Flexible and Self-Powered Thermal Sensor Based on Graphene-Modified Intumescent Flame-Retardant Coating with Hybridized Nanogenerators
Source abstract
Abstract
The number of fire events that risk human life, the economy, and the environment has significantly increased in recent years. Uncontrolled fires are one of the main causes of building collapse. Due to the high smoke concentration threshold or infrared detection temperature required to activate the fire detector, the response time is long, and the fire warning and prevention effect are not ideal. For effective monitoring and early warning of fires, an innovative fire alarm system was fabricated in this study. This system combines a highly flexible and self-powered thermal sensor (FSTS) as well as a commercial light emitting diode (LED). The FSTS is a fire-retardant sensor and very easy to install. The innovation of this paper is the hierarchical structure of the FSTS. It combines a graphene-modified intumescent flame retardant (GIFR) flame-retardant coating layer with a self-powered PVDF-based nanogenerator, which shows an innovative design in the area of fire sensors. The structure integrates poly(vinylidenefluoride- co -trifluoroethylene) (PVDF-TrFE) micro/nano fibers (MNFs) deposited by a near-field electrospinning (NFES) process and an electrostatic friction layer by polydimethylsiloxane (PDMS) rolling over technology with a fully encapsulated GIFR coating. It can be used as a motion-induced energy harvester with a self-powered fire alarm system. The voltage output of the FSTS reaches 11.8 V, which can be easily matched with a bridge rectifier circuit to charge capacitors in daily life. The unique feature of the FSTS is that, at room temperature, the FSTS is electrically insulating; however, it conducts electricity at high temperatures. In a fire, high temperatures cause the coating to char and expand transitioning from an electrically insulating state to a conducting state. In this way, warning lights connected to the FSTS will respond within a short period (∼3 s), alerting people immediately so that urgent action can be taken.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Fire Detection and Safety Systems · Fire dynamics and safety research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, National Central University, Taoyuan City 320317, Taiwan
Institute of Energy Engineering, National Central University, Taoyuan City 320317, Taiwan
Funding
Ministry of Science and Technology of the People's Republic of China · National Science and Technology Council
References (50)
Show source-provided references
1. 10.1021/acsnano.7b0659010.1021/acsnano.7b06590 ↗
2. 10.1016/j.nanoen.2014.11.03410.1016/j.nanoen.2014.11.034 ↗
3. 10.1016/j.nanoen.2018.10.05310.1016/j.nanoen.2018.10.053 ↗
4. 10.1016/j.nanoen.2020.10538110.1016/j.nanoen.2020.105381 ↗
5. 10.1021/acsnano.7b0297510.1021/acsnano.7b02975 ↗
6. 10.1021/acsnano.8b0041610.1021/acsnano.8b00416 ↗
7. 10.1016/j.nanoen.2020.10525110.1016/j.nanoen.2020.105251 ↗
8. 10.1021/nn404023v10.1021/nn404023v ↗
9. 10.1021/nl904071910.1021/nl9040719 ↗
10. 10.1002/admt.20200077910.1002/admt.202000779 ↗
11. 10.1016/j.nanoen.2020.10502910.1016/j.nanoen.2020.105029 ↗
12. 10.1002/advs.20180223010.1002/advs.201802230 ↗
13. 10.1038/srep0930910.1038/srep09309 ↗
14. 10.1002/aenm.20160156910.1002/aenm.201601569 ↗
15. 10.1002/adma.20150012110.1002/adma.201500121 ↗
16. 10.3390/app1102051910.3390/app11020519 ↗
17. 10.3144/expresspolymlett.2019.4510.3144/expresspolymlett.2019.45 ↗
18. 10.1007/s12274-022-4321-710.1007/s12274-022-4321-7 ↗
19. 10.1016/j.mser.2017.04.00110.1016/j.mser.2017.04.001 ↗
20. 10.1177/073490411039546910.1177/0734904110395469 ↗
21. 10.1016/j.polymdegradstab.2015.09.00510.1016/j.polymdegradstab.2015.09.005 ↗
22. 10.1016/S0079-6700(02)00018-710.1016/S0079-6700(02)00018-7 ↗
23. 10.1021/ie101737n10.1021/ie101737n ↗
24. 10.1016/j.porgcoat.2021.10640010.1016/j.porgcoat.2021.106400 ↗
25. 10.1016/j.polymdegradstab.2019.02.02110.1016/j.polymdegradstab.2019.02.021 ↗
26. 10.1002/app.5186010.1002/app.51860 ↗
27. 10.1080/0360255080267564510.1080/03602550802675645 ↗
28. 10.1016/j.matdes.2011.05.03210.1016/j.matdes.2011.05.032 ↗
29. 10.3390/coatings902009410.3390/coatings9020094 ↗
30. 10.1016/j.progpolymsci.2015.04.01010.1016/j.progpolymsci.2015.04.010 ↗
31. 10.1039/b702511d10.1039/b702511d ↗
32. 10.1016/j.mser.2008.09.00210.1016/j.mser.2008.09.002 ↗
33. 10.1016/j.polymdegradstab.2013.04.00910.1016/j.polymdegradstab.2013.04.009 ↗
34. 10.1016/j.compositesa.2017.04.01210.1016/j.compositesa.2017.04.012 ↗
35. 10.1007/s10853-015-9083-010.1007/s10853-015-9083-0 ↗
36. 10.1016/j.polymer.2011.06.04510.1016/j.polymer.2011.06.045 ↗
37. 10.1016/j.compscitech.2016.12.01510.1016/j.compscitech.2016.12.015 ↗
38. 10.1016/j.compositesa.2013.12.01010.1016/j.compositesa.2013.12.010 ↗
39. 10.1016/j.sna.2022.11362210.1016/j.sna.2022.113622 ↗
40. 10.1016/j.nanoen.2018.03.06410.1016/j.nanoen.2018.03.064 ↗
41. 10.1007/s11431-018-9386-910.1007/s11431-018-9386-9 ↗
42. 10.1002/admt.20200004610.1002/admt.202000046 ↗
43. 10.1021/acsami.1c0034010.1021/acsami.1c00340 ↗
44. 10.1039/D1TC05087G10.1039/D1TC05087G ↗
45. 10.1007/978-1-4615-5019-8_510.1007/978-1-4615-5019-8_5 ↗
46. 10.1201/978142006402510.1201/9781420064025 ↗
47. 10.1201/978142006402510.1201/9781420064025 ↗
48. Das A. K. · 2014 · 89
49. Qualey J. · Proc. NIST · 2001 · 12 · 283
50. 10.3390/f1107075510.3390/f11070755 ↗