Electrospun Nanofiber‐Based Synaptic Transistor with Tunable Plasticity for Neuromorphic Computing

• DOI: 10.1002/adfm.202208055
• Publication Date: 2022-12-12T21:00:14Z
• Authors: Yizhe Guo; Fan Wu; Guan‐Hua Dun; Tianrui Cui; Yanming Liu; Xichao Tan; Yancong Qiao; Mario Lanza; He Tian; Yi Yang; Tian‐Ling Ren
• Keywords: Neuromorphic engineering; Synaptic weight; Electrospinning

Abstract Biological synapses are the operational connection of neurons for signal transmission in neuromorphic networks and hardware implementation combined with electrospun 1D nanofibers have realized its functionality complicated computing tasks basic three‐terminal field‐effect transistors gate‐controlled channel conductance. However, it still lacks fundamental understanding that how technological parameters influence intensity information processing neural systems nanofiber‐based synaptic transistors. Here, by tuning electrospinning introducing surface doping, an ZnO transistor tunable plasticity is presented to emulate changing functions. The underlying mechanism carrier concentration mobility on device's electrical performance revealed as well. Short‐term behaviors including paired‐pulse facilitation, spike duration‐dependent plasticity, dynamic filtering tuned this fiber‐based device. Furthermore, Perovskite‐doped devices ultralow energy consumption down ≈0.2554 fJ their handwritten recognition application show great potential based a nanostructure active layer building next‐generation networks.