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It is of great significance to study the characteristics and working mechanism of NO2 sensor material for monitoring air pollution and protecting human health. As a metal oxide semiconductor material with simple preparation, low cost and good long-term stability, In2O3 has been widely studied in the detection of NO2. In order to explore the influence of Fe content on the gas sensing properties of porous In2O3 material, porous Fe-doped In2O3 nanoparticles are synthesized by the hydrothermal method, and the NO2 sensor is fabricated by using the above nanoparticles. The X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy and specific surface area measurement are used to characterize the micro morphology of the prepared nanoparticles in this paper, while the sensor performance is studied, including temperature, response recovery, selectivity and stability. In most samples, Fe atoms are completely doped into the In2O3 lattice as indicated by the XRD results. The SEM results show that the Fe-doped In2O3 nanoparticles prepared with Span-40 as activators are square in size of 50–200 nm, and a large number of small pores are distributed in it, which are also observed in the N2 adsorption/desorption experiment, this is one of the main reasons for the large specific surface area and high sensitivity of the nano materials. Studying the performance of the sensor, we find that when the molar ratio of In∶Fe is 9∶1, the sensor made of porous Fe-doped In2O3 nanoparticles has an excellent selectivity and short response recovery time for NO2 gas. The sensitivity of the sensor to 50-ppm-concentration (1 ppm = 1 mg/L) NO2 can reach 960.5 at 260 ℃, and the response time and recovery time are 5 s and 6 s respectively. Based on the theory of space charge and the knowledge of built-in barrier and energy band change before and after doping, the mechanism of the sensor is analyzed.
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Keywords:
- Fe-doped In2O3 /
- porous /
- NO2 /
- sensor
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Google Scholar
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图 1 传感器灵敏度测量示意图 (a) 传感器结构图; (b) 传感测试系统
Figure 1. Diagram used to measure the sensitivity of sensor: (a) Structure of sensor; (b) sensor test system.
图 2 Fe掺杂In2O3的XRD图谱
Figure 2. XRD patterns of Fe-doped In2O3.
图 3 SEM图像 (a) 样品1; (b) 样品2; (c) 样品3; (d) 样品4; (e) 样品5; (f) 样品6
Figure 3. SEM images: (a) S1; (b) S2; (c) S3; (d) S4; (e) S5; (f) S6.
图 4 (a) 样品4的TEM图像; (b) 样品4的EDS光谱和SAED图案
Figure 4. (a) TEM image of S4; (b) EDS spectroscopy and SAED pattern taken from S4.
图 5 (a) 样品1的N2吸附/脱附曲线; (b) 样品1的孔径分布; (c) 样品4的N2吸附/脱附曲线; (d) 样品4的孔径分布
Figure 5. N2 adsorption/desorption curves of (a) S1 and (c) S4; the pore size distribution of (b) S1 and (d) S4.
图 6 掺杂In2O3结构形成机理图
Figure 6. Schematic illustrating the formation mechanism of the doped In2O3 structures.
图 7 (a) 6种传感器在温度为260 ℃时放置在浓度为5−100 ppm的NO2下的气体响应; (b) 样品1−样品6的比表面积
Figure 7. (a) Gas response of the 6 sensors exposed to NO2 at concentrations ranging from 5 ppm to 100 ppm at 260 °C; (b) surface area of S1−S6.
图 8 样品4气体响应随温度的变化 (a) 不同工作温度下的典型响应和恢复曲线; (b) 不同温度下对50 ppm NO2的气体响应
Figure 8. Gas response of S4 as a function of temperature: (a) Typical response and recovery curves at different working temperatures; (b) gas response to 50 ppm NO2 at different working temperatures.
图 9 基于样品4制作的传感器在260 ℃时对NO2气体的响应-恢复曲线 (a)气体浓度范围为5−100 ppm; (b) 气体浓度为50 ppm
Figure 9. Gas response-recovery of the sensor based on S4 exposed to NO2 at 260 °C: (a) Gas concentrations ranging from 5 ppm to 100 ppm; (b) gas concentration is 50 ppm.
图 10 在260 ℃时样品4对浓度为50 ppm不同试验气体的灵敏度
Figure 10. Selectivity of S4 to different test gases with a concentration of 50 ppm at 260 °C.
图 11 在260 ℃时Fe掺杂In2O3传感器(S4)对浓度为50 ppm的NO2的稳定性测试(插图为S4在(a)第1天和(b) 第90天的气体响应)
Figure 11. Stability of the Fe-doped In2O3 structures (S4) sensor to NO2 with a concentration of 50 ppm at 260 °C (inset: gas response of S4 for (a) the first day and (b) the 90th day).
图 12 (a) 反应示意图; (b) 传感机理图; (c) 能带图
Figure 12. (a) Schematic diagram; (b) gas sensing mechanism; (c) the band diagram.
表 1 样品原材料组成表
Table 1. Composition of sample raw materials.
