Flexible Multimode Sensors: Structural Design, Signal Decoupling, and Emerging Applications
Source abstract
Abstract
Abstract Flexible multimode sensors have become key components in intelligent sensing due to their flexibility, multifunctionality, and adaptability, with broad applications in wearables, healthcare, and robotics. This review summarizes recent advances in their structural design, sensing mechanisms, and signal processing strategies, and highlights applications in industrial automation, smart agriculture, and wearable systems. Compared to previous reviews, this work uniquely classifies multimode sensors into three structural types—homogeneous, heterogeneous, and array‐based—and comprehensively compares their design principles and use cases. To address multimodal signal coupling, three decoupling strategies—material‐, structure‐, and algorithm‐driven—providing a holistic perspective rarely integrated in earlier literature is highlighted. Representative case studies demonstrate practical value, while current challenges such as signal crosstalk and manufacturing complexity are outlined. Finally, future directions including biomimetic materials, edge computing, and green manufacturing are proposed to guide further development.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Gas Sensing Nanomaterials and Sensors · Analytical Chemistry and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering Hangzhou Dianzi University Hangzhou 310018 China
Funding
National Natural Science Foundation of China
References (100+)
Show source-provided references
1. 10.1016/j.nanoen.2024.10944310.1016/j.nanoen.2024.109443 ↗
2. 10.1021/acssensors.3c0255510.1021/acssensors.3c02555 ↗
3. 10.1021/acsnano.3c0408910.1021/acsnano.3c04089 ↗
4. 10.3390/ma1317378110.3390/ma13173781 ↗
5. 10.1002/VIW.2022002710.1002/VIW.20220027 ↗
6. 10.1109/JAS.2017.751060410.1109/JAS.2017.7510604 ↗
7. 10.3390/ma1318394710.3390/ma13183947 ↗
8. 10.1016/j.bios.2022.11429810.1016/j.bios.2022.114298 ↗
9. 10.1021/acsnano.2c1260610.1021/acsnano.2c12606 ↗
10. 10.3390/electronics707011410.3390/electronics7070114 ↗
11. 10.1038/micronano.2016.4310.1038/micronano.2016.43 ↗
12. Lee J. H. · Adv. Mater. · 2024 · 36
13. 10.3390/mi911058010.3390/mi9110580 ↗
14. Liu R. · Front. Chem. · 2021 · 9
15. Han F. · Nanomaterials · 2021 · 11
16. 10.1021/acsami.9b1334910.1021/acsami.9b13349 ↗
17. 10.1038/s41378-022-00358-210.1038/s41378-022-00358-2 ↗
18. O'Neill J. · Sensors · 2018 · 18
19. 10.1109/TIM.2004.83461310.1109/TIM.2004.834613 ↗
20. 10.3390/mi1408155410.3390/mi14081554 ↗
21. 10.1109/JPROC.2019.293080810.1109/JPROC.2019.2930808 ↗
22. 10.1002/adma.20230470110.1002/adma.202304701 ↗
23. 10.3390/s10060546910.3390/s100605469 ↗
24. 10.1021/acsami.0c0226310.1021/acsami.0c02263 ↗
25. 10.1007/s40820-019-0288-710.1007/s40820-019-0288-7 ↗
26. 10.1088/2058-8585/ab807310.1088/2058-8585/ab8073 ↗
27. 10.3390/s10111021110.3390/s101110211 ↗
28. Wang B. · Sensors · 2016 · 16
29. 10.3390/s2301054310.3390/s23010543 ↗
30. Yan C. · Adv. Funct. Mater. · 2024 · 34
31. 10.1016/j.mattod.2019.12.00410.1016/j.mattod.2019.12.004 ↗
32. 10.1016/j.nanoen.2018.06.05910.1016/j.nanoen.2018.06.059 ↗
33. 10.1149/1945-7111/ab682810.1149/1945-7111/ab6828 ↗
34. Gao Y. · Adv. Funct. Mater. · 2020 · 30
35. 10.1109/JSEN.2020.303417210.1109/JSEN.2020.3034172 ↗
36. 10.1002/adma.20160316010.1002/adma.201603160 ↗
