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Feb 13, 2025; e2419159.

Bionic Olfactory Neuron with In-Sensor Reservoir Computing for Intelligent Gas Recognition.

Xiaosong Wu, Shuhui Shi, Jingyan Jiang, Dedong Lin, Jian Song, Zhongrui Wang, Weiguo Huang
Author Information
  1. Xiaosong Wu: State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China.
  2. Shuhui Shi: Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong SAR, P. R. China.
  3. Jingyan Jiang: College of Big Data and Internet, Shenzhen Technology University, Shenzhen, 518118, P. R. China.
  4. Dedong Lin: College of Big Data and Internet, Shenzhen Technology University, Shenzhen, 518118, P. R. China.
  5. Jian Song: School of Microelectronics, Shanghai University, Shanghai, 201800, P. R. China.
  6. Zhongrui Wang: Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong SAR, P. R. China.
  7. Weiguo Huang: State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China. ORCID
PMID: 39945055 DOI: 10.1002/adma.202419159

Abstract

Gas sensing and recognition are closely related to the sustainable development of human society, current electronic noses (e-noses) typically focus on detecting specific gases, with only a few capable of recognizing complex odor mixtures. Further, these sensors often struggle to distinguish between isomers and homologs, as these compounds usually have similar physical and chemical properties, yielding nearly identical sensor responses. Even the mammalian olfactory systems consisting of a large variety of receptor cells and efficient neuron networks sometimes fail in this task. The bottleneck stems from the inability to extract the fingerprints of these compounds and the inefficiency of signal processing. To address these limitations, a material-device-algorithm co-design strategy is proposed that integrates an organic field-effect transistor (OFET) array with in-sensor reservoir computing (RC) and the k-nearest neighbors (KNN) algorithm. Organic semiconductors diversify responses to different gases, while RC efficiently extracts spatiotemporal features with lower training costs and reduced energy overhead. This synergy achieves 100% classification accuracy for eight gases and 99.04% accuracy for a library of 26 gases, including mixtures, isomers, and homologs-among the highest reported accuracies. This work provides a groundbreaking hardware solution for bionic olfactory neurons with edge artificial intelligence (AI) functions, surpassing traditional e-noses.

Keywords

bionic olfactory neuron intelligent gas recognition in���sensor reservoir computing isomers and homologs discrimination pollutant analysis in underground water

