High‐Endurance STO:YSZ Optoelectronic Memristors with Vertically Aligned Nanocomposite Structure for Edge Detection

Edge detection plays a critical role in cutting-edge domains such as real-time monitoring and automatic driving, with optoelectronic device-based real-time image processing garnering significant attention. However, the poor endurance and unstable optical responsivity of conventional optoelectronic memristors constrain their application in highly integrated edge detection systems. In this study, a silicon-based integrated optoelectronic memristor based on SrTiO<sub>3</sub>:(Y<sub>2</sub>O<sub>3</sub>:ZrO<sub>2</sub>) (STO:YSZ) vertically aligned nanocomposite (VAN) structure is introduced, where the conductive channels at the spatial vertical interface providing an effective transport pathway. The device achieves excellent endurance (10<sup>8</sup> switching cycles) and stable multi-band (405-650 nm) optical switching. Additionally, it also exhibits the ability of simulating biological synaptic plasticity, implementing optical image extraction and ASCII code transmission. Importantly, edge detection of real-time road vehicle imagery is demonstrated via an optoelectronic memristor network. This work opens a promising paradigm for developing stable and high endurance machine vision systems based on optoelectronic memristor.

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Publication Details

Journal
Advanced Science
Published
2025-11-06
DOI
https://doi.org/10.1002/advs.202513646
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

High‐Endurance STO:YSZ Optoelectronic Memristors with Vertically Aligned Nanocomposite Structure for Edge Detection

Haoning Liu, Jikang Xu, Xiaobing Yan, Weidong Sun et al.
2 citations
Advanced Science
Advanced Memory and Neural Computing
1.46
article

High‐Endurance STO:YSZ Optoelectronic Memristors with Vertically Aligned Nanocomposite Structure for Edge Detection

Haoning Liu, Jikang Xu, Xiaobing Yan, Weidong Sun, Hong Wang, Jiacheng Wang, Biao Yang, Zhen Zhao, Fu Wang, Xu Han, Yufei Shang, Kangbo Zhao
article en
2 citations

Abstract

Edge detection plays a critical role in cutting-edge domains such as real-time monitoring and automatic driving, with optoelectronic device-based real-time image processing garnering significant attention. However, the poor endurance and unstable optical responsivity of conventional optoelectronic memristors constrain their application in highly integrated edge detection systems. In this study, a silicon-based integrated optoelectronic memristor based on SrTiO<sub>3</sub>:(Y<sub>2</sub>O<sub>3</sub>:ZrO<sub>2</sub>) (STO:YSZ) vertically aligned nanocomposite (VAN) structure is introduced, where the conductive channels at the spatial vertical interface providing an effective transport pathway. The device achieves excellent endurance (10<sup>8</sup> switching cycles) and stable multi-band (405-650 nm) optical switching. Additionally, it also exhibits the ability of simulating biological synaptic plasticity, implementing optical image extraction and ASCII code transmission. Importantly, edge detection of real-time road vehicle imagery is demonstrated via an optoelectronic memristor network. This work opens a promising paradigm for developing stable and high endurance machine vision systems based on optoelectronic memristor.

Advanced ScienceVol. 13(1)
Hebei University (CN)
Openalex Percentile: Top 15%
Advanced Memory and Neural Computing
1.46
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