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Vol. 9. Issue 1.
Pages 1129-1136 (January - February 2020)
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Vol. 9. Issue 1.
Pages 1129-1136 (January - February 2020)
Short Communication
DOI: 10.1016/j.jmrt.2019.12.094
Open Access
Improved sub-ppm acetone sensing properties of SnO2 nanowire-based sensor by attachment of Co3O4 nanoparticles
Hongseok Kima, Zhicheng Caib, Sung-Pil Changa, Sunghoon Parkb,c,
Corresponding author

Corresponding author.
a Department of Electronic Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, South Korea
b Department of Software Convergence, Sejong University, 209 Neungdong-ro, Gangjin-gu, Seoul 05006, South Korea
c Department of Intelligent and Mechatronics Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, South Korea
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Tables (1)
Table 1. Acetone sensing responses of various SnO2 nanostructure-based sensors.
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Co3O4 nanoparticle-attached SnO2 nanowires are synthesized to fabricate highly sensitive acetone gas sensor by vapor-liquid-solid (VLS), sol-gel, and thermal annealing processes. To analyze enhanced acetone gas sensing responses, Co3O4 nanoparticles are attached SnO2 nanowires, and several samples are synthesized followed by the cycles of Co3O4 nanoparticle attachment process. The sensing response of Co3O4 nanoparticle-attached SnO2 nanowires, which are one time performed Co3O4 nanoparticle attachment process, is improved by 7 times compared with as-synthesized SnO2 nanowires when exposed to 50 ppm acetone gas. In particular, when exposed to 0.5 ppm acetone gas, as-synthesized SnO2 nanowires present an extremely low response — close to negligible. However, when Co3O4 nanoparticles are attached, the response is improved drastically. Furthermore, the sensing selectivity toward acetone gas is improved compared with its counterpart. This improved sensing property is derived from the increasing variation in the surface depletion area located in the p-n heterojunction.

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Acetone is among the major volatile organic compounds (VOCs). It is applied to lots of purpose in the fields of industrials such as a solvent to dilute and dissolve chemical matters [1]. Meanwhile, despite of its necessaries, it has some side effects. It has volatile and flammable properties in low temperature and causes various diseases [2]. However, without this chemical, lots of chemical industries cannot be continued. Furthermore, diabetes has been diagnosed through the detection of acetone gas in exhaled human breath. The breath of diabetes patients contains over 1.8 ppm acetone gas. Therefore, diabetes can be diagnosed easily and expeditiously using acetone sensors [3]. In these reasons, devices to use acetone safely have to be prepared. Many accidents such as explosion and disease originated by acetone are caused by acetone fume and gas, and lots of problems caused by acetone can be prevented to control concentration of acetone gas. Therefore, highly sensitive acetone gas sensors have to be developed to use acetone safely [4–6].

Metal oxide semiconductors (MOS) nanostructures are applied to gas sensors owing to its unique properties. Lots of gases including VOCs can be recognized using this material-based sensor [7–9]. Among these MOS nanomaterials, SnO2 nanowires are well-known gas-sensitive materials [10]. Since nanowire structure can maximize its properties owing to the large surface area and high aspect ratio [11–13], highly sensitive gas sensor can be fabricated using nanowire structured SnO2. Table 1 presents acetone sensing properties of SnO2 based gas sensors. Many acetone sensors using SnO2 nanostructures are fabricated followed by these researches. However, despite of these benefits, its poor sensing selectivity is a major issue to overcome. Because of its low selectivity for various kinds of gases, this gas cannot specify the specific gas in many gases [23,24]. Many techniques are introduced to improve its selectivity. The response and selectivity of SnO2 nanomaterial-based acetone gas sensor can be improved to attach noble metal or MOS nanoparticles [25], to synthesize core/shell structure [26], and to modify microstructures [27]. Among these methods, selectivity and sensitivity of MOS nanomaterial gas sensors can be enhanced to attach heterostructured MOS nanoparticles [28]. Since SnO2 nanowire-based gas sensor presents poor selectivity although it presents sensitive response, additional processing has to be performed. And Co3O4 nanoparticles, which present good selectivity to acetone gas, are attached to surface of SnO2 nanowire surface to improve its response and selectivity. With the interactions of SnO2 nanowire back bone and attached Co3O4 nanoparticles, variation of depletion layers can be changed more drastically, and acetone sensing properties are improved significantly [29,30]. In this research, methods of synthesis of Co3O4 nanoparticle-attached SnO2 nanowires are introduced, and its acetone sensing properties are analyzed. Furthermore, the sensing mechanisms of this nanostructure-based sensors are also discussed.

