3D Fe₃O₄ nanoparticle/graphene aerogel for NO₂ sensing at room temperature

Abstract

Three-dimensional graphene aerogel-supported Fe₃O₄ nanoparticles for efficient detection of NO₂ at room temperature are reported. The graphene composite exhibits an interconnected macroporous framework of graphene sheets with uniform dispersion of Fe₃O₄ nanoparticles. Such a hybrid nanostructure would effectively facilitate target gas diffusion and exhibit significantly higher response and faster recovery speed than pure reduced graphene oxide, highlighting the importance of the 3D macropores and high specific surface area of the graphene aerogel support for improving sensing performance. We also propose a hybrid sensing mechanism for the drastic improvement in the sensing behavior which combines the resistance modulation of Fe₃O₄ nanoparticles/graphene heterointerfaces in addition to the radial modulation of the surface depletion layer of the Fe₃O₄ nanocomposite.

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Introduction

Gas sensors are widely considered to have an important role in the quantitative detection of different toxic gases.^1–3 To develop fast responding, sensitive, and highly selective gas sensor materials is of great interest for fundamental and industrial applications. The metal oxide Fe₃O₄ has an inverse spinel structure, symbolized as [Fe³⁺]_A−[Fe²⁺Fe³⁺]_BO₄, in which the A sites (tetrahedral sites) are occupied by Fe³⁺ ions, and the B sites (octahedral sites) by equal numbers of Fe²⁺ and Fe³⁺ ions. As one of the important applications, it is expected that it can be used to build gas sensors, owing to its enhanced ability to serve as active sites for gas molecules.^4–9 However, as with most metal oxide, they often function at elevated temperatures and take a few days to recover, i.e., to desorb the sensed molecules.^10–13 The high operation temperature, slow response and high cost would limit their further applications. To circumvent these problems, one effective strategy is to employ a suitable flexible matrix to improve the electric conductivity.^14,15

Graphene, a two-dimensional sheet of sp²-hybridized carbon atoms has been received much attention due to its unique physical and chemical properties, including high electron mobility, broadband optical response and strong mechanic property.¹⁶ Particularly, graphene or reduced graphene oxide (rGO), has been widely investigated and proven as an effective conducting support to metal oxides in high-efficiency gas sensor.^17–19 However, due to the interaction of NO₂ with the oxygen functional groups or other types of defects, the overall unrecoverable feature of the graphene composite based sensor was also observed.²⁰ More recently, compared with 2D graphene, 3D graphene aerogels (GAs) have drawn much more attention due to their fast mass and electron transport rates benefiting from the 3D interconnected framework and the intriguing properties of graphene.²¹ The continuous porous structure could provide favorable transport pathways for gas which may be beneficial to the fast recovery. Nevertheless, to the best of our knowledge, a study of Fe₃O₄ nanoparticles (NPs) supported on 3D interconnected graphene as a NO₂ gas sensor has not been reported to date.

In this paper, 3D graphene aerogel–Fe₃O₄ NPs (Fe/GAs) nanocomposite has been successfully synthesized by a simple solvothermal route. The composite shows an interconnected macroporous framework of graphene sheets with uniform deposition of Fe₃O₄ NPs. In this composite, the 3D graphene not only creates a conductive matrix that provides a rapid electron channels in sensing process, but also create local heterojunctions at the interfaces of Fe₃O₄ and GAs. Additionally, 3D interconnected macroporous channels provide a large specific surface area which greatly increases the gas contact area, ensuring that the NO₂ molecules easily penetrate the mesoporous. By incorporating 3D interconnected graphene with Fe₃O₄ as conducting network, rapid detection of NO₂ at RT has been successfully realized. The obtained Fe/GAs composite exhibits enhanced performance, fast response and recovery behavior at RT. Furthermore, sensing mechanism for the detection of NO₂ is also discussed.

