» Articles » PMID: 37888859

Multi-Layered Triboelectric Nanogenerators with Controllable Multiple Spikes for Low-Power Artificial Synaptic Devices

Overview
Journal Adv Sci (Weinh)
Date 2023 Oct 27
PMID 37888859
Authors
Affiliations
Soon will be listed here.
Abstract

In the domains of wearable electronics, robotics, and the Internet of Things, there is a demand for devices with low power consumption and the capability of multiplex sensing, memory, and learning. Triboelectric nanogenerators (TENGs) offer remarkable versatility in this regard, particularly when integrated with synaptic transistors that mimic biological synapses. However, conventional TENGs, generating only two spikes per cycle, have limitations when used in synaptic devices requiring repetitive high-frequency gating signals to perform various synaptic plasticity functions. Herein, a multi-layered micropatterned TENG (M-TENG) consisting of a polydimethylsiloxane (PDMS) film and a composite film that includes 1H,1H,2H,2H-perfluorooctyltrichlorosilane/BaTiO /PDMS are proposed. The M-TENG generates multiple spikes from a single touch by utilizing separate triboelectric charges at the multiple friction layers, along with a contact/separation delay achieved by distinct spacers between layers. This configuration allows the maximum triboelectric output charge of M-TENG to reach up to 7.52 nC, compared to 3.69 nC for a single-layered TENG. Furthermore, by integrating M-TENGs with an organic electrochemical transistor, the spike number multiplication property of M-TENGs is leveraged to demonstrate an artificial synaptic device with low energy consumption. As a proof-of-concept application, a robotic hand is operated through continuous memory training under repeated stimulations, successfully emulating long-term plasticity.

Citing Articles

Multi-Layered Triboelectric Nanogenerators with Controllable Multiple Spikes for Low-Power Artificial Synaptic Devices.

Park Y, Ro Y, Shin Y, Park C, Na S, Chang Y Adv Sci (Weinh). 2023; 10(36):e2304598.

PMID: 37888859 PMC: 10754122. DOI: 10.1002/advs.202304598.

References
1.
Pu X, Guo H, Chen J, Wang X, Xi Y, Hu C . Eye motion triggered self-powered mechnosensational communication system using triboelectric nanogenerator. Sci Adv. 2017; 3(7):e1700694. PMC: 5533541. DOI: 10.1126/sciadv.1700694. View

2.
Liu Y, Liu D, Gao C, Zhang X, Yu R, Wang X . Self-powered high-sensitivity all-in-one vertical tribo-transistor device for multi-sensing-memory-computing. Nat Commun. 2022; 13(1):7917. PMC: 9789038. DOI: 10.1038/s41467-022-35628-0. View

3.
Chun J, Ye B, Lee J, Choi D, Kang C, Kim S . Boosted output performance of triboelectric nanogenerator via electric double layer effect. Nat Commun. 2016; 7:12985. PMC: 5059471. DOI: 10.1038/ncomms12985. View

4.
Kim M, Um D, Shin Y, Ko H . High-Performance Triboelectric Devices via Dielectric Polarization: A Review. Nanoscale Res Lett. 2021; 16(1):35. PMC: 7881083. DOI: 10.1186/s11671-021-03492-4. View

5.
Kim S, Yoon J, Kim H, Choi S . Carbon Nanotube Synaptic Transistor Network for Pattern Recognition. ACS Appl Mater Interfaces. 2015; 7(45):25479-86. DOI: 10.1021/acsami.5b08541. View