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识别和理解忆阻器件的非线性行为。

Identifying and understanding the nonlinear behavior of memristive devices.

作者信息

Yarragolla Sahitya, Hemke Torben, Jalled Fares, Gergs Tobias, Trieschmann Jan, Arul Tolga, Mussenbrock Thomas

机构信息

Chair of Applied Electrodynamics and Plasma Technology, Ruhr University Bochum, Universitätsstraße 150, 44780, Bochum, Germany.

Theoretical Electrical Engineering, Faculty of Engineering, Kiel University, Kaiserstraße 2, 24143, Kiel, Germany.

出版信息

Sci Rep. 2024 Dec 30;14(1):31633. doi: 10.1038/s41598-024-80568-y.

DOI:10.1038/s41598-024-80568-y
PMID:39738176
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11686099/
Abstract

Nonlinearity is a crucial characteristic for implementing hardware security primitives or neuromorphic computing systems. The main feature of all memristive devices is this nonlinear behavior observed in their current-voltage characteristics. To comprehend the nonlinear behavior, we have to understand the coexistence of resistive, capacitive, and inertia (virtual inductive) effects in these devices. These effects originate from corresponding physical and chemical processes in memristive devices. A physics-inspired compact model is employed to model and simulate interface-type RRAMs such as Au/BiFeO[Formula: see text]/Pt/Ti, Au/Nb[Formula: see text]O[Formula: see text]/Al[Formula: see text]O[Formula: see text]/Nb, while accounting for the modeling of capacitive and inertia effects. The simulated current-voltage characteristics align well with experimental data and accurately capture the non-zero crossing hysteresis generated by capacitive and inductive effects. This study examines the response of two devices to increasing frequencies, revealing a shift in their nonlinear behavior characterized by a reduced hysteresis range Fourier series analysis utilizing a sinusoidal input voltage of varying amplitudes and frequencies indicates harmonics or frequency components that considerably influence the functioning of RRAMs. Moreover, we propose and demonstrate the use of the frequency spectra as one of the fingerprints for memristive devices.

摘要

非线性是实现硬件安全原语或神经形态计算系统的关键特性。所有忆阻器的主要特征是在其电流 - 电压特性中观察到的这种非线性行为。为了理解这种非线性行为，我们必须了解这些器件中电阻、电容和惯性（虚拟电感）效应的共存情况。这些效应源自忆阻器中的相应物理和化学过程。采用一个受物理启发的紧凑模型对诸如Au/BiFeO[化学式：见原文]/Pt/Ti、Au/Nb[化学式：见原文]O[化学式：见原文]/Al[化学式：见原文]O[化学式：见原文]/Nb等界面型RRAM进行建模和仿真，同时考虑电容和惯性效应的建模。模拟的电流 - 电压特性与实验数据吻合良好，并准确捕捉了由电容和电感效应产生的非零交叉滞后现象。本研究考察了两个器件对频率增加的响应，揭示了它们非线性行为的变化，其特征是滞后范围减小。利用不同幅度和频率的正弦输入电压进行傅里叶级数分析表明，谐波或频率成分对RRAM的功能有相当大的影响。此外，我们提出并证明了使用频谱作为忆阻器器件的指纹之一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/46e8cbccf603/41598_2024_80568_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/147f0cff01e5/41598_2024_80568_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/415408a68223/41598_2024_80568_Fig2_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/2f817943c899/41598_2024_80568_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/430911bdf4ff/41598_2024_80568_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/52b8767ddc1c/41598_2024_80568_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/46e8cbccf603/41598_2024_80568_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/147f0cff01e5/41598_2024_80568_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/415408a68223/41598_2024_80568_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/ed06e6f866e9/41598_2024_80568_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/2f817943c899/41598_2024_80568_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/430911bdf4ff/41598_2024_80568_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/52b8767ddc1c/41598_2024_80568_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b77/11686099/46e8cbccf603/41598_2024_80568_Fig7_HTML.jpg

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Physics inspired compact modelling of [Formula: see text] based memristors.基于物理原理的[公式：见原文]忆阻器紧凑建模。
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