神经形态工程学
材料科学
钙钛矿(结构)
量子点
碳纳米管
光子学
光电子学
纳米技术
记忆电阻器
冯·诺依曼建筑
电子工程
计算机科学
人工神经网络
化学工程
人工智能
操作系统
工程类
作者
Jinxin Li,Priyanka Dwivedi,Kowsik Sambath Kumar,Tania Roy,Kaitlyn E. Crawford,Jayan Thomas
标识
DOI:10.1002/aelm.202000535
摘要
Abstract Brain‐inspired (neuromorphic) computing that offers lower energy consumption and parallelism (simultaneous processing and memorizing) compared to von Neumann computing provides excellent opportunities in many computational tasks ranging from image recognition to speech processing. To accomplish neuromorphic computing, highly efficient optoelectronic synapses, which can be the building blocks of optoelectronic neuromorphic computers, are necessary. Currently, carbon nanotubes (CNTs), an attractive candidate to develop circuit‐level photonic synapses, provide weak light responses. The inferior photoresponse of CNTs increases the energy consumption of neuromorphic optoelectronic devices. Herein, a method to grow organic–inorganic halide perovskite quantum dots (PQDs) directly on multiwall CNTs (MWCNTs) to increase the photosensitivity of optoelectronic synapses is demonstrated. The new hybrid material synchronizes the high photoresponse of PQDs and the excellent electrical properties of MWCNTs to provide photonic memory under very low light intensity (125 µW cm −2 ). However, neat MWCNTs do not show any detectable light response at the tested light intensity, as high as 25 mW cm −2 . Since the PQDs are grown directly on and in the MWCNTs, the hybrid PQD‐MWCNT provides a new direction for the future MWCNT‐based optoelectronic devices for neuromorphic computing with a potential to break the von Neumann bottleneck.
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