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Vol. 13 (2021)

Remote Tracking Gas Molecular via the Standalone-Like Nanosensor-Based Tele-Monitoring System

https://doi.org/10.1007/s40820-020-00551-w
Han Jin
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Junkan Yu
School of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, People’s Republic of China
Daxiang Cui
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Shan Gao
State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, People’s Republic of China
Hao Yang
State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, People’s Republic of China
Xiaowei Zhang
School of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, People’s Republic of China
Changzhou Hua
School of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, People’s Republic of China
Shengsheng Cui
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Cuili Xue
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Yuna Zhang
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Yuan Zhou
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Bin Liu
Institute of Micro‑Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People’s Republic of China
Wenfeng Shen
Ningbo Materials Science and Technology Institute, Chinese Academy of Sciences, Ningbo 315201, People’s Republic of China
Shengwei Deng
College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, People’s Republic of China
Wanlung Kam
Qi Diagnostics Ltd, Hongkong, People’s Republic of China
Waifung Cheung
Qi Diagnostics Ltd, Hongkong, People’s Republic of China

Corresponding Author: Han Jin

jinhan10@sjtu.edu.cn

Nano-Micro Letters, Vol. 13 (2021), Article Number: 32

Abstract

Remote tracking the variation of air quality in an effective way will be highly helpful to decrease the health risk of human short- and long-term exposures to air pollution. However, high power consumption and poor sensing performance remain the concerned issues, thereby limiting the scale-up in deploying air quality tracking networks. Herein, we report a standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way. Brevity, the created smart device demonstrated satisfactory selectivity (against six kinds of representative exhaust gases or air pollutants), desirable response magnitude (164–100 ppm), and acceptable response/recovery rate (52.0/50.5 s), as well as linear response relationship to NO2. After aging for 2 weeks, the created device exhibited relatively stable sensing performance more than 3 months. Moreover, a photoluminescence-enhanced light fidelity (Li-Fi) telecommunication technique is proposed and the Li-Fi communication distance is significantly extended. Conclusively, our reported standalone-like smart device would sever as a powerful sensing platform to construct high-performance and low-power consumption air quality wireless sensor networks and to prevent air pollutant-induced diseases via a more effective and low-cost approach.


Highlights:


1 A standalone-like smart device that can remotely track the variation of air pollutants in a power-saving way is created;
2 Metal–organic framework-derived hollow polyhedral ZnO was successfully synthesized, allowing the created smart device to be highly selective and to sensitively track the variation of NO2 concentration;
3 A novel photoluminescence-enhanced Li-Fi telecommunication technique is proposed, offering the created smart device with the capability of long distance wireless communication.

