Spintronic nano-oscillators with reduced non-linearity could offer key benefits for realizing neuromorphic applications such as spike-based neurons and frequency multiplexing in neural networks. Here, we experimentally demonstrate the reduction in non-linearity of a spin-Hall nano-oscillator (SHNO) by compensation of its effective magnetic anisotropy. The study involves optimization of Co/Ni multilayer growth to achieve the compensation, followed by spin diode measurements on patterned microstrips to quantify their anisotropy. The relation between the second (Hk2 = 0.47 mT) and the first order (Hk1eff = −0.8 mT) anisotropy fields reveals the existence of an easy cone, thereby validating the presence of compensation. Furthermore, we demonstrate a synapse based on the compensated spin diode which has a fixed frequency when the input power is varied. We then study the current-induced auto-oscillation properties of SHNOs on compensated films by patterning nano-constrictions of widths 200 and 100 nm. The invariance of the resonance frequency and linewidth of the compensated SHNO with applied dc current indicates the absence of non-linearity. This independence is maintained irrespective of the applied external fields and its orientations. The compensated SHNO obtained has a linewidth of 1.1 MHz and a peak output power of up to 1 pW/MHz emulating a nano-neuron with a low linewidth and a fixed frequency.
@article{arxiv.2301.03794,
title = {Compensation of anisotropy in spin-Hall devices for neuromorphic applications},
author = {Pankaj Sethi and Dédalo Sanz-Hernández and Florian Godel and Sachin Krishnia and Fernando Ajejas and Alice Mizrahi and Vincent Cros and Danijela Marković and Julie Grollier},
journal= {arXiv preprint arXiv:2301.03794},
year = {2023}
}