在神经形态记忆器中增强稳定性和代学习通过TiN/SiO/TiN接口工程
Hyun Kyu Seo1,2, Jae-Seung Jeong2, Jaeho Jung3
1Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea.
Nanoscale
|April 9, 2025
概括
我们开发了基于SiO2的先进电阻随机存储器 (ReRAM) 设备,功耗低,线性高. 这些设备在神经形态应用中实现了出色的性能,包括精确的MNIST数字识别.
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:
- 电阻随机访问存储器 (ReRAM) 是下一代计算的一个有前途的技术.
- 接口类型的ReRAM设备提供了高性能和低功耗的潜力.
- 神经形态计算需要高效和稳定的突触装置.
研究的目的:
- 为了制造和描述基于SiO2的接口类型ReRAM设备.
- 为了评估这些设备用于神经形态应用的性能,特别是MNIST数字识别.
- 研究耐久性和材料选择对突触装置性能的影响.
主要方法:
- 制造TiN/SiO2/TiN和Pt/SiO2/Pt ReRAM设备. 这些设备包括:
- 电气表征包括I-V曲线,耐久性测试和保留测量.
- 对神经形态学习的设备线性和突触重量降解的评估.
主要成果:
- 设备运行在3V以下,电流<1mA,实现启/关比为~10.
- 演示了快速切换速度 (1μs设置/重置) 和良好的保留 (10^4s在85°C).
- 高线性使MNIST识别的准确度达到92.21%;TiN/SiO2/TiN由于有氧储存器,显示出更高的耐久性.
结论:
- 基于SiO2的接口类型ReRAM设备在神经形态计算方面表现出色.
- TiN/SiO2/TiN结构提供了增强的耐久性和稳定性,对于突触应用至关重要.
- 渐进的切换动态和设备的稳定性有助于神经形态系统的高效学习.
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