11-bit two-dimensional floating-gate memories

Yanrong Wang, Yuchen Cai, Feng Wang (), Tao Yan, Shuhui Li, Mingyang Cao, Ruohao Hong, Baoxing Zhai, Kai Xu, Xueying Zhan, Jun He and Zhenxing Wang ()
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Yanrong Wang: Henan Academy of Sciences
Yuchen Cai: National Center for Nanoscience and Technology
Feng Wang: National Center for Nanoscience and Technology
Tao Yan: University of Chinese Academy of Sciences
Shuhui Li: National Center for Nanoscience and Technology
Mingyang Cao: Henan Academy of Sciences
Ruohao Hong: Henan Academy of Sciences
Baoxing Zhai: Henan Academy of Sciences
Kai Xu: Zhejiang University
Xueying Zhan: National Center for Nanoscience and Technology
Jun He: Henan Academy of Sciences
Zhenxing Wang: National Center for Nanoscience and Technology

Nature Communications, 2025, vol. 16, issue 1, 1-9

Abstract: Abstract Floating-gate memories (FGMs) show great promise for neuromorphic computing in efficient data-centric applications. However, their limited single-device state capacity remains insufficient for highly integrated precision computing. Here, we demonstrate 11-bit two-dimensional (2D) MoS2 FGMs by contacting the 2D channels with bismuth electrodes, enabling 100 μA on-state current with 108 on/off ratio and reducing the current noise by 3 times (approaching the equipment limits) due to the Schottky barrier-free interfaces. Moreover, we employed a dual-pulse state editing scheme enhancing the stability of our FGMs. The devices show as high as 2,249 distinct conductance levels (>11-bit) while maintaining 230 ns operation speed, >104 s retention, and >105 cycle endurance. Furthermore, the gate-injection operation prevents the influence from generated defects during cycling, maintaining low noise even after 105 cycles and at 85 °C. Theoretical analysis reveals interfacial defects as the primary state-number limitation, suggesting 17-bit capacity is achievable through further trap density reduction. This work establishes 2D FGMs as promising candidates for high-bit-density, low-power neuromorphic hardware.

Date: 2025
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DOI: 10.1038/s41467-025-64333-x

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