Keywords

Metal–organic framework-derived polyhedral ZnO Perovskite quantum dots Nanosensor NO2 Tele-monitoring system
Jin, Han, Junkan Yu, Daxiang Cui, Shan Gao, Hao Yang, Xiaowei Zhang, Changzhou Hua, Shengsheng Cui, Cuili Xue, Yuna Zhang, Yuan Zhou, Bin Liu, Wenfeng Shen, Shengwei Deng, Wanlung Kam, and Waifung Cheung. 2021. “Remote Tracking Gas Molecular via the Standalone-Like Nanosensor-Based Tele-Monitoring System”. Nano-Micro Letters 13 (January):32. https://doi.org/10.1007/s40820-020-00551-w.
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References
  1. P. Arroyo, J.L. Herrero, J.L. Suárez, J. Lozano, Wireless sensor network combined with cloud computing for air quality monitoring. Sensors 19, 691–707 (2019). https://doi.org/10.3390/s19030691
  2. S.B. Zhong, Z.C. Yu, W. Zhu, Study of the effects of air pollutants on human health based on daidu indices of disease symptoms and air quality monitoring data in Beijing, China. Int. J. Environ. Res. Public Health 16, 1014–1032 (2019). https://doi.org/10.3390/ijerph16061014
  3. X.W. Sun, P.L. Chen, L. Ren, Y.N. Lin, J.P. Zhou et al., The cumulative effect of air pollutants on the acute exacerbation of COPD in Shanghai. China. Sci. Total Environ. 622–623, 875–881 (2018). https://doi.org/10.1016/j.scitotenv.2017.12.042
  4. M.Z. Jiao, N.V. Duy, D.D. Trung, N.D. Hoa, N.V. Hieu et al., Comparison of NO2 gas-sensing properties of three different ZnO nanostructures synthesized by On-Chip low-temperature hydrothermal growth. J. Electron. Mater. 47, 785–793 (2018). https://doi.org/10.1007/s11664-017-5829-6
  5. M. Kampa, E. Castanas, Human health effects of air pollution. Environ. Pollut. 151, 362–367 (2008). https://doi.org/10.1016/j.envpol.2007.06.012
  6. T. Boningari, P.G. Smirniotis, Impact of nitrogen oxides on the environment and human health: Mn-based materials for the NOx abatement. Curr. Opin. Chem. Eng. 13, 133–141 (2016). https://doi.org/10.1016/j.coche.2016.09.004
  7. J. Huang, X.C. Pan, X.B. Guo, G.X. Li, Health impact of China’s air pollution prevention and control action plan: an analysis of national air quality monitoring and mortality data. Lancet Planet Health 2, e313–e323 (2018). https://doi.org/10.1016/S2542-5196(18)30141-4
  8. H.D. Kan, R.J. Chen, S.L. Tong, Ambient air pollution, climate change, and population health in China. Environ. Int. 42, 10–19 (2012). https://doi.org/10.1016/j.envint.2011.03.003
  9. C.B. Song, L. Wu, Y.C. Xie, J.J. He, X. Chen et al., Air pollution in China: status and spatiotemporal variations. Environ. Pollut. 227, 334–347 (2017). https://doi.org/10.1016/j.envpol.2017.04.075
  10. S. Moltchanov, I. Levy, Y. Etzion, U. Lerner, D.M. Broday et al., On the feasibility of measuring urban air pollution by wireless distributed sensor networks. Sci. Total Environ. 502, 537–547 (2015). https://doi.org/10.1016/j.scitotenv.2014.09.059
  11. L. Sun, K.C. Wong, P. Wei, S. Ye, H. Huang et al., Development and application of a next generation air sensor network for the Hong Kong Marathon 2015 air quality monitoring. Sensors 16, 211–228 (2016). https://doi.org/10.3390/s16020211
  12. I. Gryech, Y.B. Aboud, B. Guermah, N. Sbihi, M. Ghogho et al., MoreAir: a low-cost urban air pollution monitoring system. Sensors 20, 998 (2020). https://doi.org/10.3390/s20040998
  13. P. D’Urso, D.D. Lallo, E.A. Maharaj, Autoregressive model-based fuzzy clustering and its application for detecting information redundancy in air pollution monitoring networks. Soft. Comput. 17, 83–131 (2013). https://doi.org/10.1007/s00500-012-0905-6
  14. H. Jing, Routing optimization algorithm based on nodes density and energy consumption of wireless sensor network. J. Comput. Inf. Syst. 14, 5047–5054 (2015). https://doi.org/10.12733/jcis14550
  15. A. Chandrasekhar, G. Khandelwal, N.R. Alluri, V. Vivekananthan, S.J. Kim, Battery-free electronic smart toys: a step toward the commercialization of sustainable triboelectric nanogenerators. ACS Sustain. Chem. Eng. 6, 6110–6116 (2018). https://doi.org/10.1021/acssuschemeng.7b04769
  16. A. Chandrasekhar, V. Vivekananthan, G. Khandelwal, S.J. Kim, Sustainable human-machine interactive triboelectric nanogenerator toward a smart computer mouse. ACS Sustain. Chem. Eng. 7, 7177–7182 (2019). https://doi.org/10.1021/acssuschemeng.9b00175
  17. A. Chandrasekhar, V. Vivekananthan, G. Khandelwal, S.J. Kim, A fully packed water-proof, humidity resistant triboelectric nanogenerator for transmitting Morse code. Nano Energy 60, 850–856 (2019). https://doi.org/10.1016/j.nanoen.2019.04.004
  18. A. Chandrasekhar, V. Vivekananthan, S.J. Kim, A fully packed spheroidal hybrid generator for water wave energy harvesting and self-powered position tracking. Nano Energy 69, 104439–104445 (2020). https://doi.org/10.1016/j.nanoen.2019.104439
  19. V. Vivekananthan, A. Chandrasekhar, N.R. Alluri, Y. Purusothaman, S.J. Kim, A highly reliable, impervious and sustainable triboelectric nanogenerator as a zero-power consuming active pressure sensor. Nanoscale Adv. 2, 746–754 (2020). https://doi.org/10.1039/C9NA00790C
