摘要
Carbon quantum dots (CQDs) have been used in memristors due to their attractive optical and electronic properties, which are considered candidates for brain-inspired computing devices. In this work, the performance of CQDs-based memristors is improved by utilizing nitrogen-doping. In contrast, nitrogen-doped CQDs (N-CQDs)-based optoelectronic memristors can be driven with smaller programming voltages (−0.6 to 0.7 V) and exhibit lower powers (78 nW/0.29 µW). The physical mechanism can be attributed to the reversible transition between C–N and C=N with lower binding energy induced by the electric field and the generation of photogenerated carriers by ultraviolet light irradiation, which adjusts the conductivity of the initial N-CQDs to implement resistance switching. Importantly, the convolutional image processing based on various cross kernels is efficiently demonstrated by stable multi-level storage properties. An N-CQDs-based optoelectronic reservoir computing implements impressively high accuracy in both no noise and various noise modes when recognizing the Modified National Institute of Standards and Technology (MNIST) dataset. It illustrates that N-CQDs-based memristors provide a novel strategy for developing artificial vision system with integrated in-memory sensor and computing.
基金
financially supported by the National Key Research and Development Program of China(No.2022YFE0139100)
International cooperative research project of Jiangsu province(No.BZ2022008)
the National Natural Science Foundation Project of China(No.62175028)
Program 111_2.0 in China(No.BP0719013)
Leading Technology of Jiangsu Basic Research Plan(No.BK20192003)
Postgraduate Research & Practice Innovation Program of Jiangsu Province,the Fundamental Research Funds for the Central Universities(No.KYCX23_0254).
