Abstract
Neuromorphic computing, which seeks to replicate the brain's ability to process information, has garnered significant attention due to its potential to achieve brain-like computing efficiency and human cognitive intelligence. Spin-orbit torque (SOT) devices can be used to simulate artificial synapses with non-volatile, high-speed processing and endurance characteristics. Nevertheless, achieving energy-efficient all-electric synaptic plasticity emulation using SOT devices remains a challenge. The noncollinear antiferromagnetic Mn3Pt is chose as spin source to fabricate the Mn3Pt-based SOT device, leveraging its unconventional spin current resulting from magnetic space breaking. By adjusting the amplitude, duration, and number of pulsed current, the Mn3Pt-based SOT device achieves nonvolatile multi-state modulated by all-electric SOT switching, enabling emulate synaptic behaviors like excitatory postsynaptic potential (EPSP), inhibitory postsynaptic potential (IPSP), long-term depression (LTD), long-term potentiation (LTP), and spike-timing-dependent plasticity (STDP) process. In addition, the successful training of an artificial neural network is showed based on such SOT device in recognizing handwritten digits with a high recognition accuracy of 94.95%, which is only slightly lower than that from simulations (98.04%). These findings suggest that the Mn3Pt-based SOT device is a promising candidate for the implementation of memristor-based brain-inspired computing systems.
| Original language | English |
|---|---|
| Article number | 2400995 |
| Journal | Advanced Electronic Materials |
| Volume | 11 |
| Issue number | 12 |
| DOIs | |
| State | Published - 6 Aug 2025 |
Keywords
- all-electric SOT switching
- artificial synapse
- noncollinear antiferromagnet
- spin-orbit torque
- synaptic plasticity
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