Neuromorphic computing aims to revolutionize large-scale data processing by developing efficient methods and devices inspired by neural networks. Among these, the control of magnetism through ion migration has emerged as a promising approach due to the inherent memory and nonlinearity of ionically conducting and magnetic materials. In this work, we present a lithium-ion-based magneto-ionic device that uses applied voltages to control the magnetic domain state of a perpendicularly magnetized ferromagnetic layer. This behavior emulates the analog and non-volatile properties of biological synapses and enables the creation of a simple reservoir computing system. To illustrate its capabilities, the device is used in a waveform classification task, where the voltage amplitude range and magnetic bias field are tuned to optimize the recognition accuracy.
@article{arxiv.2412.11297,
title = {A magneto-ionic synapse for reservoir computing},
author = {Sreeveni Das and Rhodri Mansell and Lukáš Flajšman and Maria-Andromachi Syskaki and Jürgen Langer and Sebastiaan van Dijken},
journal= {arXiv preprint arXiv:2412.11297},
year = {2024}
}