Optically driven intelligent computing with ZnO memristor

神经形态工程学 记忆电阻器 计算机科学 材料科学 钥匙(锁) 非常规计算 光学计算 人工神经网络 人工智能 电子工程 分布式计算 工程类 计算机安全
作者
Jing Yang,Lili Hu,Liufeng Shen,Jian Wang,Peihong Cheng,Hongda Lu,Fei Zhuge,Zhizhen Ye
出处
期刊:Fundamental research [Elsevier]
被引量:12
标识
DOI:10.1016/j.fmre.2022.06.019
摘要

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 candidates 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.
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