journal article·2018-01-01Open access

Independent gate control of injected and detected spin currents in CVD graphene nonlocal spin valves

Yoska Anugrah, Jiaxi Hu, Gordon Stecklein, Paul A. Crowell, Steven J. Koester

AIP Advances· Volume 8· Issue 1

Abstract

Graphene is an ideal material for spintronic devices due to its low spin-orbit coupling and high mobility. One of the most important potential applications of graphene spintronics is for use in neuromorphic computing systems, where the tunable spin resistance of graphene can be used to apply analog weighting factors. A key capability needed to achieve spin-based neuromorphic computing systems is to achieve distinct regions of control, where injected and detected spin currents can be tuned independently. Here, we demonstrate the ability to achieve such independent control using a graphene spin valve geometry where the injector and detector regions are modulated by two separate bottom gate electrodes. The spin transport parameters and their dependence on each gate voltage are extracted from Hanle precession measurements. From this analysis, local spin transport parameters and their dependence on the local gate voltage are found, which provide a basis for a spatially-resolved spin resistance network that simulates the device. The data and model are used to calculate the spin currents flowing into, through, and out of the graphene channel. We show that the spin current flowing through the graphene channel can be modulated by 30% using one gate and that the spin current absorbed by the detector can be modulated by 50% using the other gate. This result demonstrates that spin currents can be controlled by locally tuning the spin resistance of graphene. The integration of chemical vapor deposition (CVD) grown graphene with local gates allows for the implementation of large-scale integrated spin-based circuits.
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Research context

OpenAlex topics: Graphene research and applications · Quantum and electron transport phenomena · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical and Computer Engineering, University of Minnesota-Twin Cities 1 , Minneapolis, MN 55455, USA

School of Physics and Astronomy, University of Minnesota-Twin Cities 2 , Minneapolis, MN 55455, USA

Funding

NSF | MPS | Division of Materials Research · SRC | Microelectronics Advanced Research Corporation

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