journal article·2023-01-18

Mechano-Optical Response Behavior of Polymer-Dispersed Cholesteric Liquid Crystals for Reversible and Highly Sensitive Force Recorders

Zhao Xu, Meng Liu, Yang Liu, Yan Pan, Lili Yang, Dengteng Ge

Publisher page

Abstract

Force recording (mode, intensity, and orientation) is of great importance in medical rehabilitation, military reconnaissance, space exploration, etc. However, sensors with both reversibility and memorability are still challenging. Here, a reversible sensor based on polymer-dispersed cholesteric liquid crystals (CLC) is developed as a force recorder. Based on the microarea mechano-optical response and finite element analysis, it is confirmed that the mechanochromic response is mediated by the shear deformation of the polymer network and neighboring CLC. There is an obvious quantitative relationship between force intensity, mode, orientation, and the microarea optical response. Moreover, the sensing layer with a lower modulus or thickness is advantageous for a more sensitive device with lower starting pressure. Additionally, the excellent sensitivity and accuracy also highlight the potential applications in force analysis, path tracking, or pattern detection.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Mechanical and Optical Resonators · Ocular Surface and Contact Lens · Force Microscopy Techniques and Applications

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

Affiliations

State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai201620, China

Institute of Functional Materials, Donghua University, Shanghai201620, China

Funding

National Natural Science Foundation of China

References (33)

Show source-provided references
1. 10.1016/j.nanoen.2020.10493210.1016/j.nanoen.2020.104932 ↗
2. 10.1002/adfm.20170665810.1002/adfm.201706658 ↗
3. 10.1016/j.sna.2021.11311210.1016/j.sna.2021.113112 ↗
4. 10.1109/JLT.2017.269630110.1109/JLT.2017.2696301 ↗
5. 10.1016/j.yofte.2017.02.00610.1016/j.yofte.2017.02.006 ↗
6. 10.1039/C2CS35414D10.1039/C2CS35414D ↗
7. 10.1021/ja505163310.1021/ja5051633 ↗
8. 10.1021/ja510701810.1021/ja5107018 ↗
9. 10.1002/chem.20140632010.1002/chem.201406320 ↗
10. 10.1038/nchem.135810.1038/nchem.1358 ↗
11. 10.1002/pola.2844510.1002/pola.28445 ↗
12. 10.1016/j.progpolymsci.2017.11.00110.1016/j.progpolymsci.2017.11.001 ↗
13. 10.1002/adma.20150028110.1002/adma.201500281 ↗
14. 10.1002/adma.20180029110.1002/adma.201800291 ↗
15. 10.1002/adfm.20150277410.1002/adfm.201502774 ↗
16. 10.1089/neu.2010.171810.1089/neu.2010.1718 ↗
17. 10.1016/j.neuroimage.2010.10.07610.1016/j.neuroimage.2010.10.076 ↗
18. 10.1039/C8TC00202A10.1039/C8TC00202A ↗
19. 10.1039/C9MH00101H10.1039/C9MH00101H ↗
20. 10.1002/adma.20130069210.1002/adma.201300692 ↗
21. 10.1002/anie.20090709110.1002/anie.200907091 ↗
22. 10.1039/c2cs15267c10.1039/c2cs15267c ↗
23. 10.1016/j.dyepig.2019.10792810.1016/j.dyepig.2019.107928 ↗
24. 10.1002/adom.20150027710.1002/adom.201500277 ↗
25. 10.1016/j.dyepig.2019.04.03610.1016/j.dyepig.2019.04.036 ↗
26. 10.1002/adfm.20210326810.1002/adfm.202103268 ↗
27. 10.1364/OE.24.02996310.1364/OE.24.029963 ↗
28. 10.1002/anie.20211621910.1002/anie.202116219 ↗
29. 10.1021/acsami.5b1285410.1021/acsami.5b12854 ↗
30. 10.1002/adfm.20200315010.1002/adfm.202003150 ↗
31. 10.1002/adma.20200636110.1002/adma.202006361 ↗
32. 10.1021/acsapm.1c0136210.1021/acsapm.1c01362 ↗
33. 10.1039/c2sm26501j10.1039/c2sm26501j ↗