在电化学石墨烯晶体管中的门控制的神经形态功能转换
Chenglin Yu1, Shaorui Li1, Zhoujie Pan2
1State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China.
Nano letters
|January 26, 2024
概括
研究人员开发了可作为人工神经元或突触的石墨烯晶体管. 神经形态计算的这一突破使得自适应神经网络能够用于先进的人工智能和机器学习应用.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
背景情况:
- 神经形态设备模拟生物神经系统,用于下一代计算.
- 人工神经元和突触是神经网络的关键组成部分.
- 当前的实现通常需要为每个功能提供专用设备.
研究的目的:
- 提出一种单层石墨烯晶体管,能够在神经形态函数之间切换.
- 为了展示人工神经元和突触功能之间的门控制过渡.
- 为了利用可逆的电化学反应来实现可靠的设备操作.
主要方法:
- 使用的单层石墨烯晶体管.
- 使用门控制的电化学反应,涉及碳原子和离子.
- 操纵了石墨烯晶体管的电导率.
主要成果:
- 在单一设备中实现了神经模拟功能 (神经元/突触) 的按需切换.
- 展示了高的开/关电阻比率和明确的设置/重置电压.
- 显示了晶体管状态的延长保留时间.
结论:
- 单个石墨烯晶体管可以作为memetransistors和突触晶体管发挥作用.
- 这项技术为开发自适应神经网络提供了一个有前途的途径.
- 实现了人工智能和机器学习方面的进步.
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