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Register a new userOn the key role of oxygen vacancies electromigration in the memristive response of ferroelectric devices
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Added by
Maria Jose Sanchez Majo
Publication date
2020
fields
Physics
and research's language is
English
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Ferroelectric memristors are intensively studied due to their potential implementation in data storage and processing devices. In this work we show that the memristive behavior of metal/ferroelectric oxide/metal devices relies on the competition of two effects: the modulation of metal/ferroelectric interface barriers by the switchable ferroelectric polarization and the electromigration of oxygen vacancies, with the depolarizing field playing a fundamental role in the latter. We simulate our experimental results with a phenomenological model that includes both effects and we reproduce several non-trivial features of the electrical response, including resistance relaxations observed after external poling. Besides providing insight into the underlying physics of these complex devices, our work suggests that it is possible to combine non-volatile and volatile resistive changes in single ferroelectric memristors, an issue that could be useful for the development of neuromorphic devices.
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In this work we report on the role of ion transport for the dynamic behavior of a double barrier quantum mechanical Al/Al$_2$O$_3$/Nb$_{text{x}}$O$_{text{y}}$/Au memristive device based on numerical simulations in conjunction with experimental measurements. The device consists of an ultra-thin Nb$_{text{x}}$O$_{text{y}}$ solid state electrolyte between an Al$_2$O$_3$ tunnel barrier and a semiconductor metal interface at an Au electrode. It is shown that the device provides a number of interesting features for potential applications such as an intrinsic current compliance, a relatively long retention time, and no need for an initialization step. Therefore, it is particularly attractive for applications in highly dense random access memories or neuromorphic mixed signal circuits. However, the underlying physical mechanisms of the resistive switching are still not completely understood yet. To investigate the interplay between the current transport mechanisms and the inner atomistic device structure a lumped element circuit model is consistently coupled with 3D kinetic Monte Carlo model for the ion transport. The simulation results indicate that the drift of charged point defects within the Nb$_{text{x}}$O$_{text{y}}$ is the key factor for the resistive switching behavior. It is shown in detail that the diffusion of oxygen modifies the local electronic interface states resulting in a change of the interface properties of the double barrier device.
Ferroelectricity, especially in hafnia-based thin films at nanosizes, has been rejuvenated in the fields of low-power, nonvolatile and Si-compatible modern memory and logic applications. Despite tremendous efforts to explore the formation of the metastable ferroelectric phase and the polarization degradation during field cycling, the ability of oxygen vacancy to exactly engineer and switch polarization remains to be elucidated. Here we report reversibly electrochemical control of ferroelectricity in Hf$_{0.5}$Zr$_{0.5}$O$_2$ (HZO) heterostructures with a mixed ionic-electronic LaSrMnO$_3$ electrode, achieving a hard breakdown field more than 18 MV/cm, over fourfold as high as that of typical HZO. The electrical extraction and insertion of oxygen into HZO is macroscopically characterized and atomically imaged in situ. Utilizing this reversible process, we achieved multiple polarization states and even repeatedly repaired the damaged ferroelectricity by reversed negative electric fields. Our study demonstrates the robust and switchable ferroelectricity in hafnia oxide distinctly associated with oxygen vacancy and opens up opportunities to recover, manipulate, and utilize rich ferroelectric functionalities for advanced ferroelectric functionality to empower the existing Si-based electronics such as multi-bit storage.
The ferroelectric polarization switching in ferroelectric hafnium zirconium oxide (Hf0.5Zr0.5O2, HZO) in the HZO/Al2O3 ferroelectric/dielectric stack is investigated systematically by capacitance-voltage and polarization-voltage measurements. The thickness of dielectric layer is found to have a determinant impact on the ferroelectric polarization switching of ferroelectric HZO. A suppression of ferroelectricity is observed with thick dielectric layer. In the gate stacks with thin dielectric layers, a full polarization switching of the ferroelectric layer is found possible by the proposed leakage-current-assist mechanism through the ultrathin dielectric layer. Theoretical simulation results agree well with experimental data. This work clarifies some of the critical parts of the long-standing confusions and debating related to negative capacitance field-effect transistors (NC-FETs) concepts and experiments.
We report on resistive switching of memristive electrochemical metallization devices using 3D kinetic Monte Carlo simulations describing the transport of ions through a solid state electrolyte of an Ag/TiO$_{text{x}}$/Pt thin layer system. The ion transport model is consistently coupled with solvers for the electric field and thermal diffusion. We show that the model is able to describe not only the formation of conducting filaments but also its dissolution. Furthermore, we calculate realistic current-voltage characteristics and resistive switching kinetics. Finally, we discuss in detail the influence of both the electric field and the local heat on the switching processes of the device.
We introduce an approach based on the Chapman-Kolmogorov equation to model heterogeneous stochastic circuits, namely, the circuits combining binary or multi-state stochastic memristive devices and continuum reactive components (capacitors and/or inductors). Such circuits are described in terms of occupation probabilities of memristive states that are functions of reactive variables. As an illustrative example, the series circuit of a binary memristor and capacitor is considered in detail. Some analytical solutions are found. Our work offers a novel analytical/numerical tool for modeling complex stochastic networks, which may find a broad range of applications.
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