Launching a new dimension with 3D magnetic nanostructures

The scientific and technological exploration of three-dimensional magnetic nanostructures is an emerging research field that opens the path to exciting novel physical phenomena, originating from the increased complexity in spin textures, topology, and frustration in three dimensions. One can also anticipate a tremendous potential for novel applications with those systems in a magnetic sensor and information processing technologies in terms of improved energy efficiency, processing speed, functionalities, and miniaturization of future spintronic devices. These three-dimensional structures are distinct from traditional bulk systems as they harness the scientific achievements of nanomagnetism, which aimed at lowering the dimensions down to the atomic scale, but expand those now in a tailored and designed way into the third dimension. This research update provides an overview of the scientific challenges and recent progress with regard to advances in synthesis approaches and state-of-the-art nanoscale characterization techniques that are prerequisite to understand, realize, and control the properties, behavior, and functionalities of three-dimensional magnetic nanostructures

Tunable stochasticity in an artificial spin network

Metamaterials present the possibility of artificially generating advanced functionalities through engineering of their internal structure. Artificial spin networks, in which a large number of nanoscale magnetic elements are coupled together, are promising metamaterial candidates that enable the control of collective magnetic behavior through tuning of the local interaction between elements. In this work, the motion of magnetic domain-walls in an artificial spin network leads to a tunable stochastic response of the metamaterial, which can be tailored through an external magnetic field and local lattice modifications. This type of tunable stochastic network produces a controllable random response exploiting intrinsic stochasticity within magnetic domain-wall motion at the nanoscale. An iconic demonstration used to illustrate the control of randomness is the Galton board. In this system, multiple balls fall into an array of pegs to generate a bell-shaped curve that can be modified via the array spacing or the tilt of the board. A nanoscale recreation of this experiment using an artificial spin network is employed to demonstrate tunable stochasticity. This type of tunable stochastic network opens new paths towards post-Von Neumann computing architectures such as Bayesian sensing or random neural networks, in which stochasticity is harnessed to efficiently perform complex computational tasks.Comment: 24 pages, 10 figure

Fabrication, Detection, and Operation of a Three-Dimensional Nanomagnetic Conduit.

Three-dimensional (3D) nanomagnetic devices are attracting significant interest due to their potential for computing, sensing, and biological applications. However, their implementation faces great challenges regarding fabrication and characterization of 3D nanostructures. Here, we show a 3D nanomagnetic system created by 3D nanoprinting and physical vapor deposition, which acts as a conduit for domain walls. Domains formed at the substrate level are injected into a 3D nanowire, where they are controllably trapped using vectorial magnetic fields. A dark-field magneto-optical method for parallel, independent measurement of different regions in individual 3D nanostructures is also demonstrated. This work will facilitate the advanced study and exploitation of 3D nanomagnetic systems

RF signal classification in hardware with an RF spintronic neural network

Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications. Here we show how to leverage the intrinsic dynamics of spintronic nanodevices called magnetic tunnel junctions to process multiple analogue RF inputs in parallel and perform synaptic operations. Furthermore, we achieve classification of RF signals with experimental data from magnetic tunnel junctions as neurons and synapses, with the same accuracy as an equivalent software neural network. These results are a key step for embedded radiofrequency artificial intelligence.Comment: 8 pages, 5 figure

Neuromorphic weighted sum with magnetic skyrmions

Integrating magnetic skyrmion properties into neuromorphic computing promises advancements in hardware efficiency and computational power. However, a scalable implementation of the weighted sum of neuron signals, a core operation in neural networks, has yet to be demonstrated. In this study, we exploit the non-volatile and particle-like characteristics of magnetic skyrmions, akin to synaptic vesicles and neurotransmitters, to perform this weighted sum operation in a compact, biologically-inspired manner. To this aim, skyrmions are electrically generated in numbers proportional to the input with an efficiency given by a non-volatile weight. These chiral particles are then directed using localized current injections to a location where their presence is quantified through non-perturbative electrical measurements. Our experimental demonstration, currently with two inputs, can be scaled to accommodate multiple inputs and outputs using a crossbar array design, potentially nearing the energy efficiency observed in biological systems.Comment: 12 pages, 5 figure

Fabrication of Scaffold-Based 3D Magnetic Nanowires for Domain Wall Applications.