References

  1. K. Kalantar���Zadeh, K. Berean, N. Ha, A. Chrimes, K. Xu, D. Grando, J. Ou, N. Pillai, J. Campbell, R. Brklja��a, K. Taylor, R. Burgell, C. Yao, S. Ward, C. McSweeney, J. Muir, P. Gibson, Nat. Electron. 2018, 1, 79.
  2. M. Adeel, Y. Cotur, A. Naik, L. Gonzalez���Macia, F. G��der, Nat. Electron. 2022, 5, 719.
  3. J. Rosen, Science 2006, 354, 952.
  4. W. Xu, G. Wang, S. Liu, J. Wang, W. McDowell, K. Huang, P. Raymond, Z. Yang, X. Xia, Nat. Sustain. 2024, 7, 938.
  5. T. Wang, Z. Jiang, B. Zhao, Y. Gu, K. Liou, N. Kalandiyur, D. Zhang, Y. Zhu, Nat. Sustain. 2020, 3, 597.
  6. A. Modi, N. Koratkar, E. Lass, B. Wei, P. Ajayan, Nature 2003, 424, 171.
  7. B. Wang, T. P. Huynh, W. Wu, N. Hayek, T. Do, J. Cancilla, J. Torrecilla, M. Nahid, J. Colwell, O. Gazit, S. Puniredd, C. McNeill, P. Sonar, H. Haick, Adv. Mater. 2016, 28, 4012.
  8. K. Mori, H. Nagao, Y. Yoshihara, Science 1999, 286, 711.
  9. L. Saraiva, Sci. Adv. 2019, 5, eaax0396.
  10. L. Buck, Angew. Chem., Int. Ed. 2005, 44, 6128.
  11. S. Chun, Y. Song, J. Kim, J. Kwon, K. Soh, J. Kwon, C. Kang, J. Yoon, Adv. Mater. 2023, 35, 2302219.
  12. K. Persaud, G. Dodd, Nature 1982, 299, 352.
  13. X. Wu, S. Mao, J. Chen, J. Huang, Adv. Mater. 2018, 30, 1705642.
  14. J. Huang, G. Zhang, X. Zhao, X. Wu, D. Liu, Y. Chu, H. Katz, J. Am. Chem. Soc. 2017, 139, 12366.
  15. W. Huang, K. Besar, R. LeCover, A. Rule, P. Breysse, H. Katz, J. Am. Chem. Soc. 2012, 134, 14650.
  16. M. Lee, H. Kim, G. Jung, A. Han, S. Kwak, B. Kim, J. Oh, Adv. Mater. 2015, 27, 1540.
  17. R. Potyrailo, S. Go, D. Sexton, X. Li, N. Alkadi, A. Kolmakov, B. Amm, R. St���Pierre, B. Scherer, M. Nayeri, G. Wu, C. Collazo���Davila, D. Forman, C. Calvert, C. Mack, P. McConnell, Nat. Electron. 2020, 3, 280.
  18. C. Hagleitner, A. Hierlemann, D. Lange, A. Kummer, N. Kerness, O. Brand, H. Baltes, Nature 2001, 414, 293.
  19. S. Wang, X. Chen, C. Zhao, Y. Kong, B. Lin, Y. Wu, Z. Bi, Z. Xuan, T. Li, Y. Li, W. Zhang, E. Ma, Z. Wang, W. Ma, Nat. Electron. 2023, 6, 281.
  20. J. Chen, Z. Zhou, B. J. Kim, Y. Zhou, Z. Wang, T. Wan, J. Yan, J. Kang, J. Ahn, Y. Chai, Nat. Nanotechnol. 2023, 18, 882.
  21. X. Wu, S. Wang, W. Huang, Y. Dong, Z. Wang, W. Huang, Nat. Commun. 2023, 14, 468.
  22. M. M. Shulaker, G. Hills, R. S. Park, R. T. Howe, K. Saraswat, H. P. Wong, S. Mitra, Nature 2017, 547, 74.
  23. K. J. Albert, Chem. Rev. 2000, 100, 2595.
  24. Z. Wang, X. Jiang, K. Huang, L. Ning, J. Zhang, F. Zhang, J. Yang, Y. Wu, X. Chen, Y. Yi, X. Shi, Y. Chen, S. Wang, Adv. Mater. 2021, 33, 2106067.
  25. H. Zhang, Z. Zhang, Z. Li, H. Han, W. Song, J. Yi, Nat. Commun. 2023, 14, 3495.
  26. K. Lee, I. Cho, M. Kang, J. Jeong, M. Choi, K. Woo, K. Yoon, Y. Cho, I. Park, ACS Nano 2023, 17, 539.
  27. W. Huang, R. Hayward, ACS Appl. Mater. Interfaces 2018, 10, 33353.
  28. Y. Tong, Y. Liu, Y. Zhao, J. Thong, D. Chan, C. Zhu, Sens. Actuators, A 2017, 255, 28.
  29. A. Abbas, B. Liu, L. Chen, Y. Ma, S. Cong, N. Aroonyadet, M. Kopf, T. Nilges, C. Zhou, ACS Nano 2015, 9, 5618.
  30. H. Xie, Y. Li, Y. Lei, Y. Liu, M. Xiao, C. Gao, D. Pang, W. Huang, Z. Zhang, G. Zhang, Anal. Chem. 2016, 88, 11115.
  31. W. Yan, C. Lv, D. Zhang, Y. Chen, L. Zhang, C. Coileain, Z. Wang, Z. Jiang, K. Hung, C. Chang, H. Wu, ACS Appl. Mater. Interfaces 2020, 12, 26746.
  32. L. Sacco, S. Forel, I. Florea, C. Cojocaru, Carbon 2020, 157, 631.
  33. H. Tabata, Y. Sato, K. Oi, O. Kubo, M. Katayama, ACS Appl. Mater. Interfaces 2018, 10, 38387.
  34. S. Hong, Y. Hong, Y. Jeong, G. Jung, W. Shin, J. Park, J. Lee, D. Jang, J. Bae, J. Lee, Sens. Actuat. B: Chem. 2019, 300, 127040.
  35. M. Bastuck, D. Puglisi, J. Huotari, T. Sauerwald, J. Lappalainen, A. Lloyd Spetz, M. Andersson, A. Sch��tze, Thin Solid Films 2016, 618, 263.
  36. P. Lin, F. Yan, Adv. Mater. 2012, 24, 34.
  37. W. Huang, J. Sinha, M. Yeh, J. Hardigree, R. LeCover, K. Besar, A. Rule, P. Breysse, H. Katz, Adv. Funct. Mater. 2013, 23, 4094.
