Self‐Folded Corrugated Origami Sensor Based on Triboelectric Nanogenerator for a Smart Cushioning Device
Source abstract
Abstract
Abstract Origami technology has been gaining attention across various fields for its ability to impart mechanical properties to sheet materials. In this study, a corrugated origami triboelectric nanogenerator (CO‐TENG) soft sensor using paper self‐folding technology is developed to laminate conductive and charged layers onto paper. The mechanical performance of the paper self‐folding technology is investigated to verify its capability to form an origami structure with other functional sheets. The self‐folding technology creates hinges with elastic memory properties, which enable the conversion of unidirectional kinetic energy into periodic electrical energy. The series connection of the origami TENGs is enabled and improved their output. Specific mechanical evaluations are conducted, including frequency response, the effect of the number of series connections, external load, and a 1000‐cycle repeated test. Additionally, as a demonstration for smart cushioning devices, the output signal obtained from CO‐TENG are classified using LightGBM to identify the dropped objects, which achieved a recognition accuracy of 98.9%. This research is expected to be a core technology for realizing environmentally friendly wearable sensors and smart packaging technologies.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Advanced Materials and Mechanics · Tactile and Sensory Interactions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Graduate School of Engineering and Science Shibaura Institute of Technology 3‐7‐5 Toyosu Koto‐ku Tokyo 135–8548 Japan
College of Engineering Shibaura Institute of Technology 3‐7‐5 Toyosu Koto‐ku Tokyo 135–8548 Japan
Funding
Adaptable and Seamless Technology Transfer Program through Target-Driven R and D · Japan Society for the Promotion of Science
References (37)
Show source-provided references
1. 10.1073/pnas.150946511210.1073/pnas.1509465112 ↗
2. 10.1016/j.matdes.2022.11114610.1016/j.matdes.2022.111146 ↗
3. 10.1126/sciadv.aau283510.1126/sciadv.aau2835 ↗
4. Miura K. · Origami · 2009 · 4 · 87
5. Y.Yoshimura On the mechanism of buckling of a circular cylindrical shell under axial compression1955 No. NACA‐TM‐1390.
6. 10.1016/j.msea.2005.12.01610.1016/j.msea.2005.12.016 ↗
7. 10.1002/aisy.20220008710.1002/aisy.202200087 ↗
8. 10.1103/PhysRevApplied.11.06406910.1103/PhysRevApplied.11.064069 ↗
9. 10.1126/science.125261010.1126/science.1252610 ↗
10. 10.1109/TRO.2018.286288210.1109/TRO.2018.2862882 ↗
11. 10.1039/C1SM06564E10.1039/C1SM06564E ↗
12. 10.1073/pnas.222174012010.1073/pnas.2221740120 ↗
13. 10.1021/la700913m10.1021/la700913m ↗
14. 10.1088/0964-1726/23/9/09400510.1088/0964-1726/23/9/094005 ↗
15. 10.1109/JSEN.2021.305827510.1109/JSEN.2021.3058275 ↗
16. 10.1109/LRA.2017.265894210.1109/LRA.2017.2658942 ↗
17. M. E.Nisser S. M.Felton M. T.Tolley M.Rubenstein R. J.Wood In2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) IEEE Piscataway NJ2016 pp.1254–1261.10.1109/IROS.2016.7759208 ↗
18. 10.1109/TMECH.2016.259391210.1109/TMECH.2016.2593912 ↗
19. 10.1109/JMEMS.2020.304777410.1109/JMEMS.2020.3047774 ↗
20. 10.1021/acsami.2c0824510.1021/acsami.2c08245 ↗
21. 10.1016/j.snb.2017.01.11110.1016/j.snb.2017.01.111 ↗
22. 10.1016/j.apenergy.2018.03.03110.1016/j.apenergy.2018.03.031 ↗
23. 10.1016/j.nanoen.2016.01.00910.1016/j.nanoen.2016.01.009 ↗
24. 10.1016/j.nanoen.2012.01.00410.1016/j.nanoen.2012.01.004 ↗
25. 10.1002/admt.20210070210.1002/admt.202100702 ↗
26. 10.1038/s41467-022-29083-010.1038/s41467-022-29083-0 ↗
27. 10.1016/j.nanoen.2021.10600110.1016/j.nanoen.2021.106001 ↗
28. 10.1016/j.nanoen.2019.10439010.1016/j.nanoen.2019.104390 ↗
29. 10.1039/C7NR05222G10.1039/C7NR05222G ↗
30. 10.1007/s40820-021-00621-710.1007/s40820-021-00621-7 ↗
31. 10.1016/j.nanoen.2014.11.03410.1016/j.nanoen.2014.11.034 ↗
32. G.Ke Q.Meng T.Finley T.Wang W.Chen W.Ma T. Y.Liu Proceedings of the 31st Conference on Neural Information Processing Systems Long Beach CA USA 2017 pp.3149‐3157.
33. 10.1109/JSEN.2023.330322310.1109/JSEN.2023.3303223 ↗
34. Yang Y. · IEEE Trans. Instrum. Meas. · 2021 · 70
35. 10.1016/j.frl.2018.12.03210.1016/j.frl.2018.12.032 ↗
36. 10.3390/app1211556510.3390/app12115565 ↗
37. 10.1109/TPWRS.2020.302813310.1109/TPWRS.2020.3028133 ↗