Tunable macro–mesoporous ZnO nanostructures for highly sensitive ethanol and acetone gas sensors

Abstract

Tunable macro–mesoporous ZnO (M/m-ZnO) nanostructures with a wurtzite hexagonal structure have been successfully synthesized using polymer colloids as a hard template and 20–40 nm ZnO nanoparticles as a precursor via controlling the ratios of colloids and ZnO nanoparticles. The as-prepared macro–mesoporous ZnO nanostructures are investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) techniques. Gas sensing performance is carried out for ethanol and acetone at different temperatures and concentrations. The gas sensing results show that the tunable M/m-ZnO nanostructures exhibit excellent gas sensing performances because the hierarchical macro–mesopores provide a large contacting surface area for electrons, oxygen and target gas molecules, offer smooth transport channels for target gas diffusion and finally enhance the gas molecular diffusion kinetics. The M/m-ZnO-600 nm demonstrates the best performance for ethanol and acetone detection. In addition, the sensor based on M/m-ZnO-600 nm gives obvious tendencious selectivity and a good repeatability and long-term stability to acetone at the optimum temperature of 300 °C. This work suggests that the macro–mesoporous ZnO is a potential material for advanced gas sensing.

---

1. Introduction

Porous nanomaterials due to their unique characteristics, such as small size effects, quantum confinement effects and surface and interfacial effects, etc., have recently attracted remarkable attention. A series of porous semiconductor materials such as ZnO,^1,2 SnO₂,³ TiO₂ ^4,5 and CuO⁶ are widely used for gas sensors, biosensors, nano-generators, solar cells and other functional devices.^7–10

Among the various porous semiconductors, ZnO, an important semiconductor material with wide band gap (E_g ≈ 3.2 eV) and large exciton binding energy (60 meV), has a great potential in sensors,¹¹ light-emitting diodes,¹² photocatalysis¹³ and other fields. Previous studies suggest that the structure and the size of materials have strong influences on their electrical and optical properties.^14,15 Thus scientists have used various methods such as chemical vapor deposition, hydrothermal method, wet chemical synthesis, template-based method and electrospinning method to obtain different ZnO nanostructures with quite good performances.^16–20 For example, ZnO quantum dots synthesized by wet chemical method shows good sensitivity for nitrogen oxide, acetone and methanol at low concentration.²¹ However, such small nanoparticles tend to aggregate resulting in the decreased gas sensitivity due to the small surface area.²² Besides, the small nanoparticles will be compactly sintered during sensor preparation process via thermal heating. The final test on device for gas sensing may not reflect the real performance for such small size of nanoparticles. Thus it is necessary to design novel ZnO nanostructures to avoid such a shortage.

It has been reported that the mesoporous structure can provide high surface area and well-defined porous architecture for high gas response and rapid gas responding kinetics.²³ Therefore, tremendous three-dimensional (3D) ZnO porous nanostructures have been prepared such as hollow spheres, flower-like structures, mesoporous microspheres, nest-like hierarchically porous structures and so on.^24–34 Among the various porous nanostructures, the macro–mesoporous nanostructure has great advantages comparing to other nanostructures.^35–38 On the one hand, the macro–mesopores guarantee the smooth transport channels for target gas and enhance the gas molecular diffusion kinetics. On the other hand, the existence of mesopores can provide a large surface area to absorb gas. For example, Wang et al. have synthesized the nest-like ZnO porous structures with size of 1.0–3.0 μm through annealing the zinc hydroxide carbonate precursor. The nest-like ZnO porous structure shows excellent high sensitivity and fast response and recovery speed.³³ Liu et al. have reported the synthesis of single-crystalline ZnO nanosheets with porous structure by annealing ZnS(ethylenediamine) complex precursor, which exhibits highly sensitive performance.³⁹ However, these reports on 3D ZnO porous nanostructures are mainly synthesized via annealing the precursors.^33,39 The sizes of macropores are not tunable. Although the previous report has demonstrated that the mesoporous structure is suitable for high gas response and rapid gas responding kinetics,²³ the study on the macroporous structure is still rare. To the best of our knowledge, there are no reports about the impact of the aperture tunable ZnO macroporous material for gas sensitivity. So it is necessary to synthesize the aperture tunable 3D macro–mesoporous ZnO nanostructures and study the effect of the macroporous and mesoporous structure on gas sensing performance.

