Spin–Charge Conversion-Based Artificial Synaptic Device for Neuromorphic Computing

A synaptic function is demonstrated using spin–charge conversion in a Rashba system. In an asymmetric quantum well channel, fast-moving charges induce a Rashba effective magnetic field, which separates spin-up and spin-down potentials. The ferromagnet detects these spin-dependent potentials, corresponding to the spin information on the channel. The multiple ferromagnetic electrodes, each with different switching fields, probe their respective spin potentials, and the output terminal reads the superposition of the detected potentials, thereby realizing multiple voltage states. These multiple states are systematically modulated and changed to any desired state directly, enabling both the potentiation and depression of synaptic behavior. In this memristive function device, both charge-to-spin and spin-to-charge conversions are demonstrated in a single device, consistent with the reciprocal relation. Additionally, neuromorphic pattern recognition is clearly demonstrated by controlling the Vmax/Vmin ratio and offset resistance.

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Publication Details

Journal
ACS Applied Electronic Materials
Published
2024-12-27
DOI
https://doi.org/10.1021/acsaelm.4c02048
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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Spin–Charge Conversion-Based Artificial Synaptic Device for Neuromorphic Computing

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Spin–Charge Conversion-Based Artificial Synaptic Device for Neuromorphic Computing

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article en

Abstract

A synaptic function is demonstrated using spin–charge conversion in a Rashba system. In an asymmetric quantum well channel, fast-moving charges induce a Rashba effective magnetic field, which separates spin-up and spin-down potentials. The ferromagnet detects these spin-dependent potentials, corresponding to the spin information on the channel. The multiple ferromagnetic electrodes, each with different switching fields, probe their respective spin potentials, and the output terminal reads the superposition of the detected potentials, thereby realizing multiple voltage states. These multiple states are systematically modulated and changed to any desired state directly, enabling both the potentiation and depression of synaptic behavior. In this memristive function device, both charge-to-spin and spin-to-charge conversions are demonstrated in a single device, consistent with the reciprocal relation. Additionally, neuromorphic pattern recognition is clearly demonstrated by controlling the Vmax/Vmin ratio and offset resistance.

ACS Applied Electronic MaterialsVol. 7(1)
ON Semiconductor (United States) (US), University of Science and Technology (YE), Korea University (KR), Center for NanoScience (DE), PRG S&Tech (South Korea), Korea Institute of Science and Technology (KR), Korea University of Science and Technology (KR)
Korea Institute of Science and Technology, National Research Council of Science and Technology, KU-KIST Graduate School of Converging Science and Technology
Affordable and clean energy
Openalex Percentile: Top 78%
Advanced Memory and Neural Computing
DOISourceOpenAlex
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