Variability-aware modeling of electrochemical metallization memory cells

Abstract

Resistively switching electrochemical metallization memory cells are gaining huge interest since they are seen as promising candidates and basic building blocks for future computation-in-memory applications. However, especially filamentary-based memristive devices suffer from inherent variability, originating from their stochastic switching behavior. A variability-aware compact model of electrochemical metallization memory cells is presented in this study and verified by showing a fit to experimental data. It is an extension of the deterministic model. Since this extension consists of several different features allowing for a realistic variability-aware fit, it depicts a unique model comprising physics-based, stochastically and experimentally originating variabilities and reproduces them well. In addition, a physics-based model parameter study is executed, which enables a comprehensive view into the device physics and presents guidelines for the compact model fitting procedure.

Keywords

• memristive devices
• variability-aware modeling
• ReRAM
• ECM
• CBRAM
• SPICE level