Deterministic Conductive Filament Formation and Evolution for Improved Switching Uniformity in Embedded Metal-Oxide-Based Memristors─A Phase-Field Study

Abstract

The extreme device-to-device variation of switching performance is one of the major obstacles preventing the applications of metal-oxide-based memristors in large-scale memory storage and resistive neural networks. Recent experimental works have reported that embedding metal nano-islands (NIs) in metal oxides can effectively improve the uniformity of the memristors, but the underlying role of the NIs is not fully understood. Here, to address this specific problem, we develop a physical model to understand the origin of the variability and how the embedded NIs can improve the performance and uniformity of memristors. We find that due to the dimension confinement effect, embedding metal NIs can modulate the electric field distribution and lead to a more deterministic formation of the conductive filament (CF) from their vicinity, in contrast to the random growth of CFs without embedded NIs. This deterministic CF formation, via vacancy nucleation, further reduces the forming, reset, and set voltages and enhances the uniformity of the operation voltages and current ON/OFF ratios. We further demonstrate that modifying the shapes of the metal NIs can modulate the field strengths/distributions around the NIs and that choosing the NI metal composition and shape that chemically facilitate vacancy formations can further optimize the CF morphology, reduce the operation voltages, and improve the switching performance. Our work thus provides a fundamental understanding of how embedded metal NIs improve the resistive switching performance in oxide-based memristors and could potentially guide the selection of embedded NIs to realize a more uniform memristor that also operates at a higher efficiency than present materials.

Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices

“…The M or I phases form perpendicular to the current flow axis, presenting a transverse barrier to the movement of charge carriers that are driven by the electrical stimulus. This type of resistive switching is quite different from the more common conducting filament generation parallel to the current flow reported for other oxides exposed to E-fields. − The amplitude image recovers its original M–I contrast when the applied field is turned off, as can be seen by comparing Figure d­(v) and Figure d­(viii). For the same device, we have also performed the topography and amplitude scans with decreasing applied field (SI Figure S8) and observed similar behavior.…”

N-Doped Graphene/MXene Nanocomposite as a Temperature-Adaptive Neuromorphic Memristor

“…The model of the conductive filament in memristors was proposed according to the first-principles simulations that have been reported elsewhere. The literature found that the principle can be used to predict filament formation, which enables the regulation of operational voltages and improvement in uniformity of memristors, leading to a foundational understanding of performance optimization. , Figure illustrates the probable working mechanism schematic diagram of the fabricated memristor at several different temperatures. Figure a shows conducting filament formation at RT.…”

“…The literature found that the principle can be used to predict filament formation, which enables the regulation of operational voltages and improvement in uniformity of memristors, leading to a foundational understanding of performance optimization. 59,60 Figure 9 illustrates the probable working mechanism schematic diagram of the fabricated memristor at several different temperatures.…”