematic illustration of the sensing mechanism of the sensor device fabricated from the as-prepared ZnO nanoflakes in (a) air and (b) nbutanol.

ZnO nanoflake sensor is exposed to air, oxygen molecules in the air adsorb on the surface of the zinc oxide and ionize to O−, O2−, or O2− by capturing free electrons from the conduction band of ZnO. Such an event promotes the formation of depletion layers on the surface of the ZnO, which subsequently decreases the carrier concentration.56 However, once the sensor is exposed to n-butanol, the n-butanol molecule will react with the adsorbed oxygen species on the surface of ZnO, as depicted in Figure 6b. As a result, the trapped electrons are released back into the conduction band and increase the electron concentration, ultimately decreasing the resistance of the sensor. The gas adsorption on the surface of a semiconducting oxidebased gas sensor can be represented empirically by:

Sg = 1 + aCg b

Figure 7. Linear correlation between the log (Sg − 1) and the log Cg for all tested VOCs.

Table 2. Linear Equations Relating log (Sg − 1) and log Cg for All the Target Gases

(4)

target gases

where Sg is the sensitivity, Cg is the target gas concentration, and a and b are constants which depend on the sensor material and the type of gas sensor.57,58 In general, b is a charge parameter with a value of either 0.5 for O2− or 1 for O−, according to the surface interaction between chemisorbed oxygen and reducing gas to the n-type semiconducting oxide.58 Thus, if the value of b is obtained, the oxygen ion species adsorbed on the surface of the ZnO nanoflake sensor can be speculated. Equation 4 can be rewritten as: log(Sg − 1) = log a + b log Cg

methanol ethanol n-butanol acetone formaldehyde

linear relationship eq y y y y y

= = = = =

0.4149x 0.5776x 0.6493x 0.4266x 0.5813x

+ 0.86 + 0.0072 − 0.4081 + 0.1471 − 0.5397

b value (charge parameter) 0.4149 0.5776 0.6493 0.4266 0.5813

On the basis of the above discussion, the sensing mechanism of the sensor to n-butanol can be represented by the following equations:58,60

(5)

O2 (gas) → O2 (ads)

(6)

O2 (ads) + e− → O2−(ads)

(7)

O2−(ads) + e− → 2O−(ads)

(8)

O−(ads) + e− → O2 −(ads)

(9)

Air:

From eq 5, it can be seen that log (Sg − 1) has a linear relation to log Cg, with b being the slope value, which can be easily obtained from the slope of a log (Sg−1) vs log Cg plot. Figure 7 shows the logarithm of the response of the nanoflake sensor to each of the probe gases versus the logarithm of the gas concentration. It can be observed that for all the tested gases, there is a linear relationship between the logarithm of the sensitivity and the logarithm of the concentration. The equations relating the linear relations between the two logarithms for the different probe gases are summarized in Table 2. Clearly, the b (charge parameter) values for all the tested gases are relatively close to 0.5, which implies that the oxygen species on the surfaces of the ZnO nanoflakes are mainly O2− ions. This finding is in good agreement with the previous studies in which the chemisorbed oxygen species above 300 °C is determined to be O2−.58,59

n ‐Butanol: C4 H 9OH(ads) + 12O2 − → 4CO2 (gas) + 5H 2O(gas) + 24e−

(10)

As shown in Figure 6c, the response of sensor increases with an increase in the alkyl (carbon−carbon) chain length from CH3OH to C4H9OH. Such enhancement can be attributed to the higher increase in electron concentration (and therefore a higher increase in conductivity) when the adsorbed oxygen F



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species react with higher alkyl chain length alcohols such as nbutanol as opposed to shorter ones such as methanol. 3.4. MD Simulations. The exposure of metal and oxygen ions can vary among different materials, and many reports have shown that the exposure of these ions can vary greatly among the crystal facets within the nanostructures.26,61 This has tremendous implications in the choice over 1D or 2D nanostructures when used for a particular application. To understand the fundamentals of the enhanced gas-sensing properties, the adsorption behavior of the gases on different ZnO surfaces was simulated by using the MD method. Figure 8

Figure 9. Diffusivities of the tested VOC gas molecules on the various ZnO crystal surfaces at 330 °C.

