As the application potential of two-dimensional(2D)materials in fields such as nanoelectronics,optoelectronics,and quantum computing continues to grow,the challenge of fabricating high-quality dielectric layers has become crucial to the performance of 2D devices[1],[2].
Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.
电子自旋属性的自旋电子器件,由于其低能耗、高效率和强稳定性等特点,在磁性存储和计算技术的发展中发挥了重大作用。而如何以一种高能效、确定性和可扩展的方式对作为信息载体的磁性进行操控,这个重要问题在自旋电子学领域引起了利用电流操控磁化翻转的广泛研究。本文综述了利用自旋极化电流和纯自旋流操控磁化翻转的研究背景、重要工作和最新进展,详细介绍了自旋转移矩(spin transfer torque,STT)和自旋轨道矩(spinorbit torque,SOT)的产生和作用机制,重点阐述了利用SOT驱动磁畴壁运动和垂直磁化翻转,以及无外磁场磁化翻转的原理。最后探讨了SOT在人工合成反铁磁(synthetic antiferromagnet,SAF)结构中驱动的磁化翻转,为人工合成反铁磁体作为磁性随机访问存储器(magnetic random access memory,MRAM)的应用提供了重要基础,同时也为纯电流操控的自旋电子存储器件相关研究提供了有价值的参考。
