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/BaTiO3 /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.
Keywords: artificial synaptic devices; human-machine interface; transistors; triboelectric nanogenerators.
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