Proceedings of MATSUS Fall 2023 Conference (MATSUSFall23)
DOI: https://doi.org/10.29363/nanoge.matsus.2023.183
Publication date: 18th July 2023
With the increasing demand for artificially intelligent hardware systems for brain-inspired in-memory and neuromorphic computing, perovskite-based memristors has emerged as a promising candidate for resistive random-access memory (ReRAM) devices [1]. Metal halide perovskite semiconductors exhibit mixed ionic-electronic conduction resulting to intrinsic memory effects (hysteresis) in the current-voltage (I-V ) response [2-4]. In order to meet the necessary demands in various complex computing frameworks, understanding the underlying mechanisms governing the resistive switching of these perovskite-based memristor devices is of paramount importance. Here, we present the dynamic impedance spectral evolution of the state transition in perovskite-based memristor devices exhibiting significant transformation of the low frequency capacitance to inductance near the threshold voltage [5]. This transition implies that the interfacial reactivity between the migrating ions with the thin Ag metal contact results to the further gradual decrease in the device resistance indicative of a non-filamentary switching mechanism. Moreover, the incorporation of a thin undoped interfacial buffer layer exhibits an abrupt state transition in the characteristic I-V response [6]. This abrupt state transition is part of a two-step SET process where both drift-related halide migration and diffusion-related filamentary formation is observed. Furthermore, we develop a dynamical model that helps untangle and quantify the switching regimes consistent with the experimental memristive response. This further insight on the complex interplay among mobile ions, vacancies, and metal provides another degree of freedom in device design for versatile applications with varying levels of complexity.
We thank the financial support from the Generalitat Valenciana for the Grisolia Grant (GRISOLIAP/2019/048) and from the Ministerio de Ciencia e Innovación of Spain (MICINN) (PID2019-107348GB-100).
We thank MICINN for support by the project EUR2022-134045/ AEI / 10.13039/501100011033.
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