电阻随机存取存储器
噪音(视频)
材料科学
价(化学)
神经形态工程学
热传导
概率逻辑
计算机科学
过度拟合
记忆电阻器
光电子学
物理
人工智能
电极
量子力学
人工神经网络
图像(数学)
复合材料
作者
Kristoffer Schnieders,Carsten Funck,Felix Cüppers,Stephan Aussen,Tim Kempen,Alexandros Sarantopoulos,Regina Dittmann,Stephan Menzel,Vikas Rana,Susanne Hoffmann‐Eifert,Stefan Wiefels
出处
期刊:APL Materials
[American Institute of Physics]
日期:2022-10-01
卷期号:10 (10)
被引量:19
摘要
The read variability of redox based resistive random access memory is one of the key characteristics with regard to its application in both data storage and novel computation in memory or neuromorphic architectures. While intrinsic noise limits the number of distinguishable states, it may be beneficial for probabilistic computing or to prevent overfitting. Thus, application and material system need to be carefully matched according to their read noise characteristics. Preceding density functional theory simulations suggested dividing oxides used in valence change memory into two categories based on the dominating conduction mechanism. We provide a comprehensive experimental study, which confirms the simulations and demonstrates how the conduction mechanism affects the variability. We analyze the signal-to-noise ratio (SNR) of five different switching oxides, revealing that oxides with shallow defect states (type 1) show high SNR whereas oxides with deep defect states (type 2) exhibit pronounced ionic noise. Thus, our results provide valuable input toward tuning of read noise characteristics by material design.
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