神经形态工程学
材料科学
计算机科学
晶体管
记忆电阻器
光电子学
纳米技术
计算机体系结构
人工神经网络
电子工程
电压
人工智能
电气工程
工程类
作者
Dapeng Liu,Qianqian Shi,Junyao Zhang,Tian Li,Lize Xiong,Shilei Dai,Jia Huang
标识
DOI:10.1002/aisy.202200164
摘要
2D metal–organic frameworks (2D‐MOFs) have been extensively studied as promising materials in the fields of electrocatalysis, drug delivery, electronic devices, etc. However, few studies have explored the application potential of 2D‐MOFs in novel neuromorphic computing devices. Herein, an optoelectronic neuromorphic transistor based on a 2D‐MOF/polymer charge‐trapping layer is reported. It is found that the large specific surface area, stable crystal structure, and highly accessible active sites in 2D‐MOFs make them excellent charge‐trapping materials for the devices, which are beneficial for mimicking the memory and learning functions observed in the organism's nervous systems. Different types of synaptic behaviors have been realized in the 2D‐MOF‐based neuromorphic devices under stimuli signal, e.g., paired‐pulse facilitation, excitatory postsynaptic current, short‐term memory, and long‐term memory. More interestingly, emotion‐adjustable learning behavior is realized by changing the value of the source–drain voltage. This work can shed light on the application of 2D‐MOFs in neuromorphic computing and will contribute to the further development of neuromorphic computing devices. An interactive preprint version of the article can be found at DOI: https://doi.org/10.22541/au.165530836.62586068/v1 .
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