Herein, we report tunable macro–mesoporous ZnO (M/m-ZnO) nanostructures using polymer colloids as a hard template and 20–40 nm ZnO nanoparticles as ZnO precursor through controlling the ratios of the template and ZnO nanoparticles. The results show that the as-prepared M/m-ZnO nanostructures demonstrate better ethanol and acetone sensing properties than ZnO commercial nanoparticles (ZnO-CP). Further, the M/m-ZnO structures exhibit enhanced sensitivities with the increase of macroporous diameter. The sensors based on M/m-ZnO-600 nm demonstrate the best performance. Out results suggest such high porosity of tunable macro–mesoporous ZnO nanostructures are suitable for high performance gas sensing.

2. Experimental

2.1 Materials

Styrene, methyl methacrylate (MMA), 3-sulfopropyl methacrylate potassium (SPMAP), ammonium persulfate, ammonium bicarbonate, Zn(Ac)₂·2H₂O, ethylene glycol (EG), ethanol and acetone are purchased from Aldrich.

2.2 Colloids preparation

The mono-dispersed colloids of poly(styrene-methylmethacrylate-3-sulfopropyl methacrylate potassium) (P(St-MMA-SPMAP)) beads are synthesized by a soap-free emulsion polymerization:^13,40 22.5 mL styrene, 1.25 mL MMA and 110 mL water are mixed and heated to 70 °C under N₂ atmosphere. Then 10 mL water with dissolved 0.4 g ammonium persulfate, 0.8 g ammonium bicarbonate and (0.06–0.3 g) SPMAP are added to initiate the reaction, which lasts for 8 hours. The diameters of colloids would change by varying the amount of SPMAP. And the colloids with diameters of 400 nm, 520 nm and 600 nm have been obtained (Fig. S1†). Finally, the as-prepared colloids are diluted in water with a solid content of 0.25 wt% for further use.

2.3 ZnO nanoparticles synthesis

The ZnO nanoparticles (ZnO-NPs) are synthesized according to our previous work with a slight modification:⁴¹ 0.05 mol Zn(Ac)₂·2H₂O is dissolved in 80 mL EG by magnetic stirring to form a mixed solution at room temperature. Then, the resultant solution is transferred into a Teflon-lined stainless-steel autoclave, sealed and heated in 160 °C for 1 h. The white product is centrifuged and washed with deionized water and ethanol repeated for several times. Finally, the prepared ZnO nanoparticles (Fig. S1†) are dispersed in water with a solid content of 0.01 g mL⁻¹ for further use.

2.4 Macro–mesoporous ZnO materials synthesis

Typically, 5 mL prepared ZnO-NPs aqueous suspension and (40–2.8) mL polymer emulsion are mixed under magnetic stirring for 1–2 hours. The mixture is then filtrated and the resulting white solids are placed in 40 °C oven for 8 h. The obtained ZnO/P(St-MMA-SPMAP) composite is calcined in air at 300 °C with a ramp rate of 1 °C min⁻¹ for 2 h and then raised to 450 °C at 1 °C min⁻¹. After 4 h, the oven is cooled to room temperature. The macro–mesoporous ZnO (M/m-ZnO) materials with different pore sizes are obtained. The proportions of the colloidal suspension and ZnO-NPs are 1 : 3.5, 1 : 2, 2 : 1 for 400 nm, 520 nm and 600 nm, respectively. The final samples are designated as M/m-ZnO-400 nm, M/m-ZnO-520 nm and M/m-ZnO-600 nm, respectively.