  38. L. Zhang, C. Li, A. Liu, G. Shi, J. Mater. Chem. 2012, 22, 8438.
  39. Y. Kang, D. Kwak, J. Kwon, B. Kim, W. Lee, ACS Appl. Mater. Interfaces 2021, 13, 31910.
  40. Z. Bian, C. Vong, P. Wong, S. Wang, IEEE Trans. Cybern. 2022, 52, 5380.
  41. Y. Wang, Z. Pan, Y. Pan, IEEE T. Neur. Net. Lear. 2020, 31, 1544.
  42. S. Zhang, X. Li, M. Zong, X. Zhu, R. Wang, IEEE T. Neur. Net. Lear. 2018, 29, 1774.
  43. B. Wang, J. Zhang, T. Wang, W. Li, Q. Lu, H. Sun, L. Huang, X. Liang, F. Liu, F. Liu, P. Sun, G. Lu, ACS Appl. Mater. Interfaces 2023, 15, 6047.
  44. V. Schroeder, E. Evans, Y. Wu, C. Voll, B. McDonald, S. Savagatrup, T. Swager, ACS Sens. 2019, 4, 2101.
  45. I. Cho, K. Lee, Y. Sim, J. Jeong, M. Cho, H. Jung, M. Kang, Y. Cho, S. Ha, K. Yoon, I. Park, Light Sci. Appl. 2023, 12, 95.
  46. Q. Zou, B. Liu, Y. Zhang, J. Mater. Chem. A 2023, 11, 15811.
  47. D. Henriquez, M. Kang, I. Cho, J. Choi, J. Park, O. Gul, J. Ahn, D. Lee, I. Park, Small Methods 2023, 7, 2201352.
  48. P. Peng, X. Zhao, X. Pan, W. Ye, Sensors (Basel) 2018, 18, 157.
  49. S. Panchal, A. Phadke, U. Gopinathan, S. Datar, IEEE Sens. J. 2021, 21, 20870.
  50. T. Wang, H. Huang, X. Wang, X. Guo, InfoMat 2021, 3, 804.
  51. M. Tonezzer, Sensor. Actuat. B: Chem. 2019, 288, 53.
  52. S. Kanaparthi, S. Singh, Actuat. B: Chem. 2021, 348, 130725.
  53. J. K. Han, M. Kang, J. Jeong, I. Cho, J. Yu, K. Yoon, I. Park, Y. Choi, Adv. Sci. 2022, 9, 2106017.
  54. S. Acharyya, B. Jana, S. Nag, G. Saha, P. Guha, Sensor. Actuat. B: Chem. 2020, 321, 128484.
  55. N. Thai, M. Tonezzer, L. Masera, H. Nguyen, N. Duy, N. Hoa, Anal. Chim. Acta. 2020, 1124, 85.
  56. M. Khan, B. Thomson, R. Debnath, A. Motayed, M. Rao, IEEE Sens. J. 2020, 20, 6020.
  57. T. Wang, H. Ma, W. Jiang, H. Zhang, M. Zeng, J. Yang, X. Wang, K. Liu, R. Huang, Z. Yang, Phys. Chem. Chem. Phys. 2021, 23, 23933.
  58. M. Kang, I. Cho, J. Park, J. Jeong, K. Lee, B. Lee, D. Henriquez, K. Yoon, I. Park, ACS Sens. 2022, 7, 430.
  59. T. Julian, S. Hidayat, A. Rianjanu, A. Dharmawan, H. Wasisto, K. Triyana, ACS Omega 2020, 5, 29492.
  60. A. Shahid, J. Choi, A. Rana, H. Kim, Sensors (Basel) 2018, 18, 1446.
  61. M. Campbell, S. Liu, T. Swager, M. Dinca, J. Am. Chem. Soc. 2015, 137, 13780.
  62. D. Ma, J. Gao, Z. Zhang, H. Zhao, Sensor. Actuat. B: Chem. 2021, 330, 129349.
  63. C. Wang, Z. Chen, C. Chan, Z. Wan, W. Ye, W. Tang, Z. Ma, B. Ren, D. Zhang, Z. Song, Y. Ding, Z. Long, S. Poddar, W. Zhang, Z. Wan, F. Xue, S. Ma, Q. Zhou, G. Lu, K. Liu, Z. Fan, Nat. Electron. 2024, 7, 157.
  64. J. Shi, X. Chen, B. Ye, Z. Wang, Y. Sun, J. Wu, H. Guo, Water Res. 2023, 245, 120649.
  65. D. W. Skaf, J. Chem. Eng. Process Technol. 2015, 6, 1000235.
  66. F. Ma, Y. Wan, G. Yuan, L. Meng, Z. Dong, J. Hu, Environ. Sci. Technol. 2012, 46, 3236.

Grants

  1. 2021J06034/Natural Science Foundation of Fujian Province
  2. 2023I0030/Fujian Provincial Department of Science and Technology
  3. 2024M763266/China Postdoctoral Science Foundation
  4. /Foundation for the Excellent Postdoctoral of Fujian Province
  5. CXZX-2022-GH09/Self-deployment Project Research Program of Haixi Institutes, Chinese Academy of Science
  6. CXZX-2023-GS03/Self-deployment Project Research Program of Haixi Institutes, Chinese Academy of Science
  7. 27206321/HK RGC
  8. 17205922/HK RGC
  9. 17212923/HK RGC
  10. SQ2022YFB3600159/National Key R&D Program of China
  11. E055AJ01/Chinese Academy of Sciences
  12. E355AJ01/Chinese Academy of Sciences
  13. 2021ZR115/Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China
  14. 52473201/National Natural Science Foundation of China
  15. 52303355/National Natural Science Foundation of China
  16. 22275193/National Natural Science Foundation of China
  17. 22275189/National Natural Science Foundation of China
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