神经形态工程学
晶体管
材料科学
神经科学
计算机科学
电压
突触可塑性
可塑性
光电子学
电子工程
电气工程
化学
人工神经网络
工程类
人工智能
生物
复合材料
生物化学
受体
作者
Pengfei Chen,Wei Dou,XU Xiao-dong,Yuling Peng,Jiangyun Lei,G. C. Jiang,Guangxiu Zeng,Dongsheng Tang
摘要
This study demonstrates the integrated junctionless indium-tin-oxide transistor arrays for neuromorphic computing, exhibiting remarkable stability and consistency. Stable and dynamic synaptic plasticity is demonstrated by these devices, with both paired pulse facilitation (PPF) and paired pulse depression (PPD) being achieved within a single device. Through the modulation of synaptic weights, the dynamic conversion from PPD to PPF can be realized, thereby enabling multimodal learning and reducing the complexity of the neuromorphic system. The unique ion migration mechanism of chitosan electrolytes enables short-term plasticity and pulse-number-dependent weight modulation. Utilizing these properties, a feedback-enhanced learning model was constructed to emulate spatiotemporal integration of neural signals. The array exhibits excellent scalability, offering a cost-effective solution for large-scale neuromorphic systems. Notably, the controllable switch between inhibition and potentiation modes represents a demonstrated capability in artificial synapse design, holding promise for bioelectronic devices and adaptive sensing applications.
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