Intrinsically stretchable tribotronic mechanoplastic artificial synapse
Jianhua Zeng, Libo Chen, Tianzhao Bu, Ziyue Wang, Likun Gong, Zhibin Zhang, Junqing Zhao, Zhong Lin Wang, Chi Zhang
- 发表年份
- 2024
- 引用次数
- 9
摘要
• An intrinsically stretchable tribotronic mechanoplastic artificial synapse was proposed. • The device can be modulated by the triboelectric potential induced by mechanical stimulation. • The device establishes an active mechanically adjustable synaptic plasticity. Stretchable synaptic devices with adaptability to elastic deformation, sensing environmental stimuli, and unique information processing functions are of great significance for the development of the next generation of artificial nervous systems. Here, an intrinsically stretchable tribotronic mechanoplastic artificial synapse (STMAS) is proposed, which is integrated by a triboelectric nanogenerator and an electrolyte-gated transistor with ion-gel as dielectric layer. The STMAS can be modulated by the triboelectric potential induced by mechanical stimulation without the need to apply an external gate voltage, achieving an active mechanical tuning of synaptic plasticity such as excitatory postsynaptic current, paired-pulse facilitation, short-term plasticity, and long-term plasticity. The STMAS exhibits stable synaptic plasticity under 0–50% stretcher strain in parallel and vertical to channel directions, respectively. Furthermore, the International Morse code triggered by mechanical signals has been successfully mimicked. This work has achieved an intrinsically stretchable tribotronic artificial synapse with mechanically tuned synaptic behavior, which will help promote the development of artificial nervous systems and expand the applications of artificial synapses in intelligent robotics, artificial limbs and human–machine interaction.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992