The self-powered artificial synapse mechanotactile sensing system by integrating triboelectric plasma and gas-ionic-gated graphene transistor

• DOI: 10.1016/j.nanoen.2021.106660
• Publication Date: 2021-10-28T14:28:38Z
• Authors: Song Zhang; Junmeng Guo; Liangliang Liu; Haoran Ruan; Chuiyun Kong; Xiaobo Yuan; Bao Zhang; Guangqin Gu; Peng Cui; Gang Cheng; Zuliang Du
• Keywords: 01 natural sciences; 7. Clean energy; 0104 chemical sciences

Abstract The emulation of biological nerves to develop artificial synapse tactile sensing system has great application potentials in the fields of Internet of Things and artificial intelligence. Novel sensing strategies to achieve low power consumption, low cost, low complexity and high efficiency still face challenges. Here, a self-powered tactile sensing system has been developed by integrating a triboelectric plasma and a gas-ions-gated (GIG) graphene transistor, in which the GIG transistor is served as the artificial synapse, and the triboelectric plasma is served as both a tactile sensor and the driving signals of the GIG transistor. The N2+ ions in the triboelectric plasma are directly adsorbed on the graphene surface, acting as a floating gate of the GIG transistor to regulate its electrical transport characteristics. The adsorption density of N2+ ions reach up to 3.96 × 1012 cm−2 with a measured desorption energy of 196 meV. The theoretical simulation shows that the N2+ ion is adsorbed at the site of carbon vacancy on the graphene surface. By regulating the number, frequency and polarization of the discharge pulse, various synaptic behaviors are achieved, such as short-term depression, long-term depression, long-term potentiation, paired-pulse facilitation, etc. Also, the neural functions of learning and temporal decoding have been demonstrated in experiments. By combining triboelectric plasma and GIG transistor, a facile experimental scheme for a self-powered, integrated, and simple structured intelligent tactile sensing system has been proposed, which is highly expected to promote the development of intelligent sensing fields in the future.