Table 1.

Acetone sensing responses of various SnO2 nanostructure-based sensors.

Structures  Operating temperature(oC)  Acetone concentration (ppm)  Response (Ra/RgRef. 
Hierarchical SnO2 hollow microspheres  200  50  16  [14] 
Rh doped electrospun SnO2 nanofibers  200  50  59  [15] 
Eu-doped SnO2 electrospun nanofibers  280  100  36  [16] 
Co catalyzed SnO2 nanospheres  220  100  37  [17] 
Ag-decorated SnO2 hollow nanofibers  160  50  45  [18] 
Hierarchical SnO2 hollow nanosheets  300  100  40  [19] 
La-doped SnO2 layered nanoarrays  290  50  23  [20] 
Ce-doped SnO2 nanoparticles  270  50  50  [21] 
Pr6O11-functionalized SnO2 flower-like architectures  200  100  27  [22] 
Co3O4 nanoparticle-attached SnO2 nanowires  300  50  70  This work 
2Experimental2.1Synthesis of Co3O4 nanoparticle-attached SnO2 nanowires

Co3O4 nanoparticle-attached SnO2 nanowires were synthesized using the following two steps: First, SnO2 nanowires were synthesized on the interdigital electrode (IDE) patterned chip by the vapor-liquid-solid (VLS) method. 1 g Sn powder was placed in an alumina crucible, and the IDE chip was placed in front of the Sn powder. This crucible was loaded in the center of the horizontal tube furnace and sealed tightly. The vacuum generated in the chamber was 1 mTorr, and the chamber was heated to 900 °C. When the temperature reached 900 °C, it was maintained for 10 min with 100 sccm of 1-% O2 mixed N2 gas. Subsequently, the chamber was cooled without any gas supply.

Second, Co3O4 nanoparticles were attached through a sol-gel and annealing process. For this, 50 ml of 20 mM cobalt (II) acetate solution was mixed with 0.1 g of NaOH and stirred using a magnetic stirred for 30 min. This solution was centrifuged at 3000 rpm for 2 min. The solution without the gel was removed, and an equal amount of ethanol was refilled. This new solution was mixed using magnetic stirrer for 1 h. The SnO2 nanowire-deposited IDE chip was immersed into the solution and taken out after 10 min and dried using N2 gun. This process is repeated from 1 time to four times. The sample fabricated with as-synthesized SnO2 nanowires (Sample A) and the samples fabricated with Co3O4 nanoparticle-attached SnO2 nanowires followed by repeated cycles (Sample B, Sample C, and Sample D) are prepared to measure acetone sensing properties. This chip was annealed at 500 °C without any vacuum and gas supply for 1 h.


Synthesized nanowires in this research were analyzed their morphologies and microstructures using several instruments. The morphologies of the samples were observed by scanning electron microscopy (SEM, Seron Technology, AIS2500C), and the crystal structure was analyzed by X-ray diffraction (XRD, Philips X’pert MRD pro). The morphology and nanostructure of a single nanowire were analyzed by transmission electron microscopy (TEM, Jeol-2100F).

2.3Gas sensing measurements

The fabricated sensing samples were connected to a sourcemeter unit (Keysight B2901A) and installed in the chamber to measure its sensing properties. The target and purging gas were injected for 200 and 300 s, respectively, with a rate of 500 sccm. The operating temperature was varied from 100 °C to 400 °C with the intervals of 25 °C to determine the optimum sensing condition. To analyze the response, 0.5, 1, 2, 5, 10, and 50 ppm acetone gas were supplied to the sensors. The response of the samples was defined as Ra/Rg for the target gas, where Ra and Rg are the electrical resistances of the sensors exposed to air and the target gas, respectively. The response and recovery times are measured and calculated as the time required for the resistance to reach 90% of the equilibrium value after target and purging gas injection, respectively.

3Results and discussion3.1Characterization of Co3O4 nanoparticle-attached SnO2 nanowires