2.5 Characterization

X-ray diffraction patterns (XRD) are obtained with a Bruker D8 Advanced diffractometer using Cu Kα radiation (λ = 1.54056 Å). Field emission scanning electron microscopy (FESEM) is performed on a Hitachi S-4800 electron microscope. Transmission electron microscopy (TEM) and high resolution transmission electron microscopy (HRTEM) are performed on a JEOL JEM-2100F microscope with an acceleration voltage of 200 kV. The specific surface areas of the samples are analyzed by nitrogen adsorption on a Micromeritics Tristar II 3020 apparatus via Brunauer–Emmett–Teller (BET) method. The pore size distribution is calculated according to BJH method from the N₂ adsorption isotherms. The gas response tests are performed on WS-60A gas sensing test system (Weisheng Electronics Co. Ltd., China). The gas response value is defined as following: S = R_a/R_g, where R_a and R_g are the sensor resistance in air and testing gas environment, respectively.

3. Results and discussion

The tunable macro–mesoporous ZnO nanostructures with different pore size from 400 nm to 600 nm are first characterized by FESEM (Fig. 1). The SEM images (Fig. 1a, c and e) of the products show that macro–mesoporous structure is evenly distributed inside the powders. The top-view SEM images at low magnifications (insert images of Fig. 1a, c and e) display that the structures of macro–mesoporous ZnO are uniform and continuous. The size of macroporous ZnO can be tuned via changing the diameter of polymer colloids. High magnification SEM images (Fig. 1b, d and f) demonstrate that a series of macropores are closely arranged. In addition, there are a large number of mesoporous structures between the walls of macropores via ZnO-NPs aggregation, which further increases the specific surface area. Moreover, it shows that the macroporous structures are partially three-dimensional interconnected. This can facilitate the gas molecules diffusion and transportation.

Fig. 1 SEM images of the tunable M/m-ZnO nanostructures: (a and b) M/m-ZnO-400 nm, (c and d) M/m-ZnO-520 nm and (e and f) M/m-ZnO-600 nm. The inserts in (a), (c) and (e) are the images from the top-view of the particles.

Fig. 2a shows the XRD patterns of the as-prepared tunable M/m-ZnO nanostructures and ZnO commercial nanoparticles (ZnO-CP). All the peaks are indexed to wurtzite structure of ZnO (JCPDS no. 079-2205) and no impurity peaks are detected. Three main peaks corresponding to (100), (002) and (101) crystal planes are clearly displayed respectively. Comparing to the three main peaks of tunable M/m-ZnO nanostructures and ZnO-CP, the diffraction peaks of tunable M/m-ZnO nanostructures are much sharper and higher, indicating the good crystallization of M/m-ZnO. Table 1 gives the crystalline sizes of M/m-ZnO and ZnO-CP. It shows that the grain size of ZnO-CP is 18 nm, which is much smaller than those of the M/m-ZnO nanostructures.

Fig. 2 (a) XRD patterns and (b) nitrogen adsorption/desorption isotherms of the tunable M/m ZnO nanostructures and ZnO-CP. The inset in (b) is the corresponding pore size distribution.

Table 1 The structure parameters of the tunable M/m-ZnO nanostructures and ZnO-CP

Samples	Crystalline size (nm)	Pore diameter (nm)	BET surface area (m^2 g^−1)
M/m-ZnO-400 nm	∼33	40	16.4
M/m-ZnO-520 nm	∼32	39	12.5
M/m-ZnO-600 nm	∼30	32	19.8
ZnO-CP	∼18	29	37.8

---

In addition to the structure, the porosity and surface area of materials are important for gas sensing properties. Fig. 2b shows the nitrogen adsorption–desorption isotherms of the tunable M/m-ZnO nanostructures and ZnO-CP, indicating the presence of macropores in the M/m-ZnO nanostructures. The BET surface area of the tunable M/m-ZnO nanostructures changes a little when the aperture is different, as displayed in Table 1. However, the BET surface area of ZnO-CP is 37.8 m² g⁻¹, which is much higher than those of M/m-ZnO nanostructures due to the small particle size. The calculated pore size distribution indicates that the sizes of mesopores are 40 nm, 39 nm and 32 nm when the aperture is tuned from 400 nm to 600 nm. The pore size of ZnO-CP is 29 nm due to the small nanoparticles aggregation, which is a little smaller than those of the as-prepared M/m-ZnO nanostructures.

