journal article·2025

Stretchable hierarchical metal wire networks for neuromorphic emulation of nociception and anti-nociception

Bhupesh Yadav, Indrajit Mondal, Manpreet Kaur, Vidhyadhiraja N. S., Giridhar U. Kulkarni

Materials Horizons· Volume 12· Issue 2
Publisher page

Abstract

Among biomimetic technologies, the incorporation of sensory hardware holds exceptional utility in human-machine interfacing. In this context, devices receptive to nociception and emulating antinociception gain significance as part of pain management. Here we report, a stretchable two-terminal resistive neuromorphic device consisting of a hierarchical Ag microwire network formed using a crack templating protocol. The device demonstrates sensitivity to strain, where the application of strain induces the formation of gaps across active elements, rendering the device electrically open. Following activation by voltage pulses, the device exhibits potentiated states with finite retentions arising from filamentary growth across these gaps due to field migration. Remarkably, the strain-induced functioning alongside controllable gaps enables achieving user-controlled neuromorphic properties, desired for self-adaptive intelligent systems. Interestingly, in the neuromorphic potentiated state, the response to strain is enhanced by ∼106 due to higher sensitivities associated with nanofilaments. The device emulates basic neuromorphic functionalities such as threshold switching, and short-term (STP) and long-term potentiations (LTP). Furthermore, the sensitivity has been exploited in mimicking nociception through strain-induced changes in the potentiated state. Interestingly, repetition of the strain stimulus leads to endurance making the device restore its conductance, thereby emulating adaptation and habituation representing the antinociceptive behavior.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: EEG and Brain-Computer Interfaces · Neuroscience and Neural Engineering · Advanced Memory and Neural Computing

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

Affiliations

Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India

Theoretical Science Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India

Funding

Department of Science and Technology, Ministry of Science and Technology, India · Science and Engineering Research Board · Council of Scientific and Industrial Research, India

References (68)

