Ojha Durgesh Kumar, Huang Yu-Hsin, Lin Yu-Lon, Chatterjee Ratnamala, Chang Wen-Yueh, Tseng Yuan-Chieh
International College of Semiconductor Technology, National Yang-Ming Chiao Tung University, Hsinchu 30010, Taiwan, ROC.
Magnetics and Advance Ceramics Lab, Department of Physics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.
Nano Lett. 2024 Jun 26;24(25):7706-7715. doi: 10.1021/acs.nanolett.4c01712. Epub 2024 Jun 13.
Field-free switching (FFS) and spin-orbit torque (SOT)-based neuromorphic characteristics were realized in a W/Pt/Co/NiO/Pt heterostructure with a perpendicular exchange bias () for brain-inspired neuromorphic computing (NC). Experimental results using NiO-based SOT devices guided the development of fully spin-based artificial synapses and sigmoidal neurons for implementation in a three-layer artificial neural network. This system achieved impressive accuracies of 91-96% when applied to the Modified National Institute of Standards and Technology (MNIST) image data set and 78.85-81.25% when applied to Fashion MNIST images, due presumably to the emergence of robust NiO antiferromagnetic (AFM) ordering. The emergence of AFM ordering favored the FFS with an enhanced , which suppressed the memristivity and reduced the recognition accuracy. This indicates a trade-off between the requirements for solid-state memory and those required for brain-inspired NC devices. Nonetheless, our findings revealed opportunities by which the two technologies could be aligned via controllable exchange coupling.
在具有垂直交换偏置（）的W/Pt/Co/NiO/Pt异质结构中实现了用于脑启发神经形态计算（NC）的无场切换（FFS）和基于自旋轨道矩（SOT）的神经形态特性。使用基于NiO的SOT器件的实验结果指导了用于三层人工神经网络的全自旋人工突触和S形神经元的开发。当应用于修改后的美国国家标准与技术研究院（MNIST）图像数据集时，该系统实现了91-96%的令人印象深刻的准确率，当应用于时尚MNIST图像时，准确率为78.85-81.25%，这可能是由于强大的NiO反铁磁（AFM）有序的出现。AFM有序的出现有利于具有增强的FFS，这抑制了忆阻率并降低了识别准确率。这表明在固态存储器的要求与脑启发NC器件所需的要求之间存在权衡。尽管如此，我们的研究结果揭示了通过可控交换耦合使这两种技术对齐的机会。
