Leaky-integrate-fire and reconfigurable neuron spiking in a field free spin Hall nano-oscillator with a conically magnetized free layer

Spintronic oscillators being highly nonlinear have gained immense attention to mimic the neuron spiking behavior in spiking neural networks used for building neuromorphic computing hardware. However, the need for an external magnetic field to realize spintronic oscillators imposes significant limitations on their scalability, tunability, and fabrication complexity. So, in this study, we have realized a bias-field-free spin Hall nano-oscillator (SHNO) using a heavy metal/magnetic tunnel junction (MTJ) heterostructure. The field-free operation is achieved by biasing the free layer of the MTJ into an easy cone regime. This regime arises when the first-order magnetic anisotropy field and the demagnetization field are balanced, and the influence of the second-order magnetic anisotropy becomes predominant. We have explored the oscillation properties of this field-free SHNO, focusing on frequency tunability with current and the output power spectral density through the macrospin and micromagnetic simulations. We have theoretically derived the critical current necessary for the onset of oscillations. Using this field-free SHNO, we demonstrated neuron-like spiking behavior analogous to the Hodgkin–Huxley model by applying a constant DC current. The tunability of spiking frequency in response to input current was also examined. Moreover, we showcased leaky-integrate-and-fire neuron spiking behavior by applying a pulsed current and the reconfigurable nature of neuron spiking under a time-varying ramp current. These spiking behaviors underline the potential applications of this device in the practical realization of brain-inspired neuromorphic computing with the spiking neural network.

Authors

Institutions

Publication Details

Journal
Journal of Applied Physics
Published
2025-01-27
DOI
https://doi.org/10.1063/5.0235639
Citations
2
Primary Topic
Magnetic properties of thin films
Type
article
Field-Weighted Citation Impact
2.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Leaky-integrate-fire and reconfigurable neuron spiking in a field free spin Hall nano-oscillator with a conically magnetized free layer

Swapnil Bhuktare, Meenakshi Sravani
2 citations
Journal of Applied Physics
Magnetic properties of thin films
2.49
article

Leaky-integrate-fire and reconfigurable neuron spiking in a field free spin Hall nano-oscillator with a conically magnetized free layer

Swapnil Bhuktare, Meenakshi Sravani
article en
2 citations

Abstract

Spintronic oscillators being highly nonlinear have gained immense attention to mimic the neuron spiking behavior in spiking neural networks used for building neuromorphic computing hardware. However, the need for an external magnetic field to realize spintronic oscillators imposes significant limitations on their scalability, tunability, and fabrication complexity. So, in this study, we have realized a bias-field-free spin Hall nano-oscillator (SHNO) using a heavy metal/magnetic tunnel junction (MTJ) heterostructure. The field-free operation is achieved by biasing the free layer of the MTJ into an easy cone regime. This regime arises when the first-order magnetic anisotropy field and the demagnetization field are balanced, and the influence of the second-order magnetic anisotropy becomes predominant. We have explored the oscillation properties of this field-free SHNO, focusing on frequency tunability with current and the output power spectral density through the macrospin and micromagnetic simulations. We have theoretically derived the critical current necessary for the onset of oscillations. Using this field-free SHNO, we demonstrated neuron-like spiking behavior analogous to the Hodgkin–Huxley model by applying a constant DC current. The tunability of spiking frequency in response to input current was also examined. Moreover, we showcased leaky-integrate-and-fire neuron spiking behavior by applying a pulsed current and the reconfigurable nature of neuron spiking under a time-varying ramp current. These spiking behaviors underline the potential applications of this device in the practical realization of brain-inspired neuromorphic computing with the spiking neural network.

Journal of Applied PhysicsVol. 137(4)
Indian Institute of Technology Tirupati (IN)
Science and Engineering Research Board
Openalex Percentile: Top 14%
Magnetic properties of thin films
2.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.