A graphene nanoplatelets-based high-performance, durable triboelectric nanogenerator for harvesting the energy of human motion
- Authors
- Shabbir, Irfan; Lee, Dong-Min; Choo, Dong Chul; Lee, Yong Hun; Park, Kwan Kyu; Yoo, Keon Ho; Kim, Sang-Woo; Kim, Tae Whan
- Issue Date
- Nov-2022
- Publisher
- Elsevier Ltd
- Keywords
- Gesture recognition; Graphene nanoplatelet; Sliding mode; Surface abrasion; Triboelectric nanogenerators
- Citation
- Energy Reports, v.8, pp.1026 - 1033
- Indexed
- SCIE
SCOPUS
- Journal Title
- Energy Reports
- Volume
- 8
- Start Page
- 1026
- End Page
- 1033
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/169997
- DOI
- 10.1016/j.egyr.2021.12.020
- ISSN
- 2352-4847
- Abstract
- Triboelectric nanogenerators (TENGs) have been widely investigated to harness mechanical energy that is driven by repetitive human motion. Conventional human motion-driven TENGs are mostly based on contact–separation (CS) mode, but their energy harvesting performance is limited due to the high crest factor (the ratio of the peak to the RMS value of output voltage). Here, we demonstrate a new rolling type triboelectric nanogenerator (RL-TENG), exhibiting the lower crest factor than CS mode TENGs, using a metal layer and graphene nanoplatelets-doped PDMS. These additions helped improve the dielectric constant and the charge storage capacity of the TENG, which led to a high electrical output while minimizing surface damage. As compared to a pristine TENG, our device, a RL-TENG, generated an open-circuit peak voltage of 75.2 V, which was almost 15 times higher than that of the pristine device, and a short-circuit peak current of 7.36μA, which was 12 times higher. With a dual-side double-belt TENG (DB-TENG), these values were improved to 164 V and 10μA. Lastly, our device was used in a real-life application, to harvest mechanical energy from the movement of the human elbow while walking, and was able to produce a high voltage output of up to 821 V. These results show that the DB-TENG can be used for high-efficiency harvesting of energy from human motion.
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