Transmission electron microscopy (TEM) is further performed to reveal the detail structures of the as-prepared M/m-ZnO-400 nm as shown in Fig. 3. The low magnification TEM images (Fig. 3a and b) show that the macroporous structures are assembled by a series of ZnO nanoparticles with uniform size 30 nm. The HRTEM image (Fig. 3c) clearly demonstrates that the lattice fringe spacing is measured to be 2.60 Å, corresponding to the (002) crystal plane of hexagonal wurtzite ZnO.

Fig. 3 (a and b) Low magnification TEM and (c) HRTEM images of M/m-ZnO-400 nm.

It is well known that the sensitivity of ZnO gas sensor is closely related to operating temperature and gas concentration. Generally, all sensors have an optimum work temperature.³⁸ With the working temperature increasing, the redox reaction between reducing gas and oxygen ion will strengthen resulting in a lower resistance. However, too high temperature weakens the reaction due to the gas desorption. Therefore, an optimal operating temperature is often obtained for semiconductor gas sensor and the sensitivity will decrease above the optimum operating temperature.^42–45

Fig. 4a presents the gas sensitivity of M/m-ZnO nanostructures to 100 ppm ethanol with operating temperatures ranging from 240 °C to 370 °C. It shows that the maximum sensitivity locates at 340 °C. Then the sensitivity decreases with the operating temperature increasing. Fig. 4b displays the gas sensitivity curves of M/m-ZnO nanostructures to acetone at the different operating temperature, where the acetone concentration is 100 ppm. The results are quite similar to ethanol. Its gas sensitivity reaches the maximum at 300 °C, and then decreases with the operating temperature increasing. It is noted that the sensitivity of the as-prepared tunable M/m-ZnO nanostructures is much higher than that of ZnO-CP. At optimum work temperature, the sensitivities of M/m-ZnO nanostructures increases with the macroporous size increasing. The gas sensitivity of M/m-ZnO-600 nm is 30 for ethanol, which is 3 times higher than that of ZnO-CP. The gas sensitivity of M/m-ZnO-600 nm reaches up to 33 while the gas sensitivity of ZnO-CP is only 8 for acetone. This result indicates that the key point for gas sensing is not determined by BET surface but by the macro–mesoporous structure, i.e., it is the macroporous size that mainly determines the gas sensing properties in our case. Fig. 4c demonstrates the gas sensitivities of the M/m-ZnO-600 nm sensors to different concentration of ethanol and acetone at 300 °C. The sensors based on M/m-ZnO-600 nm nanostructures truly exhibit apparent selectivity for ethanol and acetone. At the same conditions, the sensors based on M/m-ZnO-600 nm exhibit much higher sensitivity to acetone than to ethanol, indicating a preferred selectivity to acetone. In addition, increasing the gas concentration strengthens the selectivity to acetone for M/m-ZnO-600 nm.

Fig. 4 Gas sensitivities at different operating temperatures for the M/m-ZnO nanostructures. (a) 100 ppm ethanol, (b) 100 ppm acetone and (c) the gas sensitivities of the M/m-ZnO-600 nm sensor to different concentration of ethanol and acetone at 300 °C, showing the preferred selectivity to acetone.

