首页|Optically driven intelligent computing with ZnO memristor

Optically driven intelligent computing with ZnO memristor

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Artificial vision is crucial for most artificial intelligence applications.Conventional artificial visual systems have been facing challenges in terms of real-time information processing due to the physical separation of sensors,memories,and processors,which results in the production of a large amount of redundant data as well as the data conversion and transfer between these three components consuming most of the time and energy.Emergent optoelectronic memristors with the ability to realize integrated sensing-computing-memory(ISCM)are key can-didates for solving such challenges and therefore attract increasing attention.At present,the memristive ISCM devices can only perform primary-level computing with external light signals due to the fact that only monotonic increase of memconductance upon light irradiation is achieved in most of these devices.Here,we propose an all-optically controlled memristive ISCM device based on a simple structure of Au/ZnO/Pt with the ZnO thin film sputtered at pure Ar atmosphere.This device can perform advanced computing tasks such as nonvolatile neuromorphic computing and complete Boolean logic functions only by light irradiation,owing to its ability to reversibly tune the memconductance with light.Moreover,the device shows excellent operation stability ascribed to a purely electronic memconductance tuning mechanism.Hence,this study is an important step towards the next generation of artificial visual systems.

MemristorAll-optically controllingZnO thin filmArtificial visionNonvolatile neuromorphic computingLogic-in-memory

Jing Yang、Lingxiang Hu、Liufeng Shen、Jingrui Wang、Peihong Cheng、Huanming Lu、Fei Zhuge、Zhizhen Ye

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Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences,Ningbo 315201,China

Center of Materials Science and Optoelectronics Engineering,University of Chinese Academy of Sciences,Beijing 100029,China

Center for Excellence in Brain Science and Intelligence Technology,Chinese Academy of Sciences,Shanghai 200072,China

Institute of Wenzhou,Zhejiang University,Wenzhou 325006,China

State Key Laboratory of Silicon Materials,School of Materials Science and Engineering,Zhejiang University,Hangzhou 310027,China

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国家自然科学基金国家自然科学基金中国科学院战略规划重点项目浙江省自然科学基金浙江省自然科学基金State Key Laboratory of Silicon Materials

U20A2020961874125XDB32050204LD19E020001LQ22F040003SKL2021-03

2024

自然科学基础研究(英文)

自然科学基础研究(英文)

CSTPCD
ISSN:
年,卷(期):2024.(1)
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