8-bit states in 2D floating-gate memories using gate-injection mode for large-scale convolutional neural networks

Yuchen Cai, Jia Yang, Yutang Hou, Feng Wang (), Lei Yin, Shuhui Li, Yanrong Wang, Tao Yan, Shan Yan, Xueying Zhan, Jun He and Zhenxing Wang ()
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Yuchen Cai: National Center for Nanoscience and Technology
Jia Yang: National Center for Nanoscience and Technology
Yutang Hou: Wuhan University
Feng Wang: National Center for Nanoscience and Technology
Lei Yin: Wuhan University
Shuhui Li: National Center for Nanoscience and Technology
Yanrong Wang: Henan Academy of Sciences
Tao Yan: National Center for Nanoscience and Technology
Shan Yan: National Center for Nanoscience and Technology
Xueying Zhan: National Center for Nanoscience and Technology
Jun He: Wuhan University
Zhenxing Wang: National Center for Nanoscience and Technology

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract The fast development of artificial intelligence has called for high-efficiency neuromorphic computing hardware. While two-dimensional floating-gate memories show promise, their limited state numbers and stability hinder practical use. Here, we report gate-injection-mode two-dimensional floating-gate memories as a candidate for large-scale neural network accelerators. Through a coplanar device structure design and a bi-pulse state programming strategy, 8-bit states with intervals larger than three times of the standard deviations and stability over 10,000 s are achieved at 3 V. The cycling endurance is over 105 and the fabricated 256 devices show a yield of 94.9%. Leveraging this, we carry out experimental image convolutions and 38,592 kernels transplanting on an integrated 9 × 2 array that exhibits results matching well with simulations. We also show that fix-point neural networks with 8-bit precision have inference accuracies approaching the ideal values. Our work validates the potential of gate-injection-mode two-dimensional floating-gate memories for high-efficiency neuromorphic computing hardware.

Date: 2025
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DOI: 10.1038/s41467-025-58005-z

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