Fig. 5 presents the gas sensing response curves of the tunable M/m-ZnO nanostructures to ethanol and acetone at different gas concentrations under the optimized temperatures, respectively. When the concentration of the detected gas increases from 10 ppm to 500 ppm, the responses values of sensors are obviously improved. Fig. 5a clearly shows that the response curves of the M/m-ZnO nanostructures to ethanol are much higher than those of ZnO-CP. The response value of M/m-ZnO-600 nm to 10 ppm ethanol is about 12.8, which is 3.8 times comparing with that of ZnO-CP (3.4) as illustrated in Table 2. A similar result is observed to acetone (Fig. 5b). The response value of M/m-ZnO-600 nm is 5.8 to 10 ppm acetone while the response value of ZnO-CP is only 3. Table 2 lists all the values of the M/m-ZnO nanostructures comparing with those of ZnO-CP. The good performance of the tunable M/m-ZnO nanostructures indicates the hierarchical macro–mesoporous structure is suitable for gas sensing.

Fig. 5 Gas response value curves of the M/m-ZnO nanostructures to (a) ethanol (340 °C) and (b) acetone (300 °C) at different concentrations.

Table 2 The sensing response values of the M/m-ZnO nanostructures and ZnO-CP to different concentrations of ethanol and acetone under 340 °C and 300 °C, respectively

Samples	Ethanol/ppm					Acetone/ppm
	10	50	100	250	500	10	50	100	250	500
M/m-ZnO-400 nm	8.8	16.4	20.4	31.1	40	4.8	14.5	19.4	28.4	44.2
M/m-ZnO-520 nm	10.4	17.1	22.3	33.2	42.4	5.1	15.1	21.3	33.8	47.5
M/m-ZnO-600 nm	12.8	22.6	30.1	46	55.1	5.8	19.3	32.7	60.4	97.1
ZnO-CP	3.4	6.6	10.4	13.4	17.7	3.0	5.8	8.0	11.1	15.9

---

Fig. 5 also shows that the sensors are stable although there is a little fluctuation in the curves, similar to the reported results for other structures.^32,46 The saturation phenomenon is not observed even the gas concentration reaching 500 ppm, indicating that the tunable M/m-ZnO nanostructures can be applied to detect ethanol and acetone ranging from very low to very high concentrations. This is very important for gas detection. These results suggest that the presence of macro–mesopores can provide the smooth transport channels for target gas and enhance the gas molecular diffusion kinetics. Further, it seems that larger macroporous size is very helpful for gas diffusion, which may have major effect on the sensitivity of gas sensors. More work is carrying out to prove this hypothesis.

To investigate the stability of the sensors, which is another important parameter for gas sensor, a continuity and repeatability test is carried out.⁴⁷ As depicted in Fig. 6, the result of ten-day cycle test on M/m-ZnO-600 nm to 100 ppm acetone shows that the sensor has a good repeatability and long-term stability. In particular, the values of sensitivity in cycle test are very close. The relative standard deviation (RSD) of the sensitivity values is only 1.38%, which further confirms that the M/m-ZnO gas sensor has a high stability and can be used repeatedly for a long time.

Fig. 6 Stability of the M/m-ZnO-600 nm sensor to 100 ppm acetone at 300 °C.

4. Conclusions

Tunable macro–mesoporous ZnO nanostructures have been successfully prepared using polymer colloids as hard template and 20–40 nm ZnO nanoparticles as precursor. XRD, SEM and HRTEM results show that the macro–mesoporous ZnO nanostructure belongs to hexagonal wurtzite crystal system. Comparing to the gas sensitivity of ZnO-CP, the as-prepared M/m-ZnO nanostructures exhibit excellent gas sensing performances owing to hierarchical macro–mesopores providing a large contacting surface area for electrons, oxygen and target gas molecules and ensuring the smooth transport channels for target gas diffusion and enhancing the gas molecular diffusion kinetics. As a result, the macro–mesoporous ZnO nanostructures demonstrate high sensitivity to acetone and ethanol. The M/m-ZnO-600 nm exhibits the best performance for gas detection. It also demonstrates obvious tendency and good stability to acetone at the optimum temperature of 300 °C. Our work here verifies that the macroporous nanostructure plays a major role on gas sensitivity, indicating the macro–mesoporous ZnO nanostructures are very suitable for gas sensors.