can significantly enhance the adsorption and improve the sensitivity toward VOCs such as alcohols and formaldehyde gases. Moreover, n-butanol has a lower diffusivity compared to ethanol and methanol. This is because the diffusivity is related to the molecular mass, in which heavier molecules will vibrate and/or rotate less than lighter molecules. The heavier molecules, i.e., n-butanol, are less diffusive, which is also one of the reasons for its higher sensitivity in comparison to other alcohol molecules with small molecular weight. The sensitivity of the gas sensor would be expected to increase with increasing number of carbons in the alkyl chain. The mixture of various gases in an operating gas sensor can greatly influence its sensitivity to the target gas. One of the major factors is the humidity of the environment, which is the reason many of the gas sensors require a high operating temperature of 200−400 °C.63 Figure 10 shows the diffusivity of n-butanol, water, and oxygen from room temperature up to 400 °C. It can be seen that the gases undergo different adsorption behaviors on the ZnO surface, but they all follow a linear relationship. At room temperature, the diffusion coefficient is relatively similar for n-butanol and water, while oxygen molecules have a relatively higher diffusion of 3 × 10−9 m2/s. The motion of the gas indicates that n-butanol and water molecules are competitive in adsorption on the crystal surface(s). This is one of the reasons why many gas sensors would fail under a high humidity environment; the water adsorbed on the surface would prevent the target sensing gas from being adsorbed and produce a high amount of noise in the detection curve. Moreover, the strongly adsorbed water molecules also prevent the adsorption of oxygen, which inhibits the transfer of O2 into O2−. Under such ratio of gas mixtures, it is highly improbable for the above-mentioned mechanism to take place. The ratio of the mixture of the gases (n-butanol, water, and oxygen) will change as the temperature increases. At a higher temperature, the interaction energy between the water molecules and the ZnO surface can be overcome by supplying thermal energy into the system. The water molecules being lighter than oxygen and n-butanol will have sufficient kinetic energy from the higher temperature and have a higher diffusion coefficient, and hence are more likely to diffuse from the

Figure 8. Snapshots of the adsorption of n-butanol onto ZnO(1010̅ ) at times (a) 0 and (b) 200 ps.

shows a typical MD simulation model of n-butanol on the ZnO(101̅0) surface at 25 °C at its initial (0 ps) and final (200 ps) frame. By analyzing the motion and adsorption behavior of the target gas molecules over a period of time, it is possible to find the crystal plane that enhances surface reactivity in gas sensors. Since our experiments have shown that the optimum working temperature for the as-prepared ZnO nanoflakes is approximately 330 °C, the same temperature is used in the simulation to understand the behavior of the gases on various ZnO planes. Figure 9 shows a summary of the diffusivities of the gas molecules (i.e., methanol, ethanol, n-butanol, formaldehyde, and acetone) on different ZnO crystal surfaces (i.e., 101̅0, 112̅0, 0001) used in the simulation. It can be seen that all the gases have the lowest diffusivity on the ZnO(101̅0), indicating that these gases can be easily adsorbed onto this particular surface in comparison to others. The numerical data from the simulation can be correlated back to our experimental results. The synthesized ZnO nanoflakes have a dominant (101̅0) crystal surface according to HRTEM analysis, and using these nanostructures as a gas sensor material has shown that the sensitivity can be greatly improved. According to several studies on 1D ZnO nanostructures, the growth direction is on the c-axis with the ZnO(0001) as the tip surface and (101̅0) and (112̅0) as the side wall surface.62 This means the ratio of the ZnO(101̅0) in comparison to other crystal planes will be lower. However, 2D ZnO nanostructures, such as nanoplates, nanodisks, or nanoflakes, will have the (101̅0) as its dominant face,28 while the (112̅0) or (0001) will be of the edge of the particle. Therefore, ZnO nanostructures with exposed (101̅0) planes G



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From the above simulations, it can be concluded that the mixture of the gases will affect the operating temperature of a gas sensor. The amount of oxygen available will determine the amount of active sites (i.e., O2−) needed to oxidize the targeting gas, while water will inhibit the adsorption of both oxygen and the targeting gas. Therefore, the sensitivity of a gas sensor is highly determined by its environmental condition and its sensitivity can be improved by using dry air with increased oxygen content. These parameters may change depending on its application and are important to be considered in changing humidity and oxygen contents, especially in underground mining, urban cities, or indoor applications. Referring back to Figure 5a, the as-prepared ZnO nanoflake sensor displays an optimal operating temperature at 330 °C based on the diffusivity data shown in Figure 9, at which water molecules can be easily removed and oxygen can adsorb on the surface of the ZnO to produce O2−. As a result, this allows nbutanol to be detected with ease by the sensor as interference from water vapor is minimized. However, at very high temperatures (>360 °C), the sensor exhibits a lower response toward n-butanol, probably attributed to the lower likelihood of n-butanol molecules adsorbing on the ZnO(101̅0) surface at very high temperatures despite molecular activity increase, as confirmed by the MD simulations (Figure 10). Furthermore, the MD simulations also confirm that the exposed (101̅0) surface is highly responsible for the enhanced gas-sensing properties of the as-prepared ZnO nanoflakes as it exhibits the lowest diffusivity and, therefore, the highest adsorption capabilities for both n-butanol and formaldehyde. The lower diffusivities for both n-butanol and oxygen molecules on the (101̅0) surface compared to (0001) imply that they are more likely to adsorb on the ZnO(101̅0) surface. This is crucial and ultimately beneficial for enhancing the gas-sensing properties of the prepared ZnO sensor as the sensitivity of a metal oxide gas sensor is greatly dependent on the amount of chemisorbed oxygen.

