Tunable Skyrmion-Antiskyrmion Dynamics in Co/Pt Nanocontacts for Spintronic Applications

TL;DR

This study investigates the controllable dynamics of skyrmion-antiskyrmion pairs in Co/Pt nanocontacts, revealing stable and metastable states that can be toggled for advanced spintronic device applications.

Contribution

It demonstrates tunable skyrmion-antiskyrmion configurations in nanocontacts, enabling independent control for potential use in spintronic memory and logic devices.

Findings

Stable merged skyrmion states at 100 nm separation.

Metastable skyrmion-antiskyrmion pairs at larger separations.

Independent toggling of skyrmion states with magnetic fields.

Abstract

Magnetic skyrmions are topologically protected quasiparticles and have drawn much attention because of their potential applications in next-generation spintronics devices. Their inherent topological stability, nanoscale size, and efficient manipulation via spin currents make them promising candidates for high-density data storage and novel computing paradigms. We micromagnetically investigate the nucleation dynamics of magnetic skyrmion pairs excited underneath two 30 nm nanocontacts with varying separations on top of an extended Co/Pt bilayer thin film. At close separation of 100 nm, the magnetization configurations strongly interact, giving rise to the formation of stable merged skyrmion states. As the separation increases beyond 200 nm, topologically distinct metastable configurations emerge, including the coexistence of tunable skyrmion-antiskyrmion pairs through Dzyaloshinskii-Moriya interaction (DMI) strengths and current pulse amplitudes. These metastable states eventually relax into two stable skyrmions that can be independently toggled ON and OFF using a weak in-plane magnetic field, enabling complex logic operations and more flexible circuit designs. Beyond the fundamental interest in skyrmion interaction dynamics, the independent control of skyrmion-antiskyrmion states holds promise for next-generation spintronic devices, with potential applications in memory, logic, and computing.