37. 10.1021/acsami.9b0981510.1021/acsami.9b09815 ↗
38. 10.1016/j.pmatsci.2021.10084010.1016/j.pmatsci.2021.100840 ↗
39. Yoon K. · Adv. Funct. Mater. · 2024 · 35
40. 10.1002/adfm.20201082410.1002/adfm.202010824 ↗
41. 10.1109/LED.2020.302093710.1109/LED.2020.3020937 ↗
42. 10.1002/admt.20180028410.1002/admt.201800284 ↗
43. 10.1016/j.scitotenv.2020.14117210.1016/j.scitotenv.2020.141172 ↗
44. 10.3390/s12060833810.3390/s120608338 ↗
45. Malik S. · Heliyon · 2023 · 9
46. 10.1021/acsami.0c1615210.1021/acsami.0c16152 ↗
47. 10.1021/acsami.1c0699310.1021/acsami.1c06993 ↗
48. 10.1002/adma.20130506410.1002/adma.201305064 ↗
49. 10.1002/aisy.20210007210.1002/aisy.202100072 ↗
50. 10.1002/adfm.20160443410.1002/adfm.201604434 ↗
51. 10.1021/acsapm.4c0006710.1021/acsapm.4c00067 ↗
52. 10.1021/acsnano.0c0375710.1021/acsnano.0c03757 ↗
53. 10.1021/acsami.3c0785710.1021/acsami.3c07857 ↗
54. 10.1002/adfm.20230731310.1002/adfm.202307313 ↗
55. 10.1126/science.aba550410.1126/science.aba5504 ↗
56. 10.1021/acsami.0c2196010.1021/acsami.0c21960 ↗
57. 10.1002/adma.20220383010.1002/adma.202203830 ↗
58. 10.1039/D0TA12359E10.1039/D0TA12359E ↗
59. 10.1038/s43586-023-00220-310.1038/s43586-023-00220-3 ↗
60. 10.1002/smtd.20210040910.1002/smtd.202100409 ↗
61. 10.1002/adfm.20190162310.1002/adfm.201901623 ↗
62. 10.1021/acs.nanolett.4c0089410.1021/acs.nanolett.4c00894 ↗
63. 10.1016/j.isci.2022.10403210.1016/j.isci.2022.104032 ↗
64. 10.1016/j.coco.2021.10083710.1016/j.coco.2021.100837 ↗
65. 10.1007/s10853-017-1644-y10.1007/s10853-017-1644-y ↗
66. 10.1021/acsaelm.9b0072410.1021/acsaelm.9b00724 ↗
67. 10.1021/acsami.9b1338310.1021/acsami.9b13383 ↗
68. 10.1002/adma.20180338810.1002/adma.201803388 ↗
69. 10.1021/acsami.0c0444810.1021/acsami.0c04448 ↗
70. 10.1021/acsami.1c0087910.1021/acsami.1c00879 ↗
71. 10.1126/scirobotics.abc687810.1126/scirobotics.abc6878 ↗
72. 10.1016/j.matt.2022.02.01610.1016/j.matt.2022.02.016 ↗
73. 10.1002/advs.20250279710.1002/advs.202502797 ↗
74. 10.1126/sciadv.160220010.1126/sciadv.1602200 ↗
75. 10.1007/s40820-021-00615-510.1007/s40820-021-00615-5 ↗
76. 10.1021/acs.nanolett.2c0114510.1021/acs.nanolett.2c01145 ↗
77. Xu Q. · Adv. Funct. Mater. · 2024 · 35
78. 10.1002/adma.20241409610.1002/adma.202414096 ↗
79. 10.1016/j.nanoen.2021.10660310.1016/j.nanoen.2021.106603 ↗
80. 10.1016/j.nanoen.2021.10677710.1016/j.nanoen.2021.106777 ↗
81. 10.1016/j.nanoen.2020.10507310.1016/j.nanoen.2020.105073 ↗
82. 10.1021/acs.nanolett.0c0251910.1021/acs.nanolett.0c02519 ↗
83. Fu Y. · Adv. Funct. Mater. · 2024
84. 10.1126/sciadv.abd779510.1126/sciadv.abd7795 ↗
85. 10.1126/scirobotics.abc880110.1126/scirobotics.abc8801 ↗
86. 10.1021/acsami.1c1380210.1021/acsami.1c13802 ↗
87. Zhang H. · Adv. Funct. Mater. · 2022 · 32
88. 10.1016/j.xcrp.2024.10222310.1016/j.xcrp.2024.102223 ↗
89. 10.1002/advs.20180212810.1002/advs.201802128 ↗
90. 10.1002/advs.20220247010.1002/advs.202202470 ↗
91. 10.1007/s10854-018-0111-010.1007/s10854-018-0111-0 ↗
92. 10.1016/j.jmst.2021.07.00810.1016/j.jmst.2021.07.008 ↗
93. 10.1021/acsami.1c2100310.1021/acsami.1c21003 ↗
94. 10.3390/s1907171610.3390/s19071716 ↗
95. 10.1002/aisy.20220021310.1002/aisy.202200213 ↗
96. 10.3390/s1908186310.3390/s19081863 ↗
97. 10.1126/sciadv.adp034810.1126/sciadv.adp0348 ↗
98. 10.3389/frobt.2021.69275410.3389/frobt.2021.692754 ↗
99. 10.1109/ACCESS.2020.298094210.1109/ACCESS.2020.2980942 ↗
100. Liu H. · Measurement · 2025 · 239