神经形态工程学
材料科学
光电子学
铟
光电效应
晶体管
可塑性
薄膜晶体管
纳米技术
计算机科学
电压
图层(电子)
电气工程
人工神经网络
人工智能
工程类
复合材料
作者
Yixin Zhu,Baocheng Peng,Li Zhu,Chunsheng Chen,Xiangjing Wang,Huiwu Mao,Ying Zhu,Chuanyu Fu,Shuo Ke,Changjin Wan,Qing Wan
摘要
Synaptic plasticity divided into long-term and short-term categories is regarded as the origin of memory and learning, which also inspires the construction of neuromorphic systems. However, it is difficult to mimic the two behaviors monolithically, which is due to the lack of time-tailoring approaches for a certain synaptic device. In this Letter, indium-gallium-zinc-oxide (IGZO) nanofiber-based photoelectric transistors are proposed for realizing tunable photoelectric synaptic plasticity by the indium composition ratio. Notably, short-term plasticity to long-term plasticity transition can be realized by increasing the ratio of indium in the IGZO channel layer. The spatiotemporal dynamic logic and low energy consumption (<100 fJ/spike) are obtained in devices with low indium ratio. Moreover, the symmetric spike-timing-dependent plasticity is achieved by exploiting customized light and electric pulse schemes. Photoelectric long-term plasticity, multi-level characteristics, and high recognition accuracy (93.5%) are emulated in devices with high indium ratio. Our results indicate that such a composition ratio modulated method could enrich the applications of IGZO nanofiber neuromorphic transistors toward the photoelectric neuromorphic systems.
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