样品编号 组成及用量/g In/Fe摩尔比 In(NO3)3·4.5H2O Fe(NO3)3·9H2O Span-40 样品1 (S1) 0.5729 0 0.6030 — 样品2 (S2) 0.5729 0.1212 0.6030 5∶1 样品3 (S3) 0.5729 0.0866 0.6030 7∶1 样品4 (S4) 0.5729 0.0673 0.6030 9∶1 样品5 (S5) 0.5729 0.0505 0.6030 12∶1 样品6 (S6) 0.5729 0.0404 0.6030 15∶1 
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[1] Xu X M, Zhang H J, Diao Q, Zhu Y S, Yang G 2019 Mater. Res. Express 6 17
Google Scholar
[2] Bo Z, Guo X Z, Wei X, Yang H C, Yan J H, Cen K F 2019 Physica E 109 156
Google Scholar
[3] Borgohain R, Das R, Mondal B, Yordsri V, Thanachayanont C, Baruah S 2018 IEEE Sens. J. 18 7203
Google Scholar
[4] 赵博硕, 强晓永, 秦岳, 胡明 2018 67 058101
Google Scholar
Zhao B S, Qiang X Y, Qin Y, Hu M 2018 Acta Phys. Sin. 67 058101
Google Scholar
[5] Zhou P F, Shen Y B, Lu W, Zhao S K, Li T T, Zhong X X, Cui B Y, Wei D Z, Zhang Y H 2020 J. Alloys Compd. 828 154395
Google Scholar
[6] Hung N M, Hieu N M, Chinh N D, Hien T T, Quang N D, Majumder S, Choi G, Kim C, Kim D 2020 Sens. Actuators, B 313 128001
Google Scholar
[7] Chen K X, Lu H, Li G, Zhang J N, Tian Y H, Gao Y, Guo Q M, Lu H B, Gao J Z 2020 Sens. Actuator, B 308 127716
Google Scholar
[8] Nam B, Ko T K, Hyun S K, Lee C 2019 Nano Converg. 6 40
Google Scholar
[9] Shen Y B, Zhong X X, Zhang J, Li T T, Zhao S K, Cui B Y, Wei D Z, Zhang Y H, Wei K F 2019 Appl. Surf. Sci. 498 143873
Google Scholar
[10] Pawar K K, Shaikh J S, Mali S S, Navale Y H, Patil V B, Hong C K, Patil P S 2019 J. Alloys Compd. 806 726
Google Scholar
[11] Yang W, Chen H T, Li C L, Meng H 2020 Mater. Lett. 271 127782
Google Scholar
[12] Park B G, Reddeppa M, Kim Y H, Kim S G, Kim M D 2020 Nanotechnology 31 335503
Google Scholar
[13] Zhao S K, Shen Y B, Zhou P F, Hao F L, Xu X Y, Gao S L, Wei D Z, Ao Y X, Shen Y S 2020 Sens. Actuator, B 308 127729
Google Scholar
[14] Bi H S, Shen Y B, Zhao S K, Zhou P F, Gao S L, Cui B Y, Wei D Z, Zhang Y H, Wei K F 2020 Vacuum 172 109086
Google Scholar
[15] Cheng M, Wu Z P, Liu G N, Zhao L J, Gao Y, Li S, Zhang B, Yan X, Lu G Y 2020 Sens. Actuator, B 304 127272
Google Scholar
[16] Ri J S, Li X W, Shao C L, Liu Y, Han C H, Li X H, Liu Y C 2020 Sens. Actuator, B 317 128194
Google Scholar
[17] Sabry R S, Agool I R, Abbas A M 2019 Silicon 11 2475
Google Scholar
[18] Lee O H, Tseng W J 2019 J. Mater. Sci.-Mater. Electron. 30 15145
Google Scholar
[19] Inyawilert K, Channei D, Tamaekong N, Liewhiran C, Wisitsoraat A, Tuantranont A, Phanichphant S 2016 J. Nanopart. Res. 18 40
Google Scholar
[20] Yoo Y K, Xue Q Z, Lee H C, Cheng S F, Xiang X D, Dionne G F, Xu S F, He J, Chu Y S, Preite S D, Lofland S E, Takeuchi I 2005 Appl. Phys. Lett. 86 042506
Google Scholar
[21] Sreethawong T, Chavadej S, Ngamsinlapasathian S, Yoshikawa S 2008 Microporous Mesoporous Mater. 109 84
Google Scholar
[22] Cao M H, Wang Y D, Chen T, Antonietti M, Niederberger M 2008 Chem. Mater. 20 5781
Google Scholar
[23] Jia X, Fan H 2010 Mater. Res. Bull. 45 1496
Google Scholar
[24] Wetchakun K, Samerjai T, Tamaekong N, Liewhiran C, Siriwong V, Kruefu V, Wisitsoraat A, Tuantranont A, Phanichphant S 2011 Sens. Actuator, B 160 580
Google Scholar
[25] Bai S L, Zhang K W, Luo R X, Li D Q, Chen A F, Liu C C 2012 J. Mater. Chem. 22 12643
Google Scholar
[26] Xiao B X, Zhao Q, Wang D X, Ma G S, Zhang M Z 2017 New J. Chem. 41 8530
Google Scholar
[27] Zhao J, Yang T L, Liu Y P, Wang Z Y, Li X W, Sun Y F, Du Y, Li Y C, Lu G Y 2014 Sens. Actuator, B 191 806
Google Scholar
[28] Han D M, Zhai L L, Gu F B, Wang Z H 2018 Sens. Actuator, B 262 655
Google Scholar
[29] Hu J, Liang Y F, Sun Y J, Zhao Z T, Zhang M, Li P W, Zhang W D, Chen Y, Zhuiykov S 2017 Sens. Actuator, B 252 116
Google Scholar
[30] Fahed C, Qadri S B, Kim H, Piqué A, Miller M, Mahadik N A, Rao M V, Osofsky M 2010 Phys. Status Solidi C 7 2298
Google Scholar
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