Acknowledgements

This work is realized in the frame of a program for Changjiang Scholars Innovative Research Team (IRT_15R52) of Chinese Ministry of Education. B. L. Su acknowledges the Chinese Central Government for an “Expert of the State” position in the Program of the “Thousand Talents”. Y. Li acknowledges Hubei Provincial Department of Education for the “Chutian Scholar” program. This work is also financially supported by Hubei Provincial Natural Science Foundation (2014CFB160, 2015CFB516 and 2015CFB428), Students Innovation and Entrepreneurship Training Program Fund at WUT (20131049701006), the National Science Foundation for Young Scholars of China (No. 21301133 and No. 51502225), Hebei Province Science and Technology Support Program (No. 15274010D), the Fundamental Research Funds for the Central Universities (2014-IV-057) and Self-determined and Innovative Research Funds of the SKLWUT (2015-ZD-7).

References

1. D. An, Y. Li, X. Lian, Y. Zou and G. Deng, Colloids Surf., A, 2014, 447, 81.
2. Q. Jia, H. Ji, Y. Zhang, Y. Chen, X. Sun and Z. Jin, J. Hazard. Mater., 2014, 276, 262.
3. X. Xu, J. Zhuang and X. Wang, J. Am. Chem. Soc., 2008, 130, 12527.
4. C. J. Chang, C. K. Lin, C. C. Chen, C. Y. Chen and E. H. Kuo, Thin Solid Films, 2011, 520, 1546.
5. B. Lyson-Sypien, A. Czapla, M. Lubecka, P. Gwizdz, K. Schneider, K. Zakrzewska, K. Michalow, T. Graule, A. Reszka, M. Rekas, A. Lacz and M. Radecka, Sens. Actuators, B, 2012, 175, 163.
6. Y. Qin, F. Zhang, Y. Chen, Y. Zhou, J. Li, A. Zhu, Y. Luo, Y. Tian and J. Yang, J. Phys. Chem. C, 2012, 116, 11994.
7. J. B. Baxter and E. S. Aydil, Appl. Phys. Lett., 2005, 86, 053114.
8. M. Song, Y. Zhang, M. Peng and J. Zhai, Nano Energy., 2014, 6, 66.
9. M. Zhang, T. Ning, S. Zhang, Z. Li, Z. Yuan and Q. Cao, Mater. Sci. Semicond. Process., 2014, 17, 149.
10. Z. Zhang, Y. Xie, Z. Liu, F. Rong, Y. Wang and D. Fu, J. Electroanal. Chem., 2011, 650, 241.
11. P. P. Sahay and R. K. Nath, Sens. Actuators, B, 2008, 134, 654.
12. K. Kim, T. Moon, M. Lee, J. Kang, Y. Jeon and S. Kim, Solid State Sci., 2011, 13, 1735.
13. J. Liu, J. Jin, Y. Li, H. W. Huang, C. Wang, M. Wu, L. H. Chen and B. L. Su, J. Mater. Chem. A, 2014, 2, 5051.
14. K. I. Mohammed, F. M. Jasim and M. I. Azawe, Curr. Appl. Phys., 2014, 14, 1318.
15. M. A. Rafea, A. A. M. Farag and N. Roushdy, Mater. Res. Bull., 2012, 47, 257.
16. B. H. Juárez, P. D. García, D. Golmayo, A. Blanco and C. López, Adv. Mater., 2005, 17, 2761.
17. Y. Li, W. Cai, G. Duan, B. Cao, F. Sun and F. Lu, J. Colloid Interface Sci., 2005, 287, 634.
18. R. K. Sharma and R. Ghose, Ceram. Int., 2014, 40, 10919.
19. S. Wei, Y. Yu and M. Zhou, Mater. Lett., 2010, 64, 2284.
