Leaky-Integrate-Fire Neuron Based on Antiferromagnetic Skyrmion Under Strain Gradient

Antiferromagnetic (AFM) skyrmion-based spintronic devices are favored over their ferromagnetic (FM) counterparts due to compelling characteristics including robust exchange interaction, interfacial Dzyaloshinskii-Moriya interaction (DMI), minimal stray fields, low susceptibility to external fields, and inherent non-volatility. The straight trajectories followed by AFM skyrmions prevent their annihilation at the edges of nanoscale racetracks, making them a more promising candidate than FM skyrmions for future spintronic applications. In this work, AFM skyrmion dynamics under strain gradient is studied. It is observed that creating the strain gradient is an efficient way to drive AFM skyrmions with a high longitudinal speed in the order 800 m/s. Furthermore, a leaky integrate-and-fire (LIF) neuron is proposed based on strain gradient for enhancing energy efficiency in neuromorphic computing systems. This opens a new alternative way to manipulate AFM skyrmions for the development of energy-efficient AFM skyrmion based devices in neuromorphic computing.