RESUMO
Van der Waals (vdW) magnets are promising, because of their tunable magnetic properties with doping or alloy composition, where the strength of magnetic interactions, their symmetry, and magnetic anisotropy can be tuned according to the desired application. However, so far, most of the vdW magnet-based spintronic devices have been limited to cryogenic temperatures with magnetic anisotropies favoring out-of-plane or canted orientation of the magnetization. Here, we report beyond room-temperature lateral spin-valve devices with strong in-plane magnetization and spin polarization of the vdW ferromagnet (Co0.15Fe0.85)5GeTe2 (CFGT) in heterostructures with graphene. Density functional theory (DFT) calculations show that the magnitude of the anisotropy depends on the Co concentration and is caused by the substitution of Co in the outermost Fe layer. Magnetization measurements reveal the above room-temperature ferromagnetism in CFGT and clear remanence at room temperature. Heterostructures consisting of CFGT nanolayers and graphene were used to experimentally realize basic building blocks for spin valve devices, such as efficient spin injection and detection. Further analysis of spin transport and Hanle spin precession measurements reveals a strong in-plane magnetization with negative spin polarization at the interface with graphene, which is supported by the calculated spin-polarized density of states of CFGT. The in-plane magnetization of CFGT at room temperature proves its usefulness in graphene lateral spin-valve devices, thus revealing its potential application in spintronic technologies.
RESUMO
Nano-constriction based spin Hall nano-oscillators (SHNOs) are at the forefront of spintronics research for emerging technological applications, such as oscillator-based neuromorphic computing and Ising Machines. However, their miniaturization to the sub-50 nm width regime results in poor scaling of the threshold current. Here, it shows that current shunting through the Si substrate is the origin of this problem and studies how different seed layers can mitigate it. It finds that an ultra-thin Al2 O3 seed layer and SiN (200 nm) coated p-Si substrates provide the best improvement, enabling us to scale down the SHNO width to a truly nanoscopic dimension of 10 nm, operating at threshold currents below 30 µ $\umu$ A. In addition, the combination of electrical insulation and high thermal conductivity of the Al2 O3 seed will offer the best conditions for large SHNO arrays, avoiding any significant temperature gradients within the array. The state-of-the-art ultra-low operational current SHNOs hence pave an energy-efficient route to scale oscillator-based computing to large dynamical neural networks of linear chains or 2D arrays.
