Tiffany Callahan, Kevin Cheng, et al.
ACS Spring 2025
Non-local spin-current conduction can be used to concentrate spin-current in a nanostructure in spin-torque switchable nanomagnets in solid-state memory. This is sometimes called spin-harvesting or spin-funneling. We use a simplified building block for understanding spin-harvest transport and some associated physical length-scales, identifying key materials and interface conductance parameters. A simple rotationally symmetric non-magnetic spin-conductor is used for solving its corresponding drift-diffusion transport equation, and for investigating the role finite interface spin-RAs play in affecting the spin-harvesting length-scale. A finite element model (FEM) is used to illustrate quantitative size and contact resistance dependent spin transport, followed by discussion of a simplified sheet-resistance-limit solution for illustrating a characteristic lateral length-scale that governs the spin-harvesting distance. Two key findings from this study are: (1) the effective spin-harvesting range is bound by spin drift-diffusion length λsfNM but usually shorter, and (2) There is a strong interplay among spin-flip diffusion length λsfNM and the bulk and interface spin-conductance of the NM. The more conducting the bulk NM is, and the more resistive a bottom interface RA is for spin-conduction, the longer range one can efficiently harvest spin-current. These results provide guidance for device structure designs utilizing spin-harvesting to maximize spin-current coupling into nanomagnets for spin-torque switching in magnetic random-access memory (STT-MRAM).
Tiffany Callahan, Kevin Cheng, et al.
ACS Spring 2025
Ana Stanojevic, Stanisław Woźniak, et al.
arXiv
Marvin Alberts, Federico Zipoli, et al.
NeurIPS 2023
Tiffany Callahan, Kevin Cheng, et al.
BPS 2025