Magneto-Ionic Physical Reservoir Computing in Perpendicularly Magnetized Heterostructures

Recent progress in magneto-ionics offers exciting potential to leverage its energy efficiency for implementing physical reservoir computing (PRC). In this work, we experimentally demonstrate the classification of temporal data using a perpendicularly magnetized magneto-ionic (MI) heterostructure. The device was specifically engineered to induce nonlinear ion migration dynamics, which in turn imparted nonlinearity and short-term memory (STM) to the magnetization. These key features for enabling reservoir computing were investigated, and the role of the ion migration mechanism, along with its history-dependent influence on STM, was explained. These attributes were utilized to distinguish between sine and square waveforms within a randomly distributed set of pulses. Additionally, two important performance metrics─STM and parity check capacity ─were quantified, yielding promising values of 1.44 and 2 for 24 virtual nodes, respectively, comparable to those of other state-of-the-art reservoirs. Our work paves the way for exploiting the relaxation dynamics of solid-state MI platforms and developing energy-efficient MI reservoir computing devices.