Bias dependent spin injection into graphene on YIG through bilayer hBN tunnel barriers

TL;DR

This study investigates how bias influences spin injection efficiency into graphene on YIG through bilayer hBN barriers, demonstrating high variability and confirming bilayer hBN's effectiveness as a tunnel barrier in spintronics.

Contribution

It provides experimental evidence that bilayer hBN barriers enable efficient, bias-dependent spin injection into graphene on YIG, extending previous findings to non-encapsulated systems.

Findings

Spin injection efficiency varies from -60% to +25% with bias.

Non-local spin signals can be increased or suppressed by bias.

Bilayer hBN is validated as an effective tunnel barrier for graphene spintronics.

Abstract

We study the spin injection efficiency into single and bilayer graphene on the ferrimagnetic insulator Yttrium-Iron-Garnet (YIG) through an exfoliated tunnel barrier of bilayer hexagonal boron nitride (hBN). The contacts of two samples yield a resistance-area product between 5 and 30 k$\Omega\mu$m$^2$. Depending on an applied DC bias current, the magnitude of the non-local spin signal can be increased or suppressed below the noise level. The spin injection efficiency reaches values from -60% to +25%. The results are confirmed with both spin valve and spin precession measurements. The proximity induced exchange field is found in sample A to be (85 $\pm$ 30) mT and in sample B close to the detection limit. Our results show that the exceptional spin injection properties of bilayer hBN tunnel barriers reported by Gurram et al. are not limited to fully encapsulated graphene systems but are also valid in graphene/YIG devices. This further emphasizes the versatility of bilayer hBN as an efficient and reliable tunnel barrier for graphene spintronics.