  20. V. Vivekananthan, A. Chandrasekhar, N.R. Alluria, Y. Purusothamana, G. Khandelwala et al., Fe2O3 magnetic particles derived triboelectric-electromagnetic hybrid generator for zero-power consuming seismic detection. Nano Energy 64, 103926–103934 (2019). https://doi.org/10.1016/j.nanoen.2019.103926
  21. Y.Y. Jian, W.W. Hu, Z.H. Zhao, P.F. Cheng, H. Haick et al., Gas sensors based on chemi-resistive hybrid functional nanomaterials. Nano-Micro Lett. 12, 71–114 (2020). https://doi.org/10.1007/s40820-020-0407-5
  22. I.H. Kadhim, H.A. Hassan, Q.N. Abdullah, Hydrogen gas sensor based on nanocrystalline SnO2 thin film grown on bare Si substrates. Nano-Micro Lett. 8, 20–28 (2016). https://doi.org/10.1007/s40820-015-0057-1
  23. J.Y. Liu, Z.X. Hu, Y.Z. Zhang, H.Y. Li, N.B. Gao et al., MoS2 nanosheets sensitized with qantum dots for room-temperature gas sensors. Nano-Micro Lett. 12, 59–72 (2020). https://doi.org/10.1007/s40820-020-0394-6
  24. T. Wang, D. Huang, Z. Yang, S.S. Xu, G.L. He et al., A review on graphene-based gas/vapor sensors with unique properties and potential applications. Nano-Micro Lett. 8, 95–119 (2016). https://doi.org/10.1007/s40820-015-0073-1
  25. K. Harshitha, A. Chaithra, N.A. Poojitha, B.R. Rao, Li-Fi (Light Fidelity)-the future technology in wireless communication. Int. J. Softw. Eng. Soft Comput. 6, 49–51 (2016). https://doi.org/10.9756/BIJSESC.8241
  26. Y.T. Xu, J. Guo, X.Y. Li, M.M. Dong, Z.G. Lu et al., Multilevel image thresholding technology based on swarm intelligent algorithm. Mach. Electron. 38, 7–13 (2020)
  27. B. Shouli, C. Liangyuan, H. Jingwei, L. Dianqing, L.R. Xian et al., Synthesis of quantum size ZnO crystals and their gas sensing properties for NO2. Sens. Actuat. B Chem. 159, 97–102 (2011). https://doi.org/10.1016/j.snb.2011.06.056
  28. B. Shouli, L. Xin, L. Dianqing, C. Song, L.R. Xian et al., Synthesis of ZnO nanorods and its application in NO2 sensors. Sens. Actuator B Chem. 153, 110–116 (2011). https://doi.org/10.1016/j.snb.2010.10.010
  29. F.Y. Fan, Y.J. Feng, S.L. Bai, J.T. Feng, A.F. Chen et al., Synthesis and gas sensing properties to NO2 of ZnO nanoparticles. Sens. Actuator B Chem. 185, 377–382 (2013). https://doi.org/10.1016/j.snb.2013.05.020
  30. J. Gonzalez-Chavarri, L. Parellada-Monreal, I. Castro-Hurtado, E. Castano, G.G. Mandayo, ZnO nanoneedles grown on chip for selective NO2 detection indoors. Sens. Actuator B Chem. 255, 1244–1253 (2018). https://doi.org/10.1016/j.snb.2017.08.094
  31. J.H. Jun, J. Yun, K. Cho, I.S. Hwang, J.H. Lee et al., Necked ZnO nanoparticle-based NO2 sensors with high and fast response. Sens. Actuator B Chem. 140, 412–417 (2009). https://doi.org/10.1016/j.snb.2009.05.019
  32. M. Chen, Z.H. Wang, D.M. Han, F.B. Gu, G.S. Guo, High-sensitivity NO2 gas sensors based on flower-like and tube-like ZnO nanomaterials. Sens. Actuator B Chem. 157, 565–574 (2011). https://doi.org/10.1016/j.snb.2011.05.023
  33. R.S. Chen, J. Wang, L. Xiang, Facile synthesis of mesoporous ZnO sheets assembled by small nanoparticles for enhanced NO2 sensing performance at room temperature. Sens. Actuator B Chem. 270, 207–215 (2018). https://doi.org/10.1016/j.snb.2018.05.005
  34. S.A. Vanalakar, V.L. Patil, N.S. Harale, S.A. Vhanalakar, M.G. Gang et al., Controlled growth of ZnO nanorod arrays via wet chemical route for NO2 gas sensor applications. Sens. Actuator B Chem. 221, 1195–1201 (2015). https://doi.org/10.1016/j.snb.2015.07.084
  35. S.L. Bai, L.Y. Chen, S. Chen, R.X. Luo, D.Q. Li et al., Reverse microemulsion in situ crystallizing growth of ZnO nanorods and application for NO2 sensor. Sens. Actuator B Chem. 190, 760–767 (2014). https://doi.org/10.1016/j.snb.2013.09.032
  36. V.L. Patil, S.A. Vanalakar, P.S. Patil, J.H. Kim, Fabrication of nanostructured ZnO thin films based NO2 gas sensor via SILAR technique. Sens. Actuator B Chem. 239, 1185–1193 (2017). https://doi.org/10.1016/j.snb.2016.08.130
  37. Y.H. Navale, S.T. Navale, N.S. Ramgir, F.J. Stadler, S.K. Gupta et al., Zinc oxide hierarchical nanostructures as potential NO2 sensors. Sens. Actuator B Chem. 251, 551–563 (2017). https://doi.org/10.1016/j.snb.2017.05.085
  38. R. Kumar, O.A. Dossary, G. Kumar, A. Umar, Zinc oxide nanostructures for NO2 gas–sensor applications: a review. Nano-Micro Lett. 7, 97–120 (2015). https://doi.org/10.1007/s40820-014-0023-3
  39. K.E. DeKrafft, C. Wang, W. Lin, Metal-organic framework templated synthesis of Fe2O3/TiO2 nanocomposite for hydrogen production. Adv. Mater. 24, 2014–2018 (2012). https://doi.org/10.1002/adma.201200330
  40. W.H. Li, X.F. Wu, N. Han, J.Y. Chen, X.H. Qian et al., MOF-derived hierarchical hollow ZnO nanocages with enhanced low-concentration VOCs gas-sensing performance. Sens. Actuator B Chem. 225, 158–166 (2016). https://doi.org/10.1016/j.snb.2015.11.034
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