A spin wave driven skyrmion-based diode on a T-shaped nanotrack

Saini, Shipra; Bindal, Namita; Raj, Ravish Kumar; Kaushik, Brajesh Kumar

doi:10.1039/d4nr00482e

Nanoscale

2024

DOI: 10.1039/d4nr00482e

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A spin wave driven skyrmion-based diode on a T-shaped nanotrack

Shipra Saini,

Namita Bindal,

Ravish Kumar Raj

et al.

Abstract: Utilizing spin waves driven skyrmion, a T-shaped nanotrack enables diode functionality, crucial for spintronic devices. It is achieved with 60–80 GHz and 0.07–0.4 T field, offering speed upto 100 m s−1. This innovation heralds non-charge-based device.

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Cited by 3 publications

References 43 publications

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Dzyaloshinskii–Moriya interaction gradient driven skyrmion based energy efficient leaky integrate fire neuron

Raj,

Saini,

Verma

et al. 2025

Journal of Magnetism and Magnetic Materials

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Dzyaloshinskii–Moriya interaction gradient driven skyrmion based energy efficient leaky integrate fire neuron

Raj,

Saini,

Verma

et al. 2025

Journal of Magnetism and Magnetic Materials

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Antiferromagnetic skyrmion dynamics in stepped geometry for various applications

Saini,

Verma,

Kaushik

2024

Journal of Applied Physics

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Antiferromagnetic skyrmions are tiny particle like spin textures, topologically more stable, having low depinning current density. They are potential candidate for spintronics devices owing to their robustness toward external magnetic field perturbations. Precise control of the skyrmion motion is essential for applications such as racetrack memories, multistate memories, and neuromorphic computing devices. However, in conventional nanotracks, these particles could not be stabilized due to inter-skyrmion repulsion. Hence, in the case of domain wall-based racetracks and multi-state memory devices, extra notches or similar geometric confinements are included within the nanotrack. Here, we show that a stepped nanotrack geometry is one possible solution for controlling the skyrmion dynamics that can be further employed in racetrack memory, multistate memory, and leaky integrate-and-fire neuron devices. Compared to the domain wall depinning current density of ∼1011–1012 A/m2, only ∼106 A/m2 is required for skyrmions. Additionally, we observe that the modified skyrmion racetracks with stepped geometry can mimic the functionality of the biological neuron, including the leaky behavior, eliminating the need for an anisotropy gradient, Dzyaloshinskii–Moriya interaction gradient, or thermal gradient, which is required for the case of domain wall nanotrack. The current density required to drive the skyrmions on this modified nanotrack is ∼1010 A/m2. The effects of defects and edge roughness due to the fabrication process are also studied.

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Multitask Learning for Estimation of Magnetic Parameters Using Pattern Recognition

Sehgal,

Saini,

Nehete

et al. 2024

IEEE Open J. Nanotechnol.

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A spin wave driven skyrmion-based diode on a T-shaped nanotrack

Abstract: Utilizing spin waves driven skyrmion, a T-shaped nanotrack enables diode functionality, crucial for spintronic devices. It is achieved with 60–80 GHz and 0.07–0.4 T field, offering speed upto 100 m s−1. This innovation heralds non-charge-based device.

Cited by 3 publications

References 43 publications

Dzyaloshinskii–Moriya interaction gradient driven skyrmion based energy efficient leaky integrate fire neuron

Dzyaloshinskii–Moriya interaction gradient driven skyrmion based energy efficient leaky integrate fire neuron

Antiferromagnetic skyrmion dynamics in stepped geometry for various applications

Multitask Learning for Estimation of Magnetic Parameters Using Pattern Recognition

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