Atomically Thin CBRAM Enabled by 2-D Materials: Scaling Behaviors and Performance Limits

Abstract

Reducing the energy and power dissipation of conductive bridge random access memory (CBRAM) cells is of critical importance for their applications in future Internet of Things (IoT) device and neuromorphic computing platforms. Atomically thin CBRAMs enabled by 2-D materials are studied theoretically by using 3-D kinetic Monte Carlo simulations together with experimental characterization. The results indicate the performance potential of attoJoule energy dissipation for intrinsic filament formation and a filament size of a single atomistic chain in such a CBRAM cell. The atomically thin CBRAM cells also show qualitatively different features from conventional CBRAM cells, including complete rupture of the filament in the reset stage and comparable forming and set voltages. The scaling and variability of the CBRAM cells down to sub-nanometer size of the switching layer as realized in the experiment are systematically studied, which indicates performance improvement and increased relative variability as the switching layer scales down. The results establish the ultimate limits of the size and energy scaling for CBRAM cells and illustrate the unique application of 2-D materials in ultralow power memory devices.