Experimental

GO was synthesized from natural graphite flakes by a modified Hummers methods.²² The fabrication process for 3D Fe/GAs is demonstrated in Fig. 1. First, 40 ml GO (1 mg ml⁻¹) was dispersion in the 20 ml EG solution, and kept at 80 °C for 11.5 h. Subsequently, 1.2 mmol FeCl₃·6H₂O was added to the above solution under mechanical stirring for 30 min and then 0.34 mmol trisodium citrate and 7.3 mmol sodium acetate were added to form a stable complex solution by stirring for 4 h (Fig. 1a). The mixture was sealed in a Teflon-lined stainless-steel autoclave. The autoclave was heated at 200 °C for 10 h, and then allowed to cool to room temperature to form a 3D graphene-based composite (Fig. 1b). Finally, the obtained GAs supported with Fe₃O₄ NPs was washed with distilled water and absolute ethanol and freeze dried to maintain the 3D monolithic ultralight architecture (Fig. 1c).

Fig. 1 Fabrication process for the 3D Fe/GAs nanocomposite. (a) Stable suspension of GO, iron ions dispersed in a vial. (b) Fe₃O₄-supporting graphene hybrid hydrogel. (c) Monolithic Fe₃O₄/GAs nanocomposite obtained after freeze-drying.

The crystal structure of the as-prepared product was investigated by X-ray diffraction (XRD, D/max2600, Rigaku, Japan) with Cu Kα radiation of wavelength λ = 1.5418 Å. The morphology and microstructure were characterized by field-emission scanning electron microscopy (FE-SEM, SU70, Hitachi, Japan). Transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM) were obtained on a FEI Tecnai F20 microscope equipped with an energy dispersive X-ray (EDX) spectrometer. Raman spectra of the products were characterized by Micro-Raman spectrometer (J-Y; HR800, France) under excitation wavelength of 488 nm. Nitrogen adsorption/desorption isotherms at 77 K were determined by NOVA2000E.

For fabricating the sensor, a paste was produced by mixing the grinding sample with deionized water and coated on the small alumina tube with two Pt electrodes. The measurement was processed by a static process in a test chamber (10 l). Environmental air was used as the reference gas. A calculated amount of the tested gas was injected into the test chamber by a syringe. For the gases like NO₂, CO and H₂, the desired concentration was gained by mixing a known volume of standard gas with air. The desired methanol, acetone and ethanol concentration was obtained by evaporating the certain volume of liquid methanol, acetone and ethanol in the testing chamber. Then the sensor was put into the chamber for the measurement of the sensing performance. When the response reached a constant value, the upper cover of the test chamber was removed and the sensor began to recover in air. The resistances of the sensor in air and target gas were measured with a digital precision multimeter (Fluke, 8846A, U.S.A.) which was connected to personal computer for data processing. The temperature (20 °C) and humidity (10% RH) of the test chamber were well controlled with a humidity/temperature controlling chamber (Espec SETH-EZ-020R, China) during the measurement. The response of the sensor was defined as S = (R − R₀)/R₀ × 100%, here, R₀ and R were the resistances of the sensor in the air and target gas, respectively. In addition, the response time was defined as the time required for the resistance to reach 90% of the equilibrium value after a test gas was injected, and the recovery time was the time necessary for a sensor to attain a resistance of 10% below its original value in air.

Results and discussion

The structure of as-prepared Fe/GAs was investigated by means of XRD, shown in Fig. 2. The XRD pattern of Fe/GAs matches well with the standard Fe₃O₄ card (JCPDS no.19-0629). No diffraction peaks for layered GO can be observed, indicating the successful reduction of GO. A broad diffraction peak of GAs was also observed in Fe/GAs which demonstrates the absence of layer-stacking after the reduction of GO,^23,24 because the graphene sheets were efficiently assembled together into the 3D network structure and most of the graphene sheets were separated by NPs.²⁵

Fig. 2 XRD patterns of the as-prepared Fe/GAs nanocomposite.

