An Analytical Model for the Forming Process of Conductive-Bridge Resistive-Switching Random-Access Memory

Lv, Shaoli; Wang, He; Zhang, Jinyu; Li, Jun; Sun, Lingling; Life, Zhiping Yu

doi:10.1109/ted.2014.2341274

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…Furthermore, in AgI a large amount of Ag ion interstitials is already available within the film and a counter charge is not required. Thus, an initial injection of Ag ions and a migration through the complete insulator thickness, which has been taken into account by other groups, 43 is not required.…”

Section: Simulation Proceduresmentioning

confidence: 99%

Understanding filamentary growth in electrochemical metallization memory cells using kinetic Monte Carlo simulations

2015

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We report on a 2D kinetic Monte Carlo model that describes the resistive switching in electrochemical metallization cells. To simulate the switching process, we consider several different processes on the atomic scale: electron-transfer reactions at the boundaries, ion migration, adsorption/desorption from/to interfaces, surface diffusion and nucleation. These processes result in a growth/dissolution of a metallic filament within an insulating matrix. In addition, the model includes electron tunneling between the growing filament and the counter electrode, which allows for simulating multilevel switching. It is shown that the simulation model can reproduce the reported switching kinetics, switching variability and multilevel capabilities of ECM devices. As a major result, the influence of mechanical stress working on the host matrix due to the filamentary growth is investigated. It is demonstrated that the size and shape of the filament depend on the Young's modulus of the insulating matrix. For high values a wire-like structure evolves, whereas the shape is dendritic if the Young's modulus is negligible.

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Section: Simulation Proceduresmentioning

confidence: 99%

Understanding filamentary growth in electrochemical metallization memory cells using kinetic Monte Carlo simulations

2015

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“…18,19 Recent experiments 17,20,21 on the nanoscale metallic clusters in dielectrics indicate complicate electrochemical mechanism to determine the filament growth in CBRAM. Some simulation works about filament growth have been reported, [22][23][24][25] the physical mechanism of filament growth in the atomistic level is still need to be clarified. In this paper, we quantitatively demonstrate two types of filament growth using KMC and appropriate model parameters.…”

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confidence: 99%

Atomistic study of dynamics for metallic filament growth in conductive-bridge random access memory

Qin

Guo

et al. 2015

Phys. Chem. Chem. Phys.

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The growth dynamics for metallic filaments in conductive-bridge resistive-switching random access memory (CBRAM) are studied using the kinetic Monte Carlo (KMC) method. The physical process at the atomistic level is revealed in explaining the experimental observation that filament growth can originate at either the cathode or the anode. The statistical nature of the filament growth is best shown by the random topography of dendrite-like conductive paths obtained. Critical material properties, such as charged-particle mobility in the switching layer of a solid electrolyte or a dielectric, are mapped to KMC model parameters through activation energy, etc. The accuracy of the simulator is established by the good agreement between the simulated forming time and the measured data.

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“…5e ). The formation of an oxygen-rich crystalline shell is attributed to a combined effect of temperature and lateral motion of , which is dominated by two opposite forces: inwards thermal diffusion driven by a temperature gradient and outwards Fickian diffusion driven by a concentration gradient 59 – 61 (see Supplementary Fig. 8 ).…”

Section: Resultsmentioning

confidence: 99%

Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging

et al. 2021

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The resistive switching effect in memristors typically stems from the formation and rupture of localized conductive filament paths, and HfO2 has been accepted as one of the most promising resistive switching materials. However, the dynamic changes in the resistive switching process, including the composition and structure of conductive filaments, and especially the evolution of conductive filament surroundings, remain controversial in HfO2-based memristors. Here, the conductive filament system in the amorphous HfO2-based memristors with various top electrodes is revealed to be with a quasi-core-shell structure consisting of metallic hexagonal-Hf6O and its crystalline surroundings (monoclinic or tetragonal HfOx). The phase of the HfOx shell varies with the oxygen reservation capability of the top electrode. According to extensive high-resolution transmission electron microscopy observations and ab initio calculations, the phase transition of the conductive filament shell between monoclinic and tetragonal HfO2 is proposed to depend on the comprehensive effects of Joule heat from the conductive filament current and the concentration of oxygen vacancies. The quasi-core-shell conductive filament system with an intrinsic barrier, which prohibits conductive filament oxidation, ensures the extreme scalability of resistive switching memristors. This study renovates the understanding of the conductive filament evolution in HfO2-based memristors and provides potential inspirations to improve oxide memristors for nonvolatile storage-class memory applications.

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An Analytical Model for the Forming Process of Conductive-Bridge Resistive-Switching Random-Access Memory

Cited by 7 publications

References 13 publications

Understanding filamentary growth in electrochemical metallization memory cells using kinetic Monte Carlo simulations

Understanding filamentary growth in electrochemical metallization memory cells using kinetic Monte Carlo simulations

Atomistic study of dynamics for metallic filament growth in conductive-bridge random access memory

Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging

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