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

delete2024-12-27
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PRE
AI
S
Seong Been Kim
J
Je‐Jun Lee
D
Dongwon Choi
S
Seung‐Whan Kim
J
Jeong Ung Ahn
K
Ki Hyuk Han
T
Tae‐Eon Park
O
OukJae Lee
K
Ki‐Young Lee
S
Seokmin Hong
B
Byoung‐Chul Min
H
Hyung-jun Kim
D
Do Kyung Hwang
H
Hyun Cheol Koo *
DOI:10.1021/acsaelm.4c02048delete
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Abstract

Abstract

En 中文
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 V max/V min ratio and offset resistance.
Keywords:
spin-chargeconversion
Rashba spin-orbitcoupling
multistate memory
artificial synapses
neuromorphic computing

Journal

ACS Applied Electronic Materials cover
ACS Applied Electronic Materials
IF:
4.7
Papers:
5.0K
Citations:
1.4W

Organization

K
Korea University
Scholars:
3.6W
Papers: 3.8W
Citations: 4.4W
K
korea institute of science & technology (kist)
Scholars:
1.2W
Papers: 1.3W
Citations: 23