一种基于高线性和多层聚合物的导电桥接memristor用于人工突触
Jianhong Zhou1, Zheng Wang1, Yujun Fu1
1School of Materials and Energy, Lanzhou University, Lanzhou 730000, China. wangqi77@lzu.edu.cn.
Nanoscale
|August 4, 2023
概括
这项研究引入了一种基于基托桑的新型碳氧化记忆器,并添加了PEDOT:PSS用于神经形态计算. 增强的设备显示了对导电丝的改进控制,使线性导电性调节和高识别精度的人工突触.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术 纳米技术
- 神经科学是一个神经科学.
背景情况:
- 导电桥梁记忆器在突触应用中利用金属离子氧化还原反应.
- 无法控制的金属离子迁移会导致随机的光线形成和电导控制不良.
研究的目的:
- 开发一种基于基托桑的碳氧化记忆器,具有增强的离子导电性和调节的金属离子氧化还原.
- 为了提高人工突触的金属离子基记忆器的性能.
主要方法:
- 用PEDOT:PSS对碳氧化奇托进行兴奋剂,以创建一种新型的memristor材料.
- 调查该设备的导电丝的形成和导电性状态.
- 模拟手写数字数据集,以提高模式识别的准确性.
主要成果:
- 碳氧化酸添加的PEDOT:PSS记忆器表现出均的导电纤维.
- 通过线性调节,在~1V范围内达到100多个非挥发性导电状态.
- 在手写数字数据集上表现出93%的识别准确度.
结论:
- 开发的memristor为高性能人工突触提供了一个可行的途径.
- 改善对金属离子迁移的控制提高了memristor的可靠性和功能.
- 这种材料创新推进了神经形态计算能力.
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