自旋传递转矩和电压控制应变梯度对磁畴壁动力学的联合影响:迈向可调谐的自旋电子神经元

IF 3.5 2区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Chinese Physics Letters Pub Date : 2024-04-17 DOI:10.1088/0256-307x/41/5/057502
Guo-Liang Yu, Xin-Yan He, Sheng-Bin Shi, Yang Qiu, Mingmin Zhu, Jia-Wei Wang, Yan Li, Yuan-Xun Li, Jie Wang, Haomiao Zhou
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引用次数: 0

摘要

磁畴壁(DW)是自旋电子器件中极具前景的信息载体之一,由于其非线性动力学和可调谐特性而受到广泛研究。在这里,我们从理论和数值上证明了多铁氧体异质结构中电流诱导的自旋转移力矩(STT)和电压控制应变梯度(VCSG)之间的协同作用所驱动的磁畴壁动力学。通过机电和微磁模拟,我们证明可以产生理想的应变梯度,并进一步调制电流驱动 DW 运动的平衡位置和速度。同时,我们还建立了一个蒂勒分析模型来描述 DW 的稳定运动,分析结果与模拟结果相当吻合。最后,我们发现可以利用这种组合效应来设计基于 DW 的生物神经元,其中 STT 和 VCSG 驱动的 DW 运动作为整合和泄漏的协同交互作用激发了模仿泄漏-整合-发射(LIF)和自复位功能。重要的是,LIF 神经元的点火响应可以被有效调制,从而促进对可调激活函数发生器的探索,这有助于进一步提高神经形态系统的计算能力。
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The Combined Effect of Spin-transfer Torque and Voltage-controlled Strain Gradient on Magnetic Domain-wall Dynamics: Toward Tunable Spintronic Neuron
Magnetic domain wall (DW), as one of the promising information carriers in spintronic devices, have been widely investigated owing to their nonlinear dynamics and tunable properties. Here, we have theoretically and numerically demonstrated the DW dynamics driven by the synergistic interaction between current-induced spintransfer torque (STT) and voltage-controlled strain gradient (VCSG) in multiferroic heterostructures. Through electromechanical and micromagnetic simulations, we have shown that a desirable strain gradient can be created and further modulated the equilibrium position and velocity of the current-driven DW motion. Meanwhile, an analytical Thiele’s model is developed to describe the steady motion of DW and the analytical results are quite consistent with the simulation one. Finally, we find that this combination effect can be leveraged to design DW-based biological neurons where the synergistic interaction between STT and VCSG-driven DW motion as integrating and leaking motivates mimicking leaky-integrate-and-fire (LIF) and self-reset function. Importantly, the firing response of the LIF neuron can be efficiently modulated, facilitating the exploration of tunable activation function generators, which can further help improve the computational capability of the neuromorphic system.
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来源期刊
Chinese Physics Letters
Chinese Physics Letters 物理-物理:综合
CiteScore
5.90
自引率
8.60%
发文量
13238
审稿时长
4 months
期刊介绍: Chinese Physics Letters provides rapid publication of short reports and important research in all fields of physics and is published by the Chinese Physical Society and hosted online by IOP Publishing.
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