Antiferromagnetic skyrmion-based energy-efficient leaky integrate and fire neuron device

被引:0
|
作者
Bindal, Namita [1 ,2 ]
Rajib, Md Mahadi [4 ]
Raj, Ravish Kumar [2 ,3 ]
Atulasimha, Jayasimha [4 ,5 ]
Kaushik, Brajesh Kumar [2 ]
机构
[1] MVJ Coll Engn, Dept Elect & Commun Engn, Bangalore 560037, India
[2] Indian Inst Technol Roorkee, Dept Elect & Commun Engn, Roorkee 247667, Uttarakhand, India
[3] Aarhus Univ, Dept Elect & Comp Engn, Elect & Photon Sect, DK-8000 Aarhus N, Denmark
[4] Virginia Commonwealth Univ, Dept Mech & Nucl Engn, Richmond, VA 23284 USA
[5] Virginia Commonwealth Univ, Dept Elect & Comp Engn, Richmond, VA 23284 USA
基金
美国国家科学基金会;
关键词
antiferromagnets; leaky-integrate-fire; neuron; spin-orbit-torque; thermal gradient; LATTICE; STATES;
D O I
10.1088/1361-6528/adb8c1
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
The development of energy-efficient neuromorphic hardware using spintronic devices based on antiferromagnetic (AFM) skyrmion motion on nanotracks has gained considerable interest. Owing to their properties such as robustness against external magnetic fields, negligible stray fields, and zero net topological charge, AFM skyrmions follow straight trajectories that prevent their annihilation at nanoscale racetrack edges. This makes the AFM skyrmions a more favorable candidate than the ferromagnetic (FM) skyrmions for future spintronic applications. This work proposes an AFM skyrmion-based neuron device exhibiting the leaky-integrate-fire (LIF) functionality by exploiting either a thermal gradient or a perpendicular magnetic anisotropy (PMA) gradient in the nanotrack for leaky behavior by moving the skyrmion in the hotter region or the region with lower PMA, respectively, to minimize the system energy. Furthermore, it is shown that the AFM skyrmion couples efficiently to the soft FM layer of a magnetic tunnel junction, enabling efficient read-out of the skyrmion. The maximum change of 9.2% in tunnel magnetoresistance is estimated while detecting the AFM skyrmion. Moreover, the proposed neuron device has an energy dissipation of 4.32 fJ per LIF operation, thus paving the way for developing energy-efficient devices in AFM spintronics for neuromorphic computing.
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页数:10
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