Unité Mixte de Physique CNRS/Thales, 1 Avenue Augustin Fresnel, Campus de l'Ecole Polytechnique, 91767 Palaiseau, France, and Université Paris-Sud, 91405 Orsay, France.
Nat Mater. 2014 Jan;13(1):11-20. doi: 10.1038/nmat3823.
The discovery of the spin-torque effect has made magnetic nanodevices realistic candidates for active elements of memory devices and applications. Magnetoresistive effects allow the read-out of increasingly small magnetic bits, and the spin torque provides an efficient tool to manipulate - precisely, rapidly and at low energy cost - the magnetic state, which is in turn the central information medium of spintronic devices. By keeping the same magnetic stack, but by tuning a device's shape and bias conditions, the spin torque can be engineered to build a variety of advanced magnetic nanodevices. Here we show that by assembling these nanodevices as building blocks with different functionalities, novel types of computing architecture can be envisaged. We focus in particular on recent concepts such as magnonics and spintronic neural networks.
自旋扭矩效应的发现使磁性纳米器件成为存储器件和应用中主动元件的现实候选者。磁阻效应允许读取越来越小的磁位,而自旋扭矩提供了一种有效的工具来精确、快速和低能耗地操纵磁状态,而磁状态又是自旋电子器件的核心信息介质。通过保持相同的磁堆栈,但通过调整器件的形状和偏置条件,可以设计自旋扭矩来构建各种先进的磁性纳米器件。在这里,我们展示了通过将这些纳米器件组装成具有不同功能的积木,可以设想出新型的计算架构。我们特别关注最近的概念,如磁子学和自旋电子神经网络。