Spintronic Memtransistor Leaky Integrate and Fire Neuron for Spiking Neural Networks

Abstract Spintronic devices based on DWss and skyrmions have shown significant potential for applications in energy‐efficient data storage and beyond CMOS computing architectures. Based on the ferromagnetic multilayer spintronic devices, a magnetic field‐gated and current‐controlled spintronic Leaky Integrate‐and‐Fire (LIF) neuron with memtransistor properties is showcased. The memtransistor property allows for tuning firing characteristics through external magnetic fields and current pulses. A LIF neuron model is developed based on measured characteristics to integrate the device into system‐level Spiking Neural Networks (SNNs). The scalability of the neuron device is confirmed with the micromagnetic simulations in a domain‐wall magnetic tunnel junction device. When integrated into SNN and convolutional SNN frameworks, the device achieves classification precision above 96%. The study highlights the device's potential as a neuron in hardware SNN architecture‐based neuromorphic computing applications, combining memtransistor properties of the device and high pattern classification accuracy. The results demonstrate a promising path toward developing energy‐efficient and scalable neural networks.