Three-dimensional magnetic nanostructures hold great potential to revolutionize information technologies and to enable the study of novel physical phenomena. In this work, we describe a hybrid nanofabrication process combining bottom-up 3D nano-printing and top-down thin film deposition, which leads to the fabrication of complex magnetic nanostructures suitable for the study of new 3D magnetic effects. First, a non-magnetic 3D scaffold is nano-printed using Focused Electron Beam Induced Deposition; then a thin film magnetic material is thermally evaporated onto the scaffold, leading to a functional 3D magnetic nanostructure. Scaffold geometries are extended beyond recently developed single-segment geometries by introducing a dual-pitch patterning strategy. Additionally, by tilting the substrate during growth, low-angle segments can be patterned, circumventing a major limitation of this nano-printing process; this is demonstrated by the fabrication of ‘staircase’ nanostructures with segments parallel to the substrate. The suitability of nano-printed scaffolds to support thermally evaporated thin films is discussed, outlining the importance of including supporting pillars to prevent deformation during the evaporation process. Employing this set of methods, a set of nanostructures tailored to precisely match a dark-field magneto-optical magnetometer have been fabricated and characterized. This work demonstrates the versatility of this hybrid technique and the interesting magnetic properties of the nanostructures produced, opening a promising route for the development of new 3D devices for applications and fundamental studies

Complex free-space magnetic field textures induced by three-dimensional magnetic nanostructures.

The design of complex, competing effects in magnetic systems-be it via the introduction of nonlinear interactions1-4, or the patterning of three-dimensional geometries5,6-is an emerging route to achieve new functionalities. In particular, through the design of three-dimensional geometries and curvature, intrastructure properties such as anisotropy and chirality, both geometry-induced and intrinsic, can be directly controlled, leading to a host of new physics and functionalities, such as three-dimensional chiral spin states7, ultrafast chiral domain wall dynamics8-10 and spin textures with new spin topologies7,11. Here, we advance beyond the control of intrastructure properties in three dimensions and tailor the magnetostatic coupling of neighbouring magnetic structures, an interstructure property that allows us to generate complex textures in the magnetic stray field. For this, we harness direct write nanofabrication techniques, creating intertwined nanomagnetic cobalt double helices, where curvature, torsion, chirality and magnetic coupling are jointly exploited. By reconstructing the three-dimensional vectorial magnetic state of the double helices with soft-X-ray magnetic laminography12,13, we identify the presence of a regular array of highly coupled locked domain wall pairs in neighbouring helices. Micromagnetic simulations reveal that the magnetization configuration leads to the formation of an array of complex textures in the magnetic induction, consisting of vortices in the magnetization and antivortices in free space, which together form an effective B field cross-tie wall14. The design and creation of complex three-dimensional magnetic field nanotextures opens new possibilities for smart materials15, unconventional computing2,16, particle trapping17,18 and magnetic imaging19.EPSRC Early Career Fellowship EP/M008517/1 Winton Program for the Physics of Sustainability Leverhulme Trust (ECF-2018-016) Isaac Newton Trust (18-08) L’Oréal-UNESCO UK and Ireland Fellowship For Women In Science 2019 European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant ref. H2020-MSCA-IF-2016-746958 Spanish AEI under project reference PID2019–104604RB/AEI/10.13039/501100011033 German Ministerium für Bildung und Forschung (BMBF) through contracts 05K16WED and 05K19WE2 European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 701647 FWF project I 4917

Multilayer spintronic neural networks with radio-frequency connections

Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided that they implement state-of-the art deep neural networks. However, there is today no scalable way to connect them in multilayers. Here we show that the flagship nano-components of spintronics, magnetic tunnel junctions, can be connected into multilayer neural networks where they implement both synapses and neurons thanks to their magnetization dynamics, and communicate by processing, transmitting and receiving radio frequency (RF) signals. We build a hardware spintronic neural network composed of nine magnetic tunnel junctions connected in two layers, and show that it natively classifies nonlinearly-separable RF inputs with an accuracy of 97.7%. Using physical simulations, we demonstrate that a large network of nanoscale junctions can achieve state-of the-art identification of drones from their RF transmissions, without digitization, and consuming only a few milliwatts, which is a gain of more than four orders of magnitude in power consumption compared to currently used techniques. This study lays the foundation for deep, dynamical, spintronic neural networks

Fabrication and Characterization of Three-Dimensional Magnetic Nanostructures

Today, two-dimensional nanoscale magnetic systems are well understood, being used in applications from spintronic circuits to automotive sensing. Despite the great progress achieved in the field during the last decades, the development of three-dimensional devices is still hindered by phenomenal patterning and characterization challenges. Most lithographic and probing techniques have historically targeted planar samples and are not suitable for three dimensional geometries. This thesis achieves three key points to overcome these fabrication and characterization challenges: improving the understanding and control of 3D nano-printing of cobalt nanostructures using Focused Electron Beam Induced Deposition (FEBID), improving the performance of synchrotron-based magnetic X-ray microscopy in 3D geometries and adapting existing magneto-optical techniques to rapidly probe 3D nanostructures in the lab. As a result of this work, new tools and skills are available in the field of 3D nano-magnetism, unlocking a path for the development of sophisticated 3D nanomagnetic devices with increased functionality and performance.Girton College Pfeiffer Graduate Scholarship Winton Fund for the Physics of Sustainabilit