Fig. 1(a) and its inset present SEM image of the Co3O4 nanoparticle-attached SnO2 nanowires (Sample B) and as-synthesized SnO2 nanowires (Sample A), respectively. From these images, the diameters of a SnO2 nanowire and Co3O4 nanoparticles are approximately 100 nm and 5 nm, respectively. Inset image of Fig. 1 (a) presents as-synthesized SnO2 nanowires. Followed by this image, SnO2 nanowires have flat and smooth surface unlike to its counterpart. However, diameter and morphology of these nanowires in inset image present almost similar with nanowires in Fig. 1 (a). Fig. 1(b) presents XRD patterns of Samples A (black line) and B (red line). The peaks indicate that the synthesized nanostructures are tetragonal-structured SnO2 (JCPDS No. 88-0287) and can be founded in both patterns. In the pattern for Sample B, an additional (311) peak is observed, indicating face-centered cubic-structured structured Co3O4 (JCPDS No. 78-1970). Fig. 1(c) and (d) present low-magnification and high-resolution TEM images of Sample B. The low-magnification image of a single Co3O4 nanoparticle-attached SnO2 nanowire is similar to the SEM image. Fig. 1(d) shows fringe patterns of SnO2 and Co3O4. The spacing between two neighboring SnO2 fringe patterns is 0.335 nm, which indicates a (110) lattice plane; the spacing of 0.244 nm between two neighboring fringe patterns indicates a (311) lattice plane of Co3O4. The inset image of Fig. 1(d) presents a selected area electron diffraction (SAD) pattern of the corresponding nanowire. In this image, well arranged patterns indicating single crystal SnO2 and indistinct ring-type patterns indicating polycrystalline Co3O4 are shown.

Fig. 1.

(a) SEM image of Sample B (inset is SEM image of Sample A), (b) XRD patterns of Samples A (black line) and B (red line), and (c) low-magnification and (d) high-resolution TEM images of Sample B (inset image is SAD pattern of corresponding nanowire).

3.2Gas sensing properties

To find optimum amount of attached Co3O4 nanoparticles presenting best acetone sensing response, 6 samples are synthesized followed by Co3O4 nanoparticle attachment process. Sensing responses are measured using these samples supplying 50 ppm acetone gas at 200 °C. Fig. 2 (a)–(e) present dynamic acetone sensing response curves of these samples. Fig. 2 (a) presents curve of as-synthesized SnO2 nanowires and (b)–(e) present sensing curves of sample B, sample C, sample D, and Sample E, respectively. Inset image of Fig. 2 (a) and (e) present enlarged sensing curves, since response variations of these samples are too small to recognize in this response range. Fig. 3 presents summary of response values measured in Fig. 2. Followed by this values, best sensing response among these samples are presented at sample B. Acetone sensing response of sample B was enhanced drastically enhanced as Co3O4 nanoparticle attachment process was performed one time, but responses decrease as the cycles of this process is repeated more. Therefore, detailed sensing measurements are analyzed using sample A as reference and sample B as optimal sample. Fig. 4 (a) presents the response of Samples A and B with varying operating temperature to determine the optimum sensing condition. The temperature was varied from 100 °C to 400 °C at 25 °C intervals. Under these conditions, both sensors present their best sensing response at 300 °C. However, in every section, Sample B exhibits a sensing response superior to that of Sample A. Fig. 4 (b) and (c) present the dynamic response curves of the samples as a function of the acetone concentration, and Fig. 4 (d) presents the summarized sensing response curves of the corresponding sensors. For every concentration, Sample B exhibits a superior response to that of Sample A. Sample B presents a seven-fold enhanced response when exposed to 50 ppm acetone gas. Furthermore, when both sensors are exposed to 0.5 ppm acetone gas, the sensing signal of Sample B can be discerned clearly, whereas it is difficult to recognize the acetone gas signal of Sample A. Because signal of Sample A (1.18) is too weak, it is buried in noise. However, as the response of Sample B is 2.2-fold enhanced, the signal patterns can be discerned clearly. Therefore, sub-ppm scale acetone gas can be detected using Sample B. Fig. 5 (a) and (b) present response and recovery times based on the curves in Fig. 4 (b) and (c), respectively. The response times of both sensors present almost similar tendency although response times of sample A are slightly faster. On the other hand, results of recovery times of sample B are improved than sample A in every concentration. And followed by Fig. 5 (b), recovery times of sample A are reduced followed by the increment of acetone concentration likely to sample B, but this trend is inverted and recovery time of sample A is worsened after acetone gas concentration increase over 2 ppm. In contrast, recovery times of sample B is reduced as the acetone gas concentration increase. The recovery time of sample B is 122 s whereas 203 s in case of sample A when exposed to 50 ppm acetone gas, and it is approximately 40% improved results as Co3O4 nanoparticles are attached.

Fig. 2.

Normalized dynamic sensing response curves of (a) pure and (b) once, (c) twice, (d) 3 times, and 4 times Co3O4 nanoparticle attached SnO2 nanowires supplying 50 ppm acetone gas in 300 °C.

Fig. 3.

Summarized acetone sensing responses of (a) pure and (b) once, (c) twice, (d) 3 times, and 4 times Co3O4 nanoparticle attached SnO2 nanowires.

