Integration of ZnO-Based Resistive-Switching Memory and Ge₂Sb₂Te₅-Based Phase-Change Memory

Abstract

Memristor devices exhibited many advantages, such as fast write/read speed, high storage density, low power consumption, and simple structure, which could be applied to 3D stacking. However, the sneak current during stacking would become a major issue in the development of 3D structures. In this study, we proposed an integrated structure, one phase-change memory one resistive random access memory (1P1R), to suppress the sneak current. The 1P1R device was always kept at [0 1] or [0 0] (logic state) with high resistance to suppress the sneak current, while it was switched to [1 1] or [1 0] (working states) to write/read its state. Phase-change memory acted as the switching element, and resistive random access memory acted as the memory. Our electrical measurement confirmed its feasibility, and the property analysis provided the information for its speculated mechanism. The results successfully demonstrated that the novel 1P1R structure could be used to suppress sneak current, demonstrating potential for 3D IC manufacturing.

In-sensor neuromorphic computing using perovskites and transition metal dichalcogenides

“…Therefore, constructing hardware-based neuromorphic computing systems based on neuromorphic devices through emulating the structural characteristics of BNNs is an efficacious approach to break the limitations imposed by von Neumann bottleneck, and realize high-efficiency and low-energy data processing. Various kind of neuromorphic devices, including memristors [129][130][131][132][133], transistors [51,[134][135][136][137][138][139], memtransistor [140][141][142][143][144][145][146], spintronic devices [147][148][149][150][151], and phase-change memory [152][153][154][155][156][157] had been developed. Memristor and neuromorphic transistor are two most common devices for mimicking the synaptic behaviors.…”