The morphology and microstructure of Fe/GAs were examined by SEM, TEM, and HRTEM measurements. SEM images revealed an interconnected, porous 3D graphene framework with continuous macropores in the micrometer size range (Fig. 3a). Better revealed by the high magnification FESEM image in Fig. 3b, it is noteworthy that a significant portion of the Fe₃O₄ NPs anchored uniformly on the graphene layers. The microstructure is also elucidated under TEM to provide further insight about the morphology and structure of the as-prepared Fe/GAs nanocomposite. In good agreement with the FESEM results, a low magnification TEM image (Fig. 3c) further validated the uniform distribution of Fe₃O₄ NPs with a size of about 5 nm. A set of distinct lattice fringes with a spacing of 0.26 nm can be observed in the HRTEM image of a typical Fe₃O₄ NPs (Fig. 3e), which corresponds to the (311) crystal planes of the cubic Fe₃O₄ phase. Furthermore, the selected area electron diffraction (SAED) rings (Fig. 3d) can be indexed to (220), (311), (400), (440) and (511) planes which readily assigned to the crystal planes of the cubic Fe₃O₄ phase. EDX mirco-analysis on the Fe/GAs nanocomposite demonstrates that it consists of C, Fe, O as shown in Fig. 3f. The Cu signal comes from TEM grid.

Fig. 3 Morphology of the as-synthesized samples. (a) and (b) Typical SEM images with different magnification of Fe/GAs nanocomposite revealing the 3D macroporous structure and uniform distribution of Fe₃O₄ NPs in the graphene aerogel. (c) and (d) TEM, HRTEM images of Fe/GAs nanocomposite. (e) SAED pattern of the Fe/GAs nanocomposite. (f) EDX spectrum.

A Brunauer−Emmett−Teller (BET) analysis (Fig. 4a) of nitrogen adsorption/desorption isotherms revealed that the specific surface area of Fe/GAs was 138 m² g⁻¹. Based on the Barrett–Joyner–Halenda model, a well-defined mesopore (3.8 nm) was obtained which may be contributed to the pores existing between the Fe₃O₄ NPs. The mesoporous configuration would benefit gas diffusion to active sites. The macropores of 3D graphene, which is beneficial to transport of the target gas which may be contributed to improving the response speed. Raman spectroscopy is a forceful means to investigate the modification of graphene and their derivatives.^26,27 The Raman spectra of Fe/GAs and rGO shown in Fig. 4b exhibit the regular two peaks, corresponding to the D band in the vicinity of 1357 cm⁻¹ and the G band in the vicinity of 1586 cm⁻¹, respectively. The D-band is the A_1g symmetry mode; the G-band can be attributed to the E_2g mode of the sp² carbon atoms.²⁸ As shown, the I_D/I_G value of the composite is bigger than that of rGO. The increased I_D/I_G indicates that the Fe₃O₄ NPs lead to the increased disorder of graphene layers.^29,30

Fig. 4 (a) Nitrogen adsorption–desorption isotherm of as-synthesized Fe/GAs nanocomposite; the inset is the pore size distribution of Fe/GAs. (b) Raman spectrum of the Fe/GAs nanocomposite.

The sensing capability of the Fe/GAs nanocomposite was investigated systematically. The dynamic response resistances of the sensors based on Fe/GAs nanocomposite (Fig. 5a) to different NO₂ concentration were investigated at RT. The resistance of the sensor decreases upon exposure NO₂, whereas it increases upon the removal of NO₂. Furthermore, the response of the sensor to NO₂ increased with the increasing of the NO₂ concentration. The response transients of the Fe/GAs nanocomposite sensor to 400 ppm NO₂ was measured at RT (Fig. 5a), the response, response time and recovery time were about 24.2%, 275 s and 738 s, respectively. The responses to 30, 50, 100 and 200 ppm NO₂ were about 4.1%, 6.4%, 10% and 14.7%, respectively. The three reversible cycles of the response curve to 400 ppm NO₂ indicated a stable and repeatable response characteristic at RT, as shown in Fig. 5b. As compared with Fe/GAs sample, the sensing properties of pure rGO were given. The first time exposure of the pure rGO based sensors to 400 ppm NO₂ induced a large decrease in the resistance while the resistance was not fully recovered for about 10 min after NO₂ was removed as shown in Fig. 5c. The sensor response to NO₂ as a function of concentration is illustrated in Fig. 5d. It can be seen clearly that the response of both sensors increase with increasing gas concentration, however, the Fe/GAs sensor possesses higher responses than those of pure rGO. Nevertheless, it should be noted here that the resistance of pure Fe₃O₄ prepared with a similar method without rGO intercalation is large (>1000 MΩ) at RT and is not measurable using the multimeters available in the laboratory. As a result, the improved sensitivity and fast recovery speed of the Fe/GAs may be attributed to forming heterostructure between graphene and Fe₃O₄ and its interconnected macroporous features which could build an excellent 3D conductive network for electron transfer, providing fast and versatile transport pathways for gas diffusion.^25,31

