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A high-speed 2D optoelectronic in-memory computing device with 6-bit storage and pattern recognition capabilities

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Abstract

The explosively developed era of big-data compels the increasing demand of nonvolatile memory with high efficiency and excellent storage properties. Herein, we fabricated a high-speed photoelectric multilevel memory device for neuromorphic computing. The novel two-dimensional (2D) MoSSe with a unique Janus structure was employed as the channel, and the stack of Al2O3/black phosphorus quantum dots (BPQDs)/Al2O3 was adopted as the dielectric. The storage performance of the resulting memory could be verified by the endurance and retention tests, in which the device could remain stable states of programming and erasing even after 1, 000 cycles and 1, 000 s. The multibit storage could be realized through both different voltage amplitudes and pulse numbers, which could achieve 6 bits (64 distinguishable levels) under pulse width of 50 ns. Furthermore, our memory device also could realize the simulations of synapses in human brain with optical and electric modulations synergistically, such as excitatory post-synaptic current (EPSC), long-term potentiation/depression (LTP/LTD), and spike-timing-dependent plasticity (STDP). Neuromorphic computing was successfully achieved through a high recognition of handwritten digits up to 92.5% after 103 epochs. This research is a promising avenue for the future development of efficient memory and artificial neural network systems.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) (Nos. 92064009, 61904033, and 62004044), Shanghai Rising-Star Program (No. 19QA1400600), the Program of Shanghai Subject Chief Scientist (No. 18XD1402800), the Support Plans for the Youth Top-Notch Talents of China, and the National Postdoctoral Program for Innovative Talents (No. BX2021070).

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Correspondence to Lin Chen or Qingqing Sun.

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Meng, J., Wang, T., He, Z. et al. A high-speed 2D optoelectronic in-memory computing device with 6-bit storage and pattern recognition capabilities. Nano Res. 15, 2472–2478 (2022). https://doi.org/10.1007/s12274-021-3729-9

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