Fig. 4.

(a) Acetone sensing response of Samples A and B as a function of operating temperature at 25 °C intervals, dynamic response curves of (b) sample A and (c) sample B as a function of supplied acetone concentration, and (d) summarized acetone sensing response of Samples A and B based on figs. (b) and (c) (inset image is the acetone sensing response graph in low-concentration acetone gas).

Fig. 5.

(a) Response and (b) recovery times of acetone gas sensors as a function of acetone concentrations.


Fig. 6 (a) presents the response of both sensors to VOC gases to analyze the selectivity of sensors. The responses to 50 ppm ethanol, methanol, toluene, and xylene gases were measured and compared with the response to acetone gas. In Sample A, the response to acetone gas is similar to that of ethanol and methanol, whereas in Sample B, the response is 2.45 times higher than that to ethanol gas; the best response is exhibited without acetone gas. Theses phenomena are derived from the synergistic effect of the SnO2 and Co3O4 nanostructures. The attached Co3O4 nanoparticles, which present a positive response to acetone gas, result in promising sensing response of the SnO2 nanowires to acetone gas; the sensing response can be maximized when exposed to acetone gas. Fig. 6 (b) presents the long-term stability of both sensors (sample A and B). Followed by the graphs, response of sample B is slightly damped during this period, but its value is small and can be negligible. In other words, the sensors present stable sensing performance possible to apply commercial sensor.

Fig. 6.

(a) Gas sensing selectivity and (b) long term stabilities of both sample-based sensors.

3.3Gas sensing mechanisms

SnO2 is an n-type semiconductor, in which electrons are the major carrier. When SnO2 nanowires are exposed to ambient air, their resistance increases because oxygen molecules in the air are adsorbed on the nanowires and absorb electrons to transform into oxygen ions followed by described equations [31]:

Therefore, the carrier concentration decreases, and the depletion layer is extended as presented in Fig. 7 (a). In contrast, when acetone gas is supplied to the SnO2 nanowires, the adsorbed oxygen ions react with acetone sensor, and the absorbed ions revert back to the nanowires followed by described equations [32]:

Fig. 7.

Schematic images of electrical structures of Sample A placed in (a) air and (b) acetone ambient, respectively, and (c) schematic images of electrical structures of Sample B in (d) air and (e) acetone ambient, respectively.


Therefore, carriers in the SnO2 nanowires increase, resulting in a decreasing in the resistance while the depletion layer decreases, as presented in Fig. 7 (b). Owing to the variations in the resistance, the sensing response of the SnO2 nanowires can be measured.

Meanwhile, by attaching Co3O4 nanoparticles, which are p-type semiconductors, the resistance of the nanowires changes more drastically. As Co3O4 nanoparticles generate p-n junctions to contact with the SnO2 nanowires, electrons in SnO2 become extinct, combining with holes in Co3O4. The depletion layer of the SnO2 nanowires is generated near the attached Co3O4. In contrast, when it is placed in ambient air, electrons are extracted from the nanowires in the same manner as the former case, and the depletion layer extends, However, because some depletion layer in the nanowire already exists, the depletion layer of the nanowires extends more. Consequently, the conductive channel should be almost eliminated in this case, as presented in Fig. 7 (c). Therefore, the resistance increases drastically. In contrast, when acetone gas is supplied to the nanowire, oxygen ions are removed and the depletion layer decreases owing to the reverted electrons, as presented in Fig. 7 (d). In this case, because conductive channel of the nanowire is much wider than the depletion layer, the effect of the depletion layer generated by the p-n junction is negligible. Therefore, because the variation in the resistance of the nanowire is more drastic, the sensing response is enhanced more.


SnO2 nanowires were synthesized to fabricate an acetone gas sensor, and Co3O4 nanoparticles were attached to improve its response and selectivity in this research. Furthermore, to find optimum amount of attached Co3O4 nanoparticles presenting best sensing properties, several kinds of samples were synthesized followed by cycles of Co3O4 nanoparticle attachment process. As a result, the response of the sensor (sample B) was enhanced 7 times compared to as-synthesized SnO2 nanowire-based sensor, and the selectivity of this sensor is improved 2.45 times. It can be estimated that this effect originated from the p-n junction between the n-type SnO2 nanowire and p-type Co3O4 nanoparticle. Because of these heterojunctions, the variation in the depletion layer was maximized, and the resistance changed more drastically. And to attach optimum amount of Co3O4 nanoparticles on the SnO2 nanowires, these phenomena can be maximized and present best sensing properties.

Conflicts of interest

The authors declare no conflicts of interest.


This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A4A1023746).

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