基于hfo2的记忆器件编程后电导漂移的综合统计研究

IF 4.6 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Materials Science in Semiconductor Processing Pub Date : 2025-05-15 DOI:10.1016/j.mssp.2025.109668

D. Maldonado , C. Acal , H. Ortiz , A.M. Aguilera , J.E. Ruiz-Castro , A. Cantudo , A. Baroni , K. Dorai Swamy Reddy , S. Pechmann , M. Uhlmann , C. Wenger , E. Pérez , J.B. Roldán

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引用次数: 0

摘要

hfo2基忆阻器的电导漂移是影响其在非易失性存储器和神经形态计算集成电路应用的关键可靠性问题。在这项工作中，我们提出了电阻随机存取存储器（RRAM）的电导漂移行为的全面统计分析，其物理基础是价变化机制。我们通过实验表征了六种不同电阻状态下的电导时间演变，并分析了各种概率分布对观察到的变异性的适用性。我们的研究结果表明，对数-逻辑概率分布在考虑阻力多电平和测量后规划时间的情况下，对实验数据有最好的拟合。此外，我们采用方差分析（ANOVA）来统计分析编程后时间和当前水平对观察到的变异性的影响。最后，在斯坦福紧凑模型的背景下，我们描述了如何实现变异性以获得测量电流值的概率分布。

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A comprehensive statistical study of the post-programming conductance drift in HfO2-based memristive devices

The conductance drift in HfO₂-based memristors is a critical reliability concern that impacts in their application in non-volatile memory and neuromorphic computing integrated circuits. In this work we present a comprehensive statistical analysis of the conductance drift behavior in resistive random access memories (RRAM) whose physics is based on valence change mechanisms. We experimentally characterize the conductance time evolution in six different resistance states and analyze the suitability of various probability distributions to model the observed variability. Our results reveal that the log-logistic probability distribution provides the best fit to the experimental data for the resistance multilevels and the measured post-programming times under consideration. Additionally, we employ an analysis of variance (ANOVA) to statistically analyze the post-programming time and current level effects on the observed variability. Finally, in the context of the Stanford compact model, we describe how variability has to be implemented to obtain the probability distribution of measured current values.

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来源期刊

Materials Science in Semiconductor Processing 工程技术-材料科学：综合

CiteScore

8.00

自引率

4.90%

发文量

780

审稿时长

42 days

期刊介绍： Materials Science in Semiconductor Processing provides a unique forum for the discussion of novel processing, applications and theoretical studies of functional materials and devices for (opto)electronics, sensors, detectors, biotechnology and green energy. Each issue will aim to provide a snapshot of current insights, new achievements, breakthroughs and future trends in such diverse fields as microelectronics, energy conversion and storage, communications, biotechnology, (photo)catalysis, nano- and thin-film technology, hybrid and composite materials, chemical processing, vapor-phase deposition, device fabrication, and modelling, which are the backbone of advanced semiconductor processing and applications. Coverage will include: advanced lithography for submicron devices; etching and related topics; ion implantation; damage evolution and related issues; plasma and thermal CVD; rapid thermal processing; advanced metallization and interconnect schemes; thin dielectric layers, oxidation; sol-gel processing; chemical bath and (electro)chemical deposition; compound semiconductor processing; new non-oxide materials and their applications; (macro)molecular and hybrid materials; molecular dynamics, ab-initio methods, Monte Carlo, etc.; new materials and processes for discrete and integrated circuits; magnetic materials and spintronics; heterostructures and quantum devices; engineering of the electrical and optical properties of semiconductors; crystal growth mechanisms; reliability, defect density, intrinsic impurities and defects.