高速度和低能耗电阻开关与二维酸三硫化物用于高效的神经形态计算
Yun Ji1, Baoshan Tang1, Jinyong Wang1
1Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore.
ACS nano
|December 31, 2024
概括
双维三硫化 (CoPS3) 记忆体为神经形态计算提供快速,低能量的切换. 这些材料可以实现高精度的人工神经网络和可扩展的集成,用于未来的电子电路.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术 纳米技术
- 计算机工程 计算机工程
背景情况:
- 由于其电气和机械性能,二维 (2D) 材料对神经形态计算具有前景.
- 实施二维记忆器在平衡低延迟和低能耗方面面临挑战.
研究的目的:
- 为了展示基于二维二硫化 (CoPS3) 的记忆器,用于神经形态应用.
- 实现高性能指标,包括速度,能源效率和可靠性.
主要方法:
- 制造 CoPS3 记忆体.
- 电成型工艺,以创建硫空隙和导电纤维.
- 切换速度,能源消耗,切换比率和电压要求的描述.
- 电导度调制线性和记忆保留的评估.
- 在人工神经网络模型中测试手写数字识别和图像处理.
主要成果:
- CoPS3 记忆元具有高开关速度 (20 ns) 和低开关能量 (1.15 pJ).
- 实现了高开关比率 (>400) 和低开关电压 (1.05V设置, -0.89V重置).
- 证明了线性导电度调制,长期记忆保留,以及在神经网络模型中的成功应用.
- 在溶液加工的大型CoPS3膜中观察到强大的切换.
结论:
- 2D CoPS3 材料显示了节能神经形态计算电路的巨大潜力.
- 开发的memristor提供了快速切换,低能耗和可扩展性的组合.
- 解决方案处理的CoPS3薄膜可以实现晶圆尺度,低温集成,用于先进的计算架构.
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