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倾斜各向异性磁隧道结中自旋轨道扭矩与内置场的协同作用:实现可调谐和可靠的自旋电子神经元。

Synergy of Spin-Orbit Torque and Built-In Field in Magnetic Tunnel Junctions with Tilted Magnetic Anisotropy: Toward Tunable and Reliable Spintronic Neurons.

机构信息

Key Laboratory of Microelectronic Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.

School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, China.

出版信息

Adv Sci (Weinh). 2022 Oct;9(30):e2203006. doi: 10.1002/advs.202203006. Epub 2022 Aug 4.

DOI:10.1002/advs.202203006
PMID:35927016
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9596820/
Abstract

Owing to programmable nonlinear dynamics, magnetic domain wall (DW)-based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy-efficient, CMOS compatible, reliable, and tunable spintronic neurons to emulate brain-inspired processes has been a key research goal for decades. Here, a new type of DW device is reported with biological neuron characteristics driven by the synergistic interaction between spin-orbit torque and built-in field (H ) in magnetic tunnel junctions, enabling time- and energy-efficient leaky-integrate-and-fire and self-reset neuromorphic implementations. A tilted magnetic anisotropic free layer is proposed and further executed to mitigate the DW retrograde motion by suppressing the Walker breakdown. Complementary experiments and micromagnetic co-simulation results show that the integrating/leaking time of the developed spintronic neuron can be tuned to 12/15 ns with an integrating power consumption of 65 µW, which is 36× and 1.84× time and energy efficient than the state-of-the-art alternatives, respectively. Moreover, the spatial distribution of H can be modulated by adjusting the width and compensation of the reference layer, facilitating tunable activation function generator exploration. Such architecture demonstrates great potential in both fundamental research and new trajectories of technology advancement for spintronic neuron hardware applications.

摘要

由于可编程的非线性动力学,基于磁畴壁 (DW) 的器件可以被配置为作为自旋电子神经元工作,有望执行复杂的任务,就像人类大脑一样。几十年来,开发具有能量效率、CMOS 兼容性、可靠性和可调谐性的自旋电子神经元,以模拟受大脑启发的过程一直是一个关键的研究目标。在这里,报道了一种新型的 DW 器件,具有由自旋轨道扭矩和内置场 (H) 在磁性隧道结中的协同作用驱动的生物神经元特性,从而能够实现高效的时间和能量的漏积分和放电以及自重置神经形态实现。提出并进一步执行了倾斜磁各向异性自由层,通过抑制 Walker 击穿来抑制 DW 逆行运动。互补实验和微磁共模拟结果表明,开发的自旋电子神经元的积分/泄漏时间可以调节为 12/15 ns,积分功耗为 65 µW,分别比现有技术提高了 36 倍和 1.84 倍的时间和能量效率。此外,通过调整参考层的宽度和补偿,可以调制 H 的空间分布,从而有利于可调谐激活函数发生器的探索。这种架构在自旋电子神经元硬件应用的基础研究和技术进步的新轨迹方面都具有巨大的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/db9c441e11de/ADVS-9-2203006-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/b1bf54ec1b11/ADVS-9-2203006-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/4b9006ef8c85/ADVS-9-2203006-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/299c39eaabbf/ADVS-9-2203006-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/8baac1b5d699/ADVS-9-2203006-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/db9c441e11de/ADVS-9-2203006-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/b1bf54ec1b11/ADVS-9-2203006-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/4b9006ef8c85/ADVS-9-2203006-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/299c39eaabbf/ADVS-9-2203006-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/8baac1b5d699/ADVS-9-2203006-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f7d9/9596820/db9c441e11de/ADVS-9-2203006-g001.jpg

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本文引用的文献

1
Roadmap of spin-orbit torques.自旋轨道扭矩路线图。
IEEE Trans Magn. 2021;57(7). doi: 10.48550/arXiv.2104.11459.
2
Experimental demonstration of skyrmionic magnetic tunnel junction at room temperature.室温下的斯格明子磁隧道结的实验演示。
Sci Bull (Beijing). 2022 Apr 15;67(7):691-699. doi: 10.1016/j.scib.2022.01.016. Epub 2022 Jan 15.
3
A crossbar array of magnetoresistive memory devices for in-memory computing.用于内存计算的磁阻式存储器件的交叉开关阵列。
用于全自旋神经形态硬件的基于畴壁磁隧道结的人工突触和神经元。
Nat Commun. 2024 May 28;15(1):4534. doi: 10.1038/s41467-024-48631-4.
4
Spintronic leaky-integrate-fire spiking neurons with self-reset and winner-takes-all for neuromorphic computing.用于神经形态计算的具有自复位和胜者全拿功能的自旋电子泄漏积分点火尖峰神经元。
Nat Commun. 2023 Feb 24;14(1):1068. doi: 10.1038/s41467-023-36728-1.
Nature. 2022 Jan;601(7892):211-216. doi: 10.1038/s41586-021-04196-6. Epub 2022 Jan 12.
4
Controlled Switching of the Number of Skyrmions in a Magnetic Nanodot by Electric Fields.通过电场对磁性纳米点中斯格明子数量进行可控切换。
Adv Mater. 2022 Mar;34(11):e2107908. doi: 10.1002/adma.202107908. Epub 2022 Feb 4.
5
Reducing Dzyaloshinskii-Moriya interaction and field-free spin-orbit torque switching in synthetic antiferromagnets.降低合成反铁磁体中的Dzyaloshinskii-Moriya相互作用和无外场自旋轨道矩开关效应
Nat Commun. 2021 May 25;12(1):3113. doi: 10.1038/s41467-021-23414-3.
6
Neuromorphic Spintronics.神经形态自旋电子学
Nat Electron. 2020;3(7). doi: 10.1038/s41928-019-0360-9.
7
Emerging Materials for Neuromorphic Devices and Systems.用于神经形态设备和系统的新兴材料。
iScience. 2020 Nov 24;23(12):101846. doi: 10.1016/j.isci.2020.101846. eCollection 2020 Dec 18.
8
Prospect of Spin-Orbitronic Devices and Their Applications.自旋轨道电子学器件及其应用前景。
iScience. 2020 Sep 28;23(10):101614. doi: 10.1016/j.isci.2020.101614. eCollection 2020 Oct 23.
9
Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks.具有时空动态和增益调制的尖峰神经元,用于单片集成的忆阻神经网络。
Nat Commun. 2020 Jul 7;11(1):3399. doi: 10.1038/s41467-020-17215-3.
10
Memory devices and applications for in-memory computing.用于内存计算的存储设备和应用。
Nat Nanotechnol. 2020 Jul;15(7):529-544. doi: 10.1038/s41565-020-0655-z. Epub 2020 Mar 30.