journal article·2023-02Open access

Chemiresistive Sensor Arrays for Gas/Volatile Organic Compounds Monitoring: A Review

Ronil J. Rath, Syamak Farajikhah, Farshad Oveissi, Fariba Dehghani, Sina Naficy

Advanced Engineering Materials· Volume 25· Issue 3

Abstract

Gas detection and monitoring are essential due to their direct impact on human health, environment, and ecosystem. Chemiresistive sensors are one of the most used classes of sensors for monitoring and measurement of gases thanks to their ease of fabrication, customizability, mechanical flexibility, and fast response time. While chemiresistive sensors can offer good sensitivity and selectivity to a particular gas in a controlled environment with known interferences, they may not be able to differentiate between various gases having similar physiochemical properties under uncontrolled conditions. To address this shortcoming of chemiresistive gas sensors, sensor arrays have been the subject of recent studies. Gas sensor arrays are a group of individual gas sensors that are arranged to simultaneously detect and differentiate multiple cross‐reactive gases. In this regard, various sensor array technologies have been developed to differentiate a given set of gases using multivariate algorithms. This review provides an insight into the different algorithms that are used to extract the data from the sensor arrays, highlighting the fabrication techniques used for developing the sensor array prototypes, and different applications in which these arrays are used.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Chemical Sensor Technologies · Gas Sensing Nanomaterials and Sensors · Analytical Chemistry and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Chemical and Biomolecular Engineering The University of Sydney Sydney NSW 2006 Australia

Sydney Nano Institute The University of Sydney Camperdown NSW 2050 Australia

Funding

Australian Research Council

References (100+)

