Reconfigurable Selector-Free All-Optical Controlled Neuromorphic Memristor for In-Memory Sensing and Reservoir Computing

Recently, the rising demand for data-based applications has driven the convergence of image sensing, memory, and computing unit interfaces. While specialized electronic hardware has spurred advancements in the in-memory and in-sensor computing, integrating the entire signal-processing chain into a single device still faces significant challenges. Here, a reconfigurable all-optical controlled memristor with the selector-free feature is demonstrated. The conductance of the device can be controlled within the pure light domain, which enables it to integrate sensing, memory, and computing together. The integrate-and-fire behavior is also realized through electrical stimuli. Furthermore, the device exhibits an excellent rectifying ratio and nonlinearity to overcome the sneak current. Finally, an in-memory sensing and computing architecture is realized through reservoir computing based on neuron and synaptic functions mimicked by the proposed device. Such an all-in-one paradigm facilitates the computing architecture with low energy consumption, low latency, and reduced hardware complexity.

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Publication Details

Journal
ACS Nano
Published
2024-10-17
DOI
https://doi.org/10.1021/acsnano.4c09199
Citations
22
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
4.59

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article

Reconfigurable Selector-Free All-Optical Controlled Neuromorphic Memristor for In-Memory Sensing and Reservoir Computing

Hao Zhu, Lu Chen, David Wei Zhang, Tianyu Wang et al.
22 citations
ACS Nano
Advanced Memory and Neural Computing
4.59
article

Reconfigurable Selector-Free All-Optical Controlled Neuromorphic Memristor for In-Memory Sensing and Reservoir Computing

Hao Zhu, Lu Chen, David Wei Zhang, Tianyu Wang, Qingqing Sun, Lin Chen, Jialin Meng, Jieru Song, Kangli Xu
article en
22 citations

Abstract

Recently, the rising demand for data-based applications has driven the convergence of image sensing, memory, and computing unit interfaces. While specialized electronic hardware has spurred advancements in the in-memory and in-sensor computing, integrating the entire signal-processing chain into a single device still faces significant challenges. Here, a reconfigurable all-optical controlled memristor with the selector-free feature is demonstrated. The conductance of the device can be controlled within the pure light domain, which enables it to integrate sensing, memory, and computing together. The integrate-and-fire behavior is also realized through electrical stimuli. Furthermore, the device exhibits an excellent rectifying ratio and nonlinearity to overcome the sneak current. Finally, an in-memory sensing and computing architecture is realized through reservoir computing based on neuron and synaptic functions mimicked by the proposed device. Such an all-in-one paradigm facilitates the computing architecture with low energy consumption, low latency, and reduced hardware complexity.

ACS NanoVol. 18(43)
Shandong University (CN), Fudan University (CN), Shanghai Innovative Research Center of Traditional Chinese Medicine (CN), Shanghai Fudan Microelectronics (China) (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Science and Technology Commission of Shanghai Municipality, Natural Science Foundation of Shandong Province, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 5%
Advanced Memory and Neural Computing
4.59
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