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11位二维浮动门的记忆
Yanrong Wang1, Yuchen Cai2,3, Feng Wang4,5
1Institute of Semiconductor, Henan Academy of Sciences, Zhengzhou, P. R. China.
Nature communications
|October 20, 2025
概括
我们开发了11位二维 (2D) MoS2浮动门记忆 (FGM) 用于神经形态计算. 这些设备提供高状态容量和低噪声,推进高效的以数据为中心的应用.
科学领域:
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
- 计算机科学 计算机科学
背景情况:
- 浮式门记忆 (FGM) 对于高效的神经形态计算至关重要.
- 有限的单个设备状态容量阻碍了精密计算应用.
研究的目的:
- 通过使用MoS2.2,演示高位容量的2D FGM.
- 为了提高神经形态硬件的FGM性能.
主要方法:
- 使用双 bismuth 电极制造 2D MoS2 FGM.
- 为了稳定性,使用双脉冲状态编辑方案.
- 描述设备性能,包括状态级别,速度,保留和耐久性.
主要成果:
- 实现了11位分辨率 (2249个级别),100μA的启动电流和10^8的开/关比.
- 由于Schottky无障碍接口,电流噪声减少了3倍.
- 经过证明的230ns运行速度,>10^4s保留,>10^5周期耐用性,在85°C时稳定低噪声.
结论:
- 2D MoS2 FGMs与珠电极显示出高位密度,低功耗神经形态硬件的前景.
- 接口缺陷限制状态容量,具有17位分辨率的潜力.
- 门注射操作确保低噪音和稳定性在延长循环.
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