Figure 10. Diffusivity of n-butanol, water, and oxygen at various temperatures on the ZnO (a) (1010̅ ), (b) (1120̅ ), and (c) (0001) surface.

surface. Under these environmental conditions, oxygen is more likely to be adsorbed to create O2− sites since water can now be removed. In comparison, the diffusion curve of water is much steeper than oxygen and n-butanol, which means higher temperatures can favor the above-mentioned reaction conditions and produce higher sensitivities. However, the diffusion coefficient will continue to increase for n-butanol and oxygen, although at a slower rate. The increase in diffusion indicates that the molecules will become less likely to be adsorbed at higher temperatures, which also explains the reason for a decreasing sensitivity at temperatures above 400 °C. Further comparison of the diffusivity of oxygen molecules ZnO crystal planes reveals that the (1010̅ ) and (1120̅ ) have similar diffusion curves for n-butanol and oxygen molecules, although water can diffuse much more easily on the (112̅0) plane. This indicates that ZnO nanostructures with (112̅0) as the dominant crystal surface may also have enhanced efficiency. However, in comparison to the (0001) surface, the diffusivity curve of the oxygen molecules is much steeper with increasing temperature. The higher temperature can remove water molecules similar to other surfaces; however, the (0001) also removes oxygen molecules at a faster rate in comparison to (101̅0) and (112̅0) planes. Therefore, the mixture of the gases may not be beneficial for the (0001) surface since the reaction will be incomplete due to the lack of O2− sites. The results also explain why ZnO nanoflakes or nanosheets with exposed (101̅0) can enhance the gas-sensing properties, while nanorods or nanowires with exposed (0001) will have a lower sensitivity.

5. CONCLUSIONS We have demonstrated a simple and effective hydrothermal approach for the synthesis of ZnO nanoflakes with exposed (101̅0) surfaces. The presented method is advantageous as it is easily scalable and allows for one-step preparation of crystalline 2D ZnO nanostructures under mild conditions (150−180 °C), without the need of high-temperature calcinations. The asprepared ZnO nanoflakes display excellent sensitivity and selectivity and good stability toward n-butanol at the optimized working temperature of 330 °C. Under similar test conditions, these ZnO nanoflakes also show excellent sensitivity toward ethanol, methanol, acetone, and formaldehyde. It is found that the enhanced gas-sensing properties of the present ZnO nanoflakes are correlated to the exposed (101̅0) surfaces and the MD simulations confirm this as the ZnO(101̅0) crystal surface exhibits lower diffusivities (i.e., higher adsorption capabilities) for all the tested gas molecules particularly for nbutanol compared to other ZnO surfaces such as ZnO(0001) and ZnO(112̅0). These findings will be useful for understanding both the adsorption behaviors of volatile reducing gases on various ZnO crystal surfaces under different temperature and humidity and the importance of designing nanostructures with specific surfaces for desired performance in gas-sensing and catalytic applications. H



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ASSOCIATED CONTENT

S Supporting Information *

Schematic diagram of the gas-sensing measurement system, digital photograph of the as-prepared ZnO gas sensor, and N2 adsorption−desorption and pore size distribution plot of the assynthesized ZnO nanoflakes. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +61-2-9385 5918. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We gratefully acknowledge the financial support of the Australian Research Council (ARC) and the access to the UNSW node of the Australian Microscopy and Microanalysis Research Facilities (AMMRF). We also thank Dr. J. Scott of Particle Catalysis Group (PARTCAT) for the assistance with the BET measurements, Mr. C. Y. Chen for the HRTEM imaging, and Mr. H. T. Fu and Mr. Z. J. Zhang for the assistance with the setup of the gas sensor measurement system.

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