GeO 2 /SiO 2 /p‐Si Heterojunction Optoelectronic Memristors: A Multifunctional Platform for Solar‐Blind UV Detection and Neuromorphic Recognition

ABSTRACT Optoelectronic memristors with sensing, storage, and computing multifunctional applications are promising for efficient in‐memory computing and intelligent visual perception. However, it is still a huge challenge to integrate these functions in a single optoelectronic platform due to the inherent contradiction between the volatile photoresponse of photodetectors and the persistent photoconductivity of memristors. Here, multifunctional optoelectronic memristors (MOMs) based on vertical GeO 2 /SiO 2 /p‐Si heterojunctions have been successfully developed with the integration of 213‐nm solar‐blind UV photodetection and artificial synaptic functionality. The GeO 2 MOM exhibits an ultralow dark current of 3 pA and a photo‐dark current ratio over 10 3 in self‐powered mode, and decreases in fast rise and decay times by more than 40‐fold and 13‐fold at an applied bias voltage of −0.7 V, enabling solar‐blind optical communication and reconfigurable optoelectronic logic gate applications. Moreover, it demonstrates stable bipolar resistive switching with a high‐to‐low resistance ratio exceeding 35 under electric field stimulation and emulates five‐dimensional synaptic plasticity under optical pulse stimulation, with which handwritten digit image recognition has been realized with a high accuracy of 96.98%. This work designs an excellent multifunctional platform and provides a versatile strategy for the development of high‐performance GeO 2 optoelectronic devices.

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Publication Details

Journal
Advanced Optical Materials
Published
2026-09-29
DOI
https://doi.org/10.1002/adom.71887
Primary Topic
Advanced Memory and Neural Computing
Type
article
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GeO 2 /SiO 2 /p‐Si Heterojunction Optoelectronic Memristors: A Multifunctional Platform for Solar‐Blind UV Detection and Neuromorphic Recognition

Suhua Zang, Gang Wang, Xu Wang, Qixin Guo et al.
Advanced Optical Materials
Advanced Memory and Neural Computing
article

GeO 2 /SiO 2 /p‐Si Heterojunction Optoelectronic Memristors: A Multifunctional Platform for Solar‐Blind UV Detection and Neuromorphic Recognition

Suhua Zang, Gang Wang, Xu Wang, Qixin Guo, Ziyang Hu, Dongdong Meng, Hao Wu, Siying Hu, Xingyu Liu, Zhengwei Chen, Hongxiang Zhou, Yuxi Wang, Ziyu Li, Yang Chen
article en

Abstract

ABSTRACT Optoelectronic memristors with sensing, storage, and computing multifunctional applications are promising for efficient in‐memory computing and intelligent visual perception. However, it is still a huge challenge to integrate these functions in a single optoelectronic platform due to the inherent contradiction between the volatile photoresponse of photodetectors and the persistent photoconductivity of memristors. Here, multifunctional optoelectronic memristors (MOMs) based on vertical GeO 2 /SiO 2 /p‐Si heterojunctions have been successfully developed with the integration of 213‐nm solar‐blind UV photodetection and artificial synaptic functionality. The GeO 2 MOM exhibits an ultralow dark current of 3 pA and a photo‐dark current ratio over 10 3 in self‐powered mode, and decreases in fast rise and decay times by more than 40‐fold and 13‐fold at an applied bias voltage of −0.7 V, enabling solar‐blind optical communication and reconfigurable optoelectronic logic gate applications. Moreover, it demonstrates stable bipolar resistive switching with a high‐to‐low resistance ratio exceeding 35 under electric field stimulation and emulates five‐dimensional synaptic plasticity under optical pulse stimulation, with which handwritten digit image recognition has been realized with a high accuracy of 96.98%. This work designs an excellent multifunctional platform and provides a versatile strategy for the development of high‐performance GeO 2 optoelectronic devices.

Advanced Optical Materials
Ningbo University (CN), Beijing University of Posts and Telecommunications (CN), Ningbo University of Technology (CN), Saga University (JP)
Affordable and clean energy
Openalex Percentile: Top 22%
Advanced Memory and Neural Computing
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