Enhancing non-volatile memory and neuromorphic computing: integration of PRAM and OTS for scalable, energy-efficient architectures

Abstract

This paper investigates the integration of phase-change random access memory (PRAM) and ovonic threshold switch (OTS) devices, emphasizing their ability to advance non-volatile memory technologies, neuromorphic computing architectures, and energy-efficient systems. OTS devices' nonlinear threshold switching effectively mitigates sneak currents in high-density crossbar arrays, while challenges like resistivity drift and structural relaxation are addressed through advanced modeling and experimental analysis. The study highlights innovations in phase-change materials, such as doped Sb2Te3 alloys and Sb2Te3-GeTe superlattices deposited by magnetron sputtering, which have been reported to improve thermal stability, reduce RESET power, and enhance cycling endurance compared with conventional GST-based phase-change memory devices. PRAM-OTS hybrid systems demonstrate exceptional performance in spiking and multi-layer neural networks, replicating neuronal behaviors such as integrate-and-fire dynamics and spike-timing-dependent plasticity for low-latency, energy-efficient processing in artificial intelligence, robotics, and internet of things applications. These scalable and reliable systems provide a robust framework for next-generation high-performance computational platforms, addressing key challenges in scalability, energy efficiency, and operational longevity.