Investigating the Impacts of Device Geometry and an Alternative Write Current Scheme on Write Time and Switching Energy of SOT-MRAMs

The spin-orbit torque magnetoresistive random access memory (SOT-MRAM) is a next generation spintronic memory device known for its fast switching speed, high endurance and non-volatility. However, as this technology is scaled up and implemented in practical memory systems, issues in switching time, energy, and reliability must be addressed. This paper investigates the impact of device geometry on write performance and the implementation of a two-pulse spin current for magnetization switching as a way to achieve a faster and more energy-efficient write process for SOT-MRAMs. To this end, conduction current redistribution was first quantified using finite element simulation. Then, spin current was calculated using the spin drift-diffusion framework, and micromagnetic simulations were carried out for different device geometries to determine their write times and switching energies. It was revealed that up to 18% reduction in both switching energy and switching time can be achieved with a 5 nm β-W heavy metal layer thickness compared against a 3 nm one. Moreover, the two-pulse spin current magnetization switching scheme reduced the switching time by an average of 15%, while keeping the switching energy constant, compared to its single-pulse counterpart.

I. Introduction

Spintronics, an emergent field in memory device technology, diverges from conventional memory systems by emphasizing electron spin as an information carrier as opposed to charge current [1]. Traditional architectures utilize power-expensive DRAM for storage [2] and then rely on SRAM banks for cache memory applications [3]. However, SRAM cells occupy relatively larger cell area and have poor retention characteristics due to their volatility. However, spintronic devices are inherently non-volatile, as electron spin is a conserved quantity [4]. In applications such as in-memory and neuromorphic computing, spintronic memory may be preferable due to its speed, low power consumption, and scalability [5].