Show source-provided references
1. Nikolenko · J. Pain Res. · 2022 · 15 · 86710.2147/JPR.S348324 ↗
2. Zhu · Appl. Phys. Rev. · 2020 · 7 · 01131210.1063/1.5118217 ↗
3. Yang · Adv. Electron. Mater. · 2023 · 9 · 220100610.1002/aelm.202201006 ↗
4. Kim · Adv. Mater. · 2018 · 30 · 1
5. Xiao · Adv. Electron. Mater. · 2020 · 6 · 1
6. Yoon · Nat. Commun. · 2018 · 9 · 110.1038/s41467-017-02088-w ↗
7. Sahu · ACS Appl. Mater. Interfaces · 2023 · 15 · 2571310.1021/acsami.3c02727 ↗
8. Feng · Adv. Mater. · 2020 · 32 · 1
9. John · Adv. Mater. · 2021 · 33 · 110.1002/adma.202007851 ↗
10. Dev · IEEE Electron Device Lett. · 2020 · 41 · 144010.1109/LED.2020.3012831 ↗
11. Chen · ACS Appl. Mater. Interfaces · 2023 · 15 · 959310.1021/acsami.2c20297 ↗
12. Li · Nanoscale · 2022 · 14 · 231610.1039/D1NR07896H ↗
13. Khan · Nanoscale · 2022 · 15 · 190010.1039/D2NR05257A ↗
14. Duan · Nanoscale · 2023 · 15 · 1008910.1039/D3NR01301D ↗
15. Patil · ACS Appl. Mater. Interfaces · 2023 · 15 · 1323810.1021/acsami.2c16481 ↗
16. Kumar · Adv. Mater. · 2019 · 31 · 1
17. Feng · Adv. Funct. Mater. · 2021 · 31 · 1
18. Zhou · Nanoscale · 2020 · 12 · 148410.1039/C9NR08872E ↗
19. Wei · Nano Energy · 2021 · 81 · 10564810.1016/j.nanoen.2020.105648 ↗
20. Shi · Nano Energy · 2023 · 110 · 10837210.1016/j.nanoen.2023.108372 ↗
21. Bhatnagar · Nanoscale · 2021 · 13 · 524310.1039/D0NR08966D ↗
22. Wu · Nano Energy · 2021 · 85 · 10600010.1016/j.nanoen.2021.106000 ↗
23. Shi · Nano Energy · 2023 · 113 · 10854910.1016/j.nanoen.2023.108549 ↗
24. Li · Adv. Intell. Syst. · 2022 · 4 · 1
25. Xu · Adv. Sci. · 2022 · 9 · 1
26. Zhu · IEEE Electron Device Lett. · 2022 · 43 · 96210.1109/LED.2022.3167421 ↗
27. Yu · Mater. Horiz. · 2021 · 8 · 279710.1039/D1MH01061A ↗
28. Yu · ACS Appl. Mater. Interfaces · 2020 · 12 · 2625810.1021/acsami.0c04718 ↗
29. Ding · Small · 2022 · 18 · 1
30. Xia · J. Mater. Chem. B · 2022 · 10 · 199110.1039/D1TB02578C ↗
31. Xu · Mater. Horiz. · 2024 · 11 · 95810.1039/D3MH01766D ↗
32. Wang · ACS Nano · 2022 · 16 · 828310.1021/acsnano.2c02089 ↗
33. Yan · Adv. Mater. · 2022 · 34 · 1
34. Xia · Nat. Mater. · 2019 · 18 · 30910.1038/s41563-019-0291-x ↗
35. Kim · iScience · 2020 · 23 · 10184610.1016/j.isci.2020.101846 ↗
36. Banerjee · Electronics · 2020 · 9 · 110.3390/electronics9061029 ↗
37. Bannur · ACS Appl. Electron. Mater. · 2022 · 4 · 155210.1021/acsaelm.1c01237 ↗
38. Yadav · Nanotechnology · 2023 · 35 · 01520510.1088/1361-6528/acf66f ↗
39. Bannur · Mater. Horiz. · 2020 · 7 · 297010.1039/D0MH01037E ↗
40. Rao · Discov. Nano · 2023 · 18 · 12410.1186/s11671-023-03906-5 ↗
41. Attri · Mater. Horiz. · 2024 · 11 · 73710.1039/D3MH01367G ↗
42. Im · Adv. Mater. · 2023 · 2307334 · 1
43. Harris · J. Physiol. (Paris) · 1996 · 90 · 1510.1016/0928-4257(96)87165-8 ↗
44. Butler · Prog. Neurobiol. · 2009 · 88 · 18410.1016/j.pneurobio.2009.04.003 ↗
45. Jhaveri · Mol. Neurobiol. · 2007 · 36 · 2610.1007/s12035-007-8007-7 ↗
46. Wan · Neuromorphic Comput. Eng. · 2022 · 2 · 04250110.1088/2634-4386/ac7a5a ↗
47. Kiruthika · J. Mater. Chem. C · 2014 · 2 · 208910.1039/c3tc32167c ↗
48. Govind · Adv. Mater. Technol. · 2022 · 7 · 210112010.1002/admt.202101120 ↗
49. Li · Adv. Mater. Technol. · 2020 · 5 · 190082310.1002/admt.201900823 ↗
50. Gupta · ACS Appl. Mater. Interfaces · 2018 · 10 · 4412610.1021/acsami.8b16282 ↗
51. Mondal · Adv. Mater. Interfaces · 2022 · 9 · 1
52. Tennico · Sens. Actuators, B · 2010 · 143 · 79910.1016/j.snb.2009.10.001 ↗
53. Nag · IEEE Access · 2018 · 6 · 7102010.1109/ACCESS.2018.2881463 ↗
54. Yang · Phys. Rev. B: Condens. Matter Mater. Phys. · 2015 · 91 · 23513710.1103/PhysRevB.91.235137 ↗
55. Rao · Adv. Mater. Interfaces · 2014 · 1 · 140009010.1002/admi.201400090 ↗
56. Masuda · J. Nanosci. Nanotechnol. · 2014 · 14 · 243610.1166/jnn.2014.8502 ↗
57. Qu · J. Phys. D: Appl. Phys. · 2021 · 55 · 15300210.1088/1361-6463/ac3e2c ↗
58. Liew · Int. J. Extrem. Manuf. · 2020 · 2 · 1200410.1088/2631-7990/ab7332 ↗
59. Islamov · J. Electrostat. · 2013 · 71 · 10910.1016/j.elstat.2012.12.019 ↗
60. Cogollo de Cádiz · Sci. Rep. · 2021 · 11 · 2417510.1038/s41598-021-03447-w ↗
61. Rodrigues · Mater. Res. · 2019 · 22 · e20180530
62. X. X. F.Sánchez-Romate , A. J.Suárez and S. G.Prolongo , in 21st Century Surface Science , ed. P. Pham , P. Goel , S. Kumar and K. Yadav , IntechOpen , Rijeka , 2020
63. Preston · Sci. Robot. · 2019 · 4 · 110.1126/scirobotics.aaw5496 ↗
64. Li · Am. J. Phys. · 2016 · 84 · 3210.1119/1.4935358 ↗
65. Zhang · Adv. Mater. · 2020 · 32 · 190661910.1002/adma.201906619 ↗
66. Yan · Nat. Commun. · 2021 · 12 · 610.1038/s41467-020-20095-2 ↗
67. Liu · Adv. Mater. · 2015 · 27 · 623010.1002/adma.201503288 ↗
68. Kumaresan · Adv. Intell. Syst. · 2022 · 4 · 110.1002/aisy.202200043 ↗