Fig. 5 (a) Response of the sensor based on Fe/GAs nanocomposite to different concentrations of NO₂ gas at RT. (b) Periodic exposure of Fe/GAs nanocomposite to NO₂ gas of 400 ppm at RT. (c) Response of the sensor based on rGO to different concentrations of NO₂ gas at RT. (d) The comparison of responses of Fe/GAs nanocomposite and rGO to different concentrations of NO₂ at RT.

From the view of the practical application, a sensor should present rather high selectivity. Fig. 6 shows the bar graph of the response of the sensor based on the as-prepared Fe/GAs and pure rGO to various gases with the concentration of 200 ppm at RT, including H₂, methanol, acetone, ethanol, CO, and NO₂. The results indicate that the sensor using Fe/GAs nanocomposite had improved selectivity compared to pure rGO and exhibited lower responses to acetone, ethanol than that of the response to NO₂, and were almost insensitive to H₂, methanol and CO. The phenomenon indicated that decoration of the rGO with metal oxides could efficiently improve the sensitivity and particularly the selectivity of the rGO based sensors.^32–34

Fig. 6 Comparison of responses of Fe/GAs composite to various gases at RT.

In order to explain the operation of the sensing mechanisms in Fe/GAs composites that leads to their exceptionally performance, two mechanisms must be considered (Fig. 7). First, we adopt the well-known ionosorption model as follows.^4,35 In air ambient conditions, oxygen molecules adsorb, diffuse, and trap electrons from which trap electrons from the conduction band of Fe₃O₄ NPs to form oxygen adsorbates (O₂⁻, O⁻).³⁵ An electron-depleted region is established due to the extraction of electrons by these adsorbed ions. The width of the depleted region increases or decreases as the chemisorbed oxygen reacts with the oxidizing or reducing analytes, respectively. For example, when the target gas molecules (NO₂) directly adsorb onto Fe₃O₄ NPs and react with oxygen adsorbates. The interaction has been proposed as follows:^36,37

NO₂(gas) + O₂⁻(ads) + 2e⁻ → NO₂⁻(ads) + 2O⁻(ads) (1)

NO₂(gas) + O⁻(ads) → NO₃⁻(ads) (2)

Fig. 7 NO₂ gas detection mechanism of Fe/GAs composite.

Second, we will explain the sensing mechanism, with regard to the Fe₃O₄/rGO heterointerfaces. Because of the larger electron affinity (∼4.75 eV), GAs acts as electron acceptor and tends to pull electrons from Fe₃O₄ NPs, forming local heterojunctions. This also results in an increase in the amount of adsorbed oxygen, resulting in more variation in the ionosorbed oxygen concentration. When the sensor is exposed to oxidizing gas NO₂, the gas molecules could directly attract the electrons from Fe/GAs composites, due to the high electron affinity of the NO₂ molecules, which leads to electron transfer from the Fe/GAs composites layer to NO₂ and forms NO₂⁻. The process leads to decreasing of electron density, increasing of the hole carriers density on the surface of Fe/GAs nanocomposite. Thus the Fe/GAs nanocomposite exhibits decrease in resistance (shown in Fig. 4) due to the p-dominant conducting properties of graphene when it is exposed to NO₂ gas.³⁸ Due to the resistance modulation caused by these two sources and the existing of the continuous macropores in the Fe/GAs nanocomposite, Fe/GAs nanocomposite showed a larger change in their resistance and exhibited rapid recovery speed compared to rGO.