Show source-provided references
1. 10.1016/j.bandc.2008.04.00810.1016/j.bandc.2008.04.008 ↗
2. 10.1016/j.chest.2018.10.04110.1016/j.chest.2018.10.041 ↗
3. 10.4324/978042947073810.4324/9780429470738 ↗
4. 10.3389/fpubh.2020.0001410.3389/fpubh.2020.00014 ↗
5. 10.1021/acssensors.7b0006410.1021/acssensors.7b00064 ↗
6. 10.1039/C5SC02632F10.1039/C5SC02632F ↗
7. 10.1021/acs.nanolett.6b0515310.1021/acs.nanolett.6b05153 ↗
8. 10.1016/j.nanoen.2020.10536910.1016/j.nanoen.2020.105369 ↗
9. 10.1149/1945-7111/abf4ea10.1149/1945-7111/abf4ea ↗
10. 10.1021/acssensors.2c0108610.1021/acssensors.2c01086 ↗
11. 10.1002/adma.20180673910.1002/adma.201806739 ↗
12. 10.1016/j.sna.2018.10.03610.1016/j.sna.2018.10.036 ↗
13. 10.1021/acsapm.9b0070710.1021/acsapm.9b00707 ↗
14. 10.1021/acssensors.9b0055510.1021/acssensors.9b00555 ↗
15. 10.1080/10408398.2020.181163510.1080/10408398.2020.1811635 ↗
16. 10.1016/j.snb.2019.12689010.1016/j.snb.2019.126890 ↗
17. 10.1016/j.snb.2018.07.17810.1016/j.snb.2018.07.178 ↗
18. 10.1021/cr980102w10.1021/cr980102w ↗
19. 10.1021/ac60191a00110.1021/ac60191a001 ↗
20. 10.1021/ac60240a03110.1021/ac60240a031 ↗
21. 10.1063/1.175512310.1063/1.1755123 ↗
22. 10.1021/ac00292a03610.1021/ac00292a036 ↗
23. 10.1021/ac00127a03710.1021/ac00127a037 ↗
24. 10.1016/0250-6874(89)87043-X10.1016/0250-6874(89)87043-X ↗
25. 10.1021/ac00295a04710.1021/ac00295a047 ↗
26. 10.1021/jf00004a02710.1021/jf00004a027 ↗
27. 10.1039/an993180037910.1039/an9931800379 ↗
28. 10.1016/S0925-4005(98)00227-510.1016/S0925-4005(98)00227-5 ↗
29. 10.1016/S0003-2670(98)00780-610.1016/S0003-2670(98)00780-6 ↗
30. 10.1016/j.snb.2005.03.11610.1016/j.snb.2005.03.116 ↗
31. 10.1016/j.snb.2005.02.01710.1016/j.snb.2005.02.017 ↗
32. 10.1021/jp064371z10.1021/jp064371z ↗
33. 10.1108/SR-07-2015-011510.1108/SR-07-2015-0115 ↗
34. 10.3390/s15010000110.3390/s150100001 ↗
35. 10.3390/s14101970010.3390/s141019700 ↗
36. 10.3390/chemosensors906011610.3390/chemosensors9060116 ↗
37. Colina J. · 2000
38. 10.1079/WPS2000001810.1079/WPS20000018 ↗
39. 10.1002/advs.20200201410.1002/advs.202002014 ↗
40. 10.1016/S0140-6736(08)61421-X10.1016/S0140-6736(08)61421-X ↗
41. 10.1016/j.snb.2016.04.16510.1016/j.snb.2016.04.165 ↗
42. 10.1016/j.snb.2017.11.16610.1016/j.snb.2017.11.166 ↗
43. 10.1016/j.snb.2019.12668910.1016/j.snb.2019.126689 ↗
44. 10.1016/j.snb.2019.01.04410.1016/j.snb.2019.01.044 ↗
45. 10.3390/chemosensors908020110.3390/chemosensors9080201 ↗
46. 10.1016/j.jcis.2021.08.02210.1016/j.jcis.2021.08.022 ↗
47. 10.1149/1945-7111/ab67a610.1149/1945-7111/ab67a6 ↗
48. 10.1016/S0140-6736(98)07552-710.1016/S0140-6736(98)07552-7 ↗
49. 10.1088/1752-7155/8/2/02711210.1088/1752-7155/8/2/027112 ↗
50. 10.1021/ac970427x10.1021/ac970427x ↗
51. 10.1016/S0925-4005(99)00153-710.1016/S0925-4005(99)00153-7 ↗
52. 10.3390/s1602018110.3390/s16020181 ↗
53. Stoller A. · RCA Rev. · 1970 · 31 · 265
54. 10.1002/ange.20190777210.1002/ange.201907772 ↗
55. 10.1007/s12274-020-2823-810.1007/s12274-020-2823-8 ↗
56. 10.1039/C8NR04198A10.1039/C8NR04198A ↗
57. 10.1021/acsami.9b0438510.1021/acsami.9b04385 ↗
58. 10.1002/smll.20160286810.1002/smll.201602868 ↗
59. 10.1002/oby.2124210.1002/oby.21242 ↗
60. 10.1002/adma.20140033410.1002/adma.201400334 ↗
61. 10.1016/j.orgel.2018.12.03510.1016/j.orgel.2018.12.035 ↗
62. 10.3390/s1608116310.3390/s16081163 ↗
63. 10.1016/j.snr.2020.10001110.1016/j.snr.2020.100011 ↗
64. 10.3390/chemosensors1002006810.3390/chemosensors10020068 ↗
65. 10.1016/j.snb.2016.08.08510.1016/j.snb.2016.08.085 ↗
66. 10.1002/smll.20190206510.1002/smll.201902065 ↗
67. 10.1109/JSEN.2018.281146110.1109/JSEN.2018.2811461 ↗
68. 10.1021/acsami.0c0072010.1021/acsami.0c00720 ↗
69. 10.1016/j.biosx.2019.10001610.1016/j.biosx.2019.100016 ↗
70. 10.1021/acsami.6b0325610.1021/acsami.6b03256 ↗
71. 10.1186/s40486-021-00136-110.1186/s40486-021-00136-1 ↗
72. 10.1038/s41427-019-0187-x10.1038/s41427-019-0187-x ↗
73. 10.1007/s12274-017-1661-910.1007/s12274-017-1661-9 ↗
74. 10.1016/j.matt.2021.06.00910.1016/j.matt.2021.06.009 ↗
75. 10.1016/j.ifset.2017.08.00310.1016/j.ifset.2017.08.003 ↗
76. 10.1016/j.matchemphys.2018.06.05610.1016/j.matchemphys.2018.06.056 ↗
77. 10.1016/j.talanta.2017.08.02410.1016/j.talanta.2017.08.024 ↗
78. 10.1021/acssensors.6b0082910.1021/acssensors.6b00829 ↗
79. 10.1016/j.snb.2018.04.07810.1016/j.snb.2018.04.078 ↗
80. 10.1021/acssensors.9b0082510.1021/acssensors.9b00825 ↗
81. 10.3390/s15112780410.3390/s151127804 ↗
82. 10.1016/B978-044451980-1.50009-410.1016/B978-044451980-1.50009-4 ↗
83. 10.1002/978111888748610.1002/9781118887486 ↗
84. Li L. · 2019
85. 10.1007/978-3-642-04898-2_39510.1007/978-3-642-04898-2_395 ↗
86. 10.1039/c3cs60179j10.1039/c3cs60179j ↗
87. Raschka S. · 2015 · 2016
88. 10.1109/JSEN.2020.297254210.1109/JSEN.2020.2972542 ↗
89. 10.1063/1.506337510.1063/1.5063375 ↗
90. 10.3390/s1707166210.3390/s17071662 ↗
91. 10.1021/acs.chemrev.8b0022610.1021/acs.chemrev.8b00226 ↗
92. 10.1038/nbt1206-156510.1038/nbt1206-1565 ↗
93. 10.7551/mitpress/4175.001.000110.7551/mitpress/4175.001.0001 ↗
94. Y.Fan D.Shen C.Davatzikos inInt. Conf. Medical Image Computing and Computer-Assisted Intervention Springer Palm Springs CA USA October 26–292005 https://link.springer.com/book/10.1007/11566465.
95. 10.1007/s11548-011-0643-810.1007/s11548-011-0643-8 ↗
96. 10.3390/s2001011710.3390/s20010117 ↗
97. 10.1016/j.snb.2004.05.04310.1016/j.snb.2004.05.043 ↗
98. Maind S. B. · Int. J. Recent Innovation Trends Comput. Commun. · 2014 · 2 · 96
99. 10.1016/j.snb.2008.05.01610.1016/j.snb.2008.05.016 ↗
100. 10.1016/j.snb.2007.08.04410.1016/j.snb.2007.08.044 ↗