PbS Quantum Dot-Based Optoelectronic Memristors toward Multi-Task Reservoir Computing

The rise of big data and the internet of things has driven the demand for multimodal sensing and high-efficiency low-latency processing. Inspired by the human sensory system, we present a multifunctional optoelectronic-memristor-based reservoir computing (OM-RC) system by utilizing a CuSCN/PbS quantum dots (QDs) heterojunction. The OM-RC system exhibits volatile and nonlinear responses to electrical signals and wide-spectrum optical stimuli covering ultraviolet, visible, and near-infrared (NIR) regions, enabling multitask processing of dynamic signals. The OM-RC system accurately performs health monitoring through dynamic electroencephalogram and electrocardiogram signal analysis and achieves object and traffic trajectory recognition for intelligent driving under challenging conditions like foggy environments. By collaboratively using the NIR perception and trajectory recognition, we develop a human-computer interaction authentication system that integrates finger veins and motion behaviors of humans, significantly enhancing the security of traditional fingerprint anticounterfeiting systems. This work demonstrates the potential of QD-based optoelectronic-memristor for multitask in-sensor processing applications.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2024-12-23
DOI
https://doi.org/10.1021/acs.jpclett.4c03350
Citations
9
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.88

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PbS Quantum Dot-Based Optoelectronic Memristors toward Multi-Task Reservoir Computing

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9 citations
The Journal of Physical Chemistry Letters
Advanced Memory and Neural Computing
1.88
article

PbS Quantum Dot-Based Optoelectronic Memristors toward Multi-Task Reservoir Computing

Yi Zhao, Deli Li, Liangxu Lin, Jiayu Sun, Yue Wang, Yang Liu, Fushan Li, Jiasong Lin, Xuan Guo, Qinghong Lin, Zhen Wang
article en
9 citations

Abstract

The rise of big data and the internet of things has driven the demand for multimodal sensing and high-efficiency low-latency processing. Inspired by the human sensory system, we present a multifunctional optoelectronic-memristor-based reservoir computing (OM-RC) system by utilizing a CuSCN/PbS quantum dots (QDs) heterojunction. The OM-RC system exhibits volatile and nonlinear responses to electrical signals and wide-spectrum optical stimuli covering ultraviolet, visible, and near-infrared (NIR) regions, enabling multitask processing of dynamic signals. The OM-RC system accurately performs health monitoring through dynamic electroencephalogram and electrocardiogram signal analysis and achieves object and traffic trajectory recognition for intelligent driving under challenging conditions like foggy environments. By collaboratively using the NIR perception and trajectory recognition, we develop a human-computer interaction authentication system that integrates finger veins and motion behaviors of humans, significantly enhancing the security of traditional fingerprint anticounterfeiting systems. This work demonstrates the potential of QD-based optoelectronic-memristor for multitask in-sensor processing applications.

The Journal of Physical Chemistry LettersVol. 16(1)
Fujian Normal University (CN), Fuzhou University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province, Fujian Normal University
Affordable and clean energy
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.88
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