| 1. |
- Bainsla, Lakhan, 1985, et al.
(författare)
-
Large out-of-plane spin-orbit torque in topological Weyl semimetal TaIrTe 4
- 2024
-
Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1, s. 4649-
-
Tidskriftsartikel (refereegranskat)abstract
- The unique electronic properties of topological quantum materials, such as protected surface states and exotic quasiparticles, can provide an out-of-plane spin-polarized current needed for external field-free magnetization switching of magnets with perpendicular magnetic anisotropy. Conventional spin-orbit torque (SOT) materials provide only an in-plane spin-polarized current, and recently explored materials with lower crystal symmetries provide very low out-of-plane spin-polarized current components, which are not suitable for energy-efficient SOT applications. Here, we demonstrate a large out-of-plane damping-like SOT at room temperature using the topological Weyl semimetal candidate TaIrTe4 with a lower crystal symmetry. We performed spin-torque ferromagnetic resonance (STFMR) and second harmonic Hall measurements on devices based on TaIrTe4/Ni80Fe20 heterostructures and observed a large out-of-plane damping-like SOT efficiency. The out-of-plane spin Hall conductivity is estimated to be (4.05 ± 0.23)×104 (ℏ ⁄ 2e) (Ωm)-1, which is an order of magnitude higher than the reported values in other materials.
|
|
| 2. |
- Bainsla, Lakhan, et al.
(författare)
-
Large out-of-plane spin-orbit torque in topological Weyl semimetal TaIrTe4
- 2024
-
Ingår i: NATURE COMMUNICATIONS. - : Springer Nature. - 2041-1723. ; 15:1
-
Tidskriftsartikel (refereegranskat)abstract
- The unique electronic properties of topological quantum materials, such as protected surface states and exotic quasiparticles, can provide an out-of-plane spin-polarized current needed for external field-free magnetization switching of magnets with perpendicular magnetic anisotropy. Conventional spin-orbit torque (SOT) materials provide only an in-plane spin-polarized current, and recently explored materials with lower crystal symmetries provide very low out-of-plane spin-polarized current components, which are not suitable for energy-efficient SOT applications. Here, we demonstrate a large out-of-plane damping-like SOT at room temperature using the topological Weyl semimetal candidate TaIrTe4 with a lower crystal symmetry. We performed spin-torque ferromagnetic resonance (STFMR) and second harmonic Hall measurements on devices based on TaIrTe4/Ni80Fe20 heterostructures and observed a large out-of-plane damping-like SOT efficiency. The out-of-plane spin Hall conductivity is estimated to be (4.05 +/- 0.23)x10(4) ((h) over bar /2e) (Omega m)(-1), which is an order of magnitude higher than the reported values in other materials.
|
|
| 3. |
- Behera, Nilamani, et al.
(författare)
-
Ultra-Low Current 10 nm Spin Hall Nano-Oscillators
- 2024
-
Ingår i: Advanced Materials. - 0935-9648 .- 1521-4095. ; 36:5
-
Tidskriftsartikel (refereegranskat)abstract
- 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 Al2O3 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 (Formula presented.) A. In addition, the combination of electrical insulation and high thermal conductivity of the Al2O3 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 2Darrays.
|
|
