材料科学
神经形态工程学
晶体管
瓶颈
人工神经网络
深度学习
光电子学
人工智能
钙钛矿(结构)
纳米技术
电子工程
电气工程
计算机科学
嵌入式系统
化学工程
工程类
电压
作者
Ruizhi Wang,Pengyue Chen,Dandan Hao,Junyao Zhang,Qianqian Shi,Dapeng Liu,Li Li,Lize Xiong,Junhe Zhou,Jia Huang
标识
DOI:10.1021/acsami.1c08424
摘要
Synaptic devices are expected to overcome von Neumann’s bottleneck and served as one of the foundations for future neuromorphic computing. Lead halide perovskites are considered as promising photoactive materials but limited by the toxicity of lead. Herein, lead-free perovskite CsBi3I10 is utilized as a photoactive material to fabricate organic synaptic transistors with a floating-gate structure for the first time. The devices can maintain the Ilight/Idark ratio of 103 for 4 h and have excellent stability within the 30 days test even without encapsulation. Synaptic functions are successfully simulated. Notably, by combining the decent charge transport property of the organic semiconductor and the excellent photoelectronic property of CsBi3I10, synaptic performance can be realized even with an operating voltage as low as −0.01 V, which is rare among floating-gate synaptic transistors. Furthermore, artificial neural networks are constructed. We propose a new method that can simulate the synaptic weight value in multiple digit form to achieve complete gradient descent. The image recognition test exhibits thrilling recognition accuracy for both supervised (91%) and unsupervised (81%) classifications. These results demonstrate the great potential of floating-gate organic synaptic transistors in neuromorphic computing.
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