A Simple Model Relating Gauge Factor to Filler Loading in Nanocomposite Strain Sensors
Source abstract
Abstract
Conductive nanocomposites are often piezoresistive, displaying significant changes in resistance upon deformation, making them ideal for use as strain and pressure sensors. Such composites typically consist of ductile polymers filled with conductive nanomaterials, such as graphene nanosheets or carbon nanotubes, and can display sensitivities, or gauge factors, which are much higher than those of traditional metal strain gauges. However, their development has been hampered by the absence of physical models that could be used to fit data or to optimize sensor performance. Here we develop a simple model which results in equations for nanocomposite gauge factors as a function of both filler volume fraction and composite conductivity. These equations can be used to fit experimental data, outputting figures of merit, or predict experimental data once certain physical parameters are known. We have found these equations to match experimental data, both measured here and extracted from the literature, extremely well. Importantly, the model shows the response of composite strain sensors to be more complex than previously thought and shows factors other than the effect of strain on the interparticle resistance to be performance limiting.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Smart Materials for Construction · Analytical Chemistry and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physics, CRANN & AMBER Research Centres, Trinity College Dublin, Dublin 2, Ireland
Funding
Science Foundation Ireland · Irish Research Council · H2020 Future and Emerging Technologies · H2020 European Research Council
References (59)
Show source-provided references
1. 10.30919/es8d51210.30919/es8d512 ↗
2. 10.30919/es8d73610.30919/es8d736 ↗
3. 10.1016/j.sna.2018.07.00610.1016/j.sna.2018.07.006 ↗
4. 10.1002/adfm.20150475510.1002/adfm.201504755 ↗
5. 10.1021/acsnano.9b0684710.1021/acsnano.9b06847 ↗
6. O’Driscoll D. P. · Small · 2020
7. Window, A. L. Strain gauge technology; Springer: New York, 1992; p 358.
8. 10.30919/esmm5f60110.30919/esmm5f601 ↗
9. 10.30919/esmm5f21410.30919/esmm5f214 ↗
10. 10.30919/es8d61510.30919/es8d615 ↗
11. 10.30919/es8d62810.30919/es8d628 ↗
12. 10.30919/es8d72610.30919/es8d726 ↗
13. 10.1002/adfm.20150475510.1002/adfm.201504755 ↗
14. 10.1063/1.480279910.1063/1.4802799 ↗
15. 10.1126/science.aag287910.1126/science.aag2879 ↗
16. 10.1021/nn503454h10.1021/nn503454h ↗
17. 10.1088/2053-1583/aac05510.1088/2053-1583/aac055 ↗
18. 10.1016/j.carbon.2020.06.07810.1016/j.carbon.2020.06.078 ↗
19. 10.1016/j.carbon.2009.10.01210.1016/j.carbon.2009.10.012 ↗
20. 10.3390/s11111069110.3390/s111110691 ↗
21. 10.1039/C5SM01958C10.1039/C5SM01958C ↗
22. 10.1088/0964-1726/22/1/01500810.1088/0964-1726/22/1/015008 ↗
23. 10.1002/admt.20170028410.1002/admt.201700284 ↗
24. 10.1016/j.compscitech.2019.03.00210.1016/j.compscitech.2019.03.002 ↗
25. 10.1021/nn501204t10.1021/nn501204t ↗
26. 10.1021/jp202999c10.1021/jp202999c ↗
27. 10.1021/acsami.7b1770910.1021/acsami.7b17709 ↗
28. 10.1021/acsnano.9b0161310.1021/acsnano.9b01613 ↗
29. 10.1016/j.compscitech.2008.06.01810.1016/j.compscitech.2008.06.018 ↗
30. 10.1088/0957-4484/23/5/05570310.1088/0957-4484/23/5/055703 ↗
31. 10.1016/j.jmps.2020.10394310.1016/j.jmps.2020.103943 ↗
32. 10.1103/PhysRevB.76.19543310.1103/PhysRevB.76.195433 ↗
33. 10.1039/C9MH00389D10.1039/C9MH00389D ↗
34. 10.1063/5.003365210.1063/5.0033652 ↗
35. 10.1063/1.243223710.1063/1.2432237 ↗
36. 10.1016/j.progpolymsci.2010.07.00510.1016/j.progpolymsci.2010.07.005 ↗
37. 10.1103/PhysRevB.77.17420410.1103/PhysRevB.77.174204 ↗
38. 10.1103/PhysRevB.71.10420110.1103/PhysRevB.71.104201 ↗
39. 10.1103/PhysRevE.52.81910.1103/PhysRevE.52.819 ↗
40. 10.1039/C7NR08077H10.1039/C7NR08077H ↗
41. 10.1103/PhysRevB.72.12140410.1103/PhysRevB.72.121404 ↗
42. 10.1039/c2nr31782f10.1039/c2nr31782f ↗
43. 10.1021/jz300048y10.1021/jz300048y ↗
44. 10.1103/PhysRevE.93.06213210.1103/PhysRevE.93.062132 ↗
45. 10.1142/S021797920402533610.1142/S0217979204025336 ↗
46. 10.1103/PhysRevB.71.06420110.1103/PhysRevB.71.064201 ↗
47. 10.1039/C5TC02751A10.1039/C5TC02751A ↗
48. 10.1063/1.33177910.1063/1.331779 ↗
49. 10.1016/j.matdes.2017.06.01110.1016/j.matdes.2017.06.011 ↗
50. 10.1021/acsami.8b1152710.1021/acsami.8b11527 ↗
51. 10.1088/0964-1726/15/3/00910.1088/0964-1726/15/3/009 ↗
52. Kim J. H. · Sci. Rep. · 2018 · 8 · 1
53. 10.1063/1.482649610.1063/1.4826496 ↗
54. 10.1038/nature0496910.1038/nature04969 ↗
55. 10.1016/j.polymer.2011.11.02010.1016/j.polymer.2011.11.020 ↗
56. 10.1088/2053-1583/aacba610.1088/2053-1583/aacba6 ↗
57. 10.1039/C5NR08047A10.1039/C5NR08047A ↗
58. 10.1016/j.carbon.2015.07.02610.1016/j.carbon.2015.07.026 ↗
59. 10.1103/PhysRevB.79.02430110.1103/PhysRevB.79.024301 ↗