Accordingly, we suggest that the combination of two factors are responsible for the enhancement of the sensing capabilities of Fe/GAs nanocomposite. First, the 3D macroporous structure could act as multidimensional transport pathways for gas diffusion and provide more active sites for the reaction with NO₂. Second, graphene acts as substrate not only enhanced the conductivity of the sensor component, but also created a heterojunctions between the graphene and the Fe₃O₄ NPs.

Conclusions

In summary, we have successfully fabricated 3D Fe/GAs nanocomposite via a combined solvothermal self-assembly, and freeze-drying process. SEM, TEM, and HRTEM characterization results shows that the Fe/GAs nanocomposite exhibits 3D macroporous structure and Fe₃O₄ NPs are evenly anchored on the graphene surface, with a size ca. 5 nm. The Fe/GAs nanocomposite material exhibits enhanced NO₂ sensing properties compared to pure rGO at RT. Because of the 3D macroporous structure and the effect of heterojunctions between the graphene and the Fe₃O₄ NPs, the resulting Fe/GAs show excellent sensing performance, including higher sensitivity, better selectivity, and faster recovery speed. These excellent properties suggest potential gas detecting applications for Fe/GAs nanocomposite at practical conditions.

Acknowledgements

This work was partially supported by Natural Science Foundation of China (No. 61403110) and the Natural Science Foundation of China (No. 11074060).

