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苯基单分子磁隧道结中自旋极化电导的电压依赖性。

Voltage-dependent plasticity of spin-polarized conductance in phenyl-based single-molecule magnetic tunnel junctions.

机构信息

Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran.

Department of Physics, University of Guilan, Rasht, Iran.

出版信息

PLoS One. 2021 Sep 10;16(9):e0257228. doi: 10.1371/journal.pone.0257228. eCollection 2021.

Abstract

Synaptic strengths between neurons in brain networks are highly adaptive due to synaptic plasticity. Spike-timing-dependent plasticity (STDP) is a form of synaptic plasticity induced by temporal correlations between the firing activity of neurons. The development of experimental techniques in recent years enabled the realization of brain-inspired neuromorphic devices. Particularly, magnetic tunnel junctions (MTJs) provide a suitable means for the implementation of learning processes in molecular junctions. Here, we first considered a two-neuron motif subjected to STDP. By employing theoretical analysis and computer simulations we showed that the dynamics and emergent structure of the motif can be predicted by introducing an effective two-neuron synaptic conductance. Then, we considered a phenyl-based single-molecule MTJ connected to two ferromagnetic (FM) cobalt electrodes and investigated its electrical properties using the non-equilibrium Green's function (NEGF) formalism. Similar to the two-neuron motif, we introduced an effective spin-polarized conductance in the MTJ. Depending on the polarity, frequency and strength of the bias voltage applied to the MTJ, the system can learn input signals by adaptive changes of the effective conductance. Interestingly, this voltage-dependent plasticity is an intrinsic property of the MTJ where its behavior is reminiscent of the classical temporally asymmetric STDP. Furthermore, the shape of voltage-dependent plasticity in the MTJ is determined by the molecule-electrode coupling strength or the length of the molecule. Our results may be relevant for the development of single-molecule devices that capture the adaptive properties of synapses in the brain.

摘要

由于突触可塑性,神经元之间的脑网络突触强度具有高度适应性。尖峰时间依赖性可塑性(STDP)是一种由神经元放电活动之间的时间相关性引起的突触可塑性形式。近年来,实验技术的发展使人们能够实现受大脑启发的神经形态器件。特别是,磁隧道结(MTJ)为在分子结中实现学习过程提供了一种合适的手段。在这里,我们首先考虑了一个受 STDP 影响的双神经元模型。通过理论分析和计算机模拟,我们表明通过引入有效的双神经元突触电导,可以预测模型的动力学和涌现结构。然后,我们考虑了一个连接到两个铁磁(FM)钴电极的苯基单分子 MTJ,并使用非平衡格林函数(NEGF)形式主义研究了其电特性。与双神经元模型类似,我们在 MTJ 中引入了有效的自旋极化电导。根据施加到 MTJ 的偏置电压的极性、频率和强度,系统可以通过有效电导的自适应变化来学习输入信号。有趣的是,这种电压依赖性可塑性是 MTJ 的固有特性,其行为类似于经典的时间不对称 STDP。此外,MTJ 中电压依赖性可塑性的形状由分子-电极耦合强度或分子长度决定。我们的结果可能与开发能够捕捉大脑中突触适应性特性的单分子器件有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ea7/8432808/0af942fb6075/pone.0257228.g001.jpg

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