20. S. Yamashita, H. Watanabe, T. Shirai, M. Fuji and M. Takahashi, Adv. Powder Technol., 2011, 22, 271.
21. A. Forleo, L. Francioso, S. Capone, P. Siciliano, P. Lommens and Z. Hens, Sens. Actuators, B, 2010, 146, 111.
22. Y. F. Sun, S. B. Liu, F. L. Meng, J. Y. Liu, Z. Jin, L. T. Kong and J. H. Liu, Sensors, 2012, 12, 2610.
23. J. H. Lee, Sens. Actuators, B, 2009, 140, 319.
24. J. Li, H. Fan, X. Jia, J. Chen, Z. Cao and X. Chen, J. Alloys Compd., 2009, 481, 735.
25. X. Jia, H. Fan, F. Zhang and L. Qin, Ultrason. Sonochem., 2010, 17, 284.
26. J. Li, H. Fan and X. Jia, J. Phys. Chem. C, 2010, 114, 14684.
27. X. Jia, H. Fan, M. Afzaal, X. Wu and P. O'Brien, J. Hazard. Mater., 2011, 193, 194.
28. Y. Xi, C. G. Hu, X. Y. Han, Y. F. Xiong, P. X. Gao and G. B. Liu, Solid State Commun., 2007, 141, 506.
29. Y. Abdi, S. M. Jebreiil Khadem and P. Afzali, Curr. Appl. Phys., 2014, 14, 227.
30. I. Gonzalez-Valls, Y. Yu, B. Ballesteros, J. Oro and M. Lira-Cantu, J. Power Source, 2011, 196, 6609.
31. P. Rai, S. Raj, K. J. Ko, K. K. Park and Y. T. Yu, Sens. Actuators, B, 2013, 178, 107.
32. J. Rao, A. Yu, C. Shao and X. Zhou, ACS Appl. Mater. Interfaces, 2012, 4, 5346.
33. X. Wang, W. Liu, J. Liu, F. Wang, J. Kong, S. Qiu, C. He and L. Luan, ACS Appl. Mater. Interfaces, 2012, 4, 817.
34. M. Yin, M. Liu and S. Liu, J. Alloys Compd., 2014, 586, 436.
35. M. L. García-Benjume, M. I. Espitia-Cabrera and M. E. Contreras-García, Mater. Charact., 2009, 60, 1482.
36. D. Xie, L. Chang, F. Wang, G. Du and B. Xu, J. Alloys Compd., 2012, 545, 176.
37. J. Zhao, P. Wan, J. Xiang, T. Tong, L. Dong, Z. Gao, X. Shen and H. Tong, Microporous Mesoporous Mater., 2011, 138, 200.
38. J. Zhou, G. Zhao, G. Han and B. Song, Ceram. Int., 2013, 39, 8347.
39. J. Liu, Z. Guo, F. Meng, T. Luo, M. Li and J. Liu, Nanotechnology, 2009, 20, 125501.
40. Z. Yang, L. Yang, M. Zhang and W. Cao, J. Mater. Chem., 2005, 15, 4723.
41. J. Liu, Z. Y. Hu, Y. Peng, H. W. Huang, Y. Li, M. Wu, X. X. Ke, G. V. Tendeloo and B. L. Su, Appl. Catal., B, 2016, 181, 138.
42. J. Liu, X. Wang, Q. Peng and Y. Li, Adv. Mater., 2005, 17, 764.
43. A. P. Lee and B. J. Reedy, Sens. Actuators, B, 1999, 60, 35.
44. K. Arshak and I. Gaidan, Mater. Sci. Eng., B, 2005, 118, 44.
45. C. Wang, L. Yin, L. Zhang, D. Xiang and R. Gao, Sensors, 2010, 10, 2088.
46. M. Ge, T. Xuan, G. Yin, J. Lu and D. He, Sens. Actuators, B, 2015, 220, 356.
47. L. Huang and H. Fan, Sens. Actuators, B, 2012, 171–172, 1257.

---

Footnotes

† Electronic supplementary information (ESI) available: The SEM images of the as-synthesized ZnO nanoparticles and polymer colloids with different sizes. See DOI: 10.1039/c5ra20508e

‡ These authors contributed equally to this work.

---