References

1. L. Renard, O. Babot, H. Saadaoui, H. Fuess, J. Brotz, A. Gurlo, E. Arveux, A. Klein and T. Toupance, Nanoscale, 2012, 4, 6806.
2. C. H. Sun, G. Maduraiveeran and P. Dutta, Sens. Actuators, B, 2013, 186, 117.
3. A. Lipatov, A. Varezhnikov, P. Wilson, V. Sysoev, A. Kolmakov and A. Sinitskii, Nanoscale, 2013, 5, 5426.
4. S. O. Hwang, C. H. Kim and Y. Myung, J. Phys. Chem. C, 2008, 112, 13911.
5. Z. H. Ai, K. J. Deng, Q. F. Wan, L. Z. Zhang and S. C. Lee, J. Phys. Chem. C, 2010, 114, 6237.
6. Z. Jing and S. Wu, Mater. Lett., 2006, 60, 952.
7. Z. Jing, Mater. Lett., 2006, 60, 3315.
8. G. Neri, A. Bonavita, C. Milone and S. Galvagno, Sens. Actuators, B, 2003, 93, 402.
9. G. Neri, A. Bonavita, S. Galvagno, N. Donato and A. Caddemi, Sens. Actuators, B, 2005, 111, 71.
10. L. M. Huang and H. Q. Fan, Sens. Actuators, B, 2012, 171, 1257.
11. Y. J. Chen, C. L. Zhu, L. J. Wang, P. Gao, M. S. Cao and X. L. Shi, Nanotechnology, 2009, 20, 045502.
12. Y. J. Chen, C. L. Zhu, X. L. Shi, M. S. Cao and H. B. Jin, Nanotechnology, 2008, 19, 205603.
13. C. L. Zhu, Y. J. Chen, R. X. Wang, L. J. Wang, M. S. Cao and X. L. Shi, Sens. Actuators, B, 2009, 140, 185–189.
14. X. An, J. C. Yu, Y. Wang, Y. Hu, X. Yu and G. Zhang, J. Mater. Chem., 2012, 22, 8525.
15. S. Srivastava, K. Jain, V. N. Singh, S. Singh, N. Vijayan, N. Dilawar, G. Gupta and T. D. Senguttuvan, Nanotechnology, 2012, 23, 205501.
16. Z. W. Zheng, C. J. Zhao, S. B. Lu, Y. Chen, Y. Li, H. Zhang and S. C. Wen, Opt. Express, 2012, 20, 23201.
17. S. Deng, V. Tjoa, H. M. Fan, H. R. Tan, D. C. Sayle, M. Olivo, S. Mhaisalkar, J. Wei and C. H. Sow, J. Am. Chem. Soc., 2012, 134, 4905–4917.
18. J. Yi, J. M. Lee and W. I. Park, Sens. Actuators, B, 2011, 155, 264–269.
19. M. Zhu, X. M. Li, S. K. Chung, L. Y. Zhao, X. Li, X. B. Zang, K. L. Wang, J. Q. Wei, M. L. Zhong, K. Zhou, D. Xie and H. W. Zhu, Carbon, 2015, 84, 138.
20. J. T. Robinson, F. K. Perkins, E. S. Snow, Z. Q. Wei and P. E. Sheehan, Nano Lett., 2008, 8, 3137.
21. Y. X. Xu, K. X. Sheng, C. Li and G. Q. Shi, ACS Nano, 2010, 4, 4324.
22. W. S. Hummers and R. E. Offeman, J. Am. Chem. Soc., 1958, 80, 1339.
23. L. H. Tang, Y. Wang, Y. M. Li, H. B. Feng, J. Lu and J. H. Li, Adv. Funct. Mater., 2009, 19, 2782.
24. J. Zhang, H. Yang, G. Shen, P. Cheng, J. Zhang and S. Guo, Chem. Commun., 2010, 46, 1112.
25. J. F. Liang, Y. K. Liu, L. Guo and L. D. Li, RSC Adv., 2013, 3, 11489.
26. F. Tuinstra and J. L. Koenig, Raman spectrum of graphite, J. Chem. Phys., 1970, 53, 1126.
27. A. C. Ferrari, J. C. Meyer, V. Scardaci, C. Casiraghi, M. Lazzeri, F. Mauri, S. Piscanec, D. Jiang, K. S. Novoselov, S. Roth and A. K. Geim, Phys. Rev. Lett., 2006, 97, 187401.
28. M. X. Chen, C. C. Zhang, X. C. Li, L. Zhang, Y. L. Ma, L. Zhang, X. Y. Xu, F. L. Xia, W. Wang and J. P. Gao, J. Mater. Chem. A, 2013, 1, 2869.
29. J. S. Zhou, H. H. Song, L. L. Ma and X. H. Chen, RSC Adv., 2011, 1, 782–791.
30. B. Luo, Y. Fang, B. Wang, J. S. Zhou, H. H. Song and L. J. Zhi, Energy Environ. Sci., 2012, 5, 5226.
31. X. Liu, J. S. Cui, J. B. Sun and X. T. Zhang, RSC Adv., 2014, 4, 22601.
32. G. Singh, A. Choudhary, D. Haranath, A. G. Joshi, N. Singh, S. Singh and R. Pasricha, Carbon, 2012, 50, 385.
33. Q. W. Huang, D. W. Zeng, H. Y. Li and C. S. Xie, Nanoscale, 2012, 4, 5651.
34. T. V. Cuong, V. H. Pham, J. S. Chung, E. W. Shin, D. H. Yoo, S. H. Hahn, J. S. Huh, G. H. Rue, E. J. Kim and S. H. Hur, Mater. Lett., 2010, 64, 2479.
35. A. Gurlo and R. Riedel, Angew. Chem., Int. Ed., 2007, 46, 3826.
36. J. W. Li, X. Liu, J. S. Cui and J. B. Sun, ACS Appl. Mater. Interfaces, 2015, 7, 10108.
37. X. Liu, J. B. Sun and X. T. Zhang, Sens. Actuators, B, 2015, 211, 220.
38. I. Sayago, H. Santos, M. C. Horrillo, M. Alexandere, M. J. Fernandez, E. Terrado, I. Tacchini, R. Aroz, W. K. Maser, A. M. Benito, M. T. Martinez, J. Gutierrez and E. Munoz, Talanta, 2008, 77, 758.

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