{"title":"Antiferromagnetic Skyrmion based Energy-Efficient Leaky Integrate and Fire Neuron Device.","authors":"Namita Bindal, Md Mahadi Rajib, Ravish Kumar Raj, Jayasimha Atulasimha, Brajesh Kumar Kaushik","doi":"10.1088/1361-6528/adb8c1","DOIUrl":null,"url":null,"abstract":"<p><p>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 over 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 alternatively a perpendicular magnetic anisotropy (PMA) gradient in the nanotrack for leaky behavior by moving the skyrmion in the hotter or lower PMA region, 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 (MTJ) enabling efficient read-out of the skyrmion. The maximum change of 9.2% in tunnel magnetoresistance (TMR) 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 path for developing energy-efficient devices in AFM spintronics for neuromorphic computing.</p>","PeriodicalId":19035,"journal":{"name":"Nanotechnology","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanotechnology","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-6528/adb8c1","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Antiferromagnetic Skyrmion based Energy-Efficient Leaky Integrate and Fire Neuron Device.
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 over 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 alternatively a perpendicular magnetic anisotropy (PMA) gradient in the nanotrack for leaky behavior by moving the skyrmion in the hotter or lower PMA region, 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 (MTJ) enabling efficient read-out of the skyrmion. The maximum change of 9.2% in tunnel magnetoresistance (TMR) 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 path for developing energy-efficient devices in AFM spintronics for neuromorphic computing.
期刊介绍:
The journal aims to publish papers at the forefront of nanoscale science and technology and especially those of an interdisciplinary nature. Here, nanotechnology is taken to include the ability to individually address, control, and modify structures, materials and devices with nanometre precision, and the synthesis of such structures into systems of micro- and macroscopic dimensions such as MEMS based devices. It encompasses the understanding of the fundamental physics, chemistry, biology and technology of nanometre-scale objects and how such objects can be used in the areas of computation, sensors, nanostructured materials and nano-biotechnology.