When working with Spin-Torque Ferromagnetic Resonance (ST-FMR), the journey from raw resonance spectra to physical parameters can be complex. We are often dealing with competing effects—bulk spin transport versus interfacial phenomena.
Based on the methodology presented in a recent study 1, I’ve visualized the analytical workflow we use to process the thickness dependence of ST-FMR data. This flowchart highlights two parallel but interconnected extraction paths:
1. The Path to SOT Efficiency (Left Panel)
The primary goal here is to quantify the torque. By decomposing the resonance lineshape into symmetric (\(V_S\)) and antisymmetric (\(V_A\)) Lorentzian components, we isolate the damping-like and field-like contributions.Crucially, we incorporate the effective magnetization (\(M_{eff}\)), derived directly from the resonance field (\(H_{FMR}\)), to correct our calculations. This allows us to convert raw voltages into the FMR efficiency (\(\xi_{FMR}\)), and ultimately disentangle the damping-like (\(\xi_{DL}\)) and field-like (\(\xi_{FL}\)) torque efficiencies.
2. The Path to Spin Dissipation (Right Panel)
Simultaneously, we must account for how spin current is lost. By analyzing the linewidth (\(\Delta H\)) across different ferromagnetic layer thicknesses, we extract the Gilbert damping constant (\(\alpha\)).The enhancement of damping leads us to the effective spin mixing conductance (\(G_{eff}\)). This is the key to quantifying spin dissipation (\(\varepsilon\))—often interpreted as spin memory loss or spin backflow at the interface.
Why this matters:
By treating these two paths systematically, we can better understand if a material's performance is limited by the bulk generation of spin currents or by losses at the interface. This workflow provides a rigorous check on our SOT efficiency values by explicitly accounting for the transparency of the interface.
Note:Drafting assistance and language polishing provided by Gemini.