Spin-torque building blocks.

By Nicolas Locatelli, Vincent Cros, Julie Grollier. Nature Materials, 2014

594 citations recorded by the source corpus.

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.

Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0bc5cf8901655df41bbb12864b0cd9854729f77e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

In Electrical and Electronic Engineering

Citations in the corpus

Towards Oxide Electronics: a Roadmap (2019, background): “tion, MTJs have been intensively investigated for applications such as highly sensitive magnetic sensors [503], non-volatile spinbased logics [504], and nanoscale microwave emitters that utilize the spin-torque oscillation effect [505].”
Spin-Torque and Spin-Hall Nano-Oscillators (2015, background): “2(a)] on an extended free layer allow spin-torque-driven emission as well as propagation of spin waves outward from the nanocontact [29], [248].”
Current-induced spin-orbit torques in ferromagnetic and antiferromagnetic systems (2018, background): “(2017) as well as neuromorphic computing architectures (Borders et al., 2018; Locatelli et al., 2014; Sengupta et al., 2015).”
Memory and Information Processing in Neuromorphic Systems (2015, background): “Other approaches that also store memory state as resistance, but that exhibit a range of different behaviors include spin-transfer torque magnetic random access memories (STT–MRAMs) [146]–[148], ferroelectric devices [149], and phase change materials [150]–[152].”
Magnetization oscillations and waves driven by pure spin currents (2016, background): “, [14] and references therein), despite the relatively lowmagnitude of the AMR effect.”