Tag: magnetic dynamics

Chiral magnets in the slow lane

Chiral magnets in the slow lane

A groundbreaking study led by Thorsten Hesjedal, Gerrit van der Laan, and Shilei Zhang from Oxford, Diamond, and ShanghaiTech University has uncovered unexpected slow relaxation processes in chiral magnets, a discovery that challenges the conventional understanding of magnetic dynamics. The study highlights the critical role of topological defects in slowing down the relaxation of non-collinear magnetic states considered for emerging skyrmionics applications.

Exploring non-collinear magnetic orders

Non-collinear magnetic orders, such as spin spirals and skyrmions, have become a central topic in modern magnetism research. These complex magnetic configurations, characterised by twisted spin textures, have topological properties that make them ideal candidates for next-generation spintronic devices. In particular, magnetic skyrmions are small, stable, and can be moved about at minimal energy cost, making them ideal for advanced information storage technologies. 

Typically, when these magnetic textures are disturbed, their relaxation back to equilibrium is believed to occur over a timescale of nanoseconds, as predicted by micromagnetic theories. However, the research team has discovered that under certain conditions, the relaxation processes can extend to hundreds of milliseconds or even seconds.

Revealing the slow dynamics 

In their experiment, the researchers studied the archetypal chiral magnet Cu2OSeO3 using a novel time-resolved resonant elastic X-ray scattering (REXS) technique (Fig a). By applying a pulsed magnetic field and measuring the magnetic order’s response, they were able to capture the entire relaxation process in real-time. Surprisingly, the team found that both the conical and skyrmion lattice phases took up to 0.2 seconds to decay to their equilibrium state – a timescale that is eight orders of magnitude longer than conventional predictions (Fig b). 

This extended relaxation is attributed to the formation of topological defects, such as dislocations and monopoles, located within the magnetic structure. These defects act as localised disturbances, slowing down the relaxation process as the system strives to unwind and return to its lowest energy state. This behaviour contrasts sharply with the rapid dynamics typically expected in magnetic systems and opens up new questions about the underlying physics of topological textures. 

Read more on Diamond website

Image: 3D simulation of the skyrmion lattice. (a) Isosurface visualization (𝑚𝑧=0) of a well-ordered 3D SkX phase. During the relaxation process, topological defects (red dots) emerge that break the local skyrmion strings, as shown in (b) and (c). (d) Shared 2D skyrmion plane, cut from the transparent slices in (a)–(c). The three 𝐐𝑖 wave vectors are shown.

A New Method to Control Magnetic Dynamics in Nanomagnets

A New Method to Control Magnetic Dynamics in Nanomagnets

An ASI (artificial spin ice) is typically an array of small nanomagnets which interact with each other and with external magnetic fields. ASIs are a class of metamaterials (so-called materials of the future), engineered to exhibit unique electromagnetic properties through structured arrangements, differing significantly from the natural behavior of their constituent materials. Recently, ASIs have shown promise for device applications, such as substrates for computation.

These magnetic systems get their name from water ice, where the magnetic moments, or spins, align similar to the hydrogen bonds of ice molecules. ASI nanomagnets are typically blocked (frozen) at room temperature, as the thermal energy is not enough to change their magnetic state. Because there are many magnets, the overall system can have many different states which can be prepared using external magnetic fields.

However until now, these methods have been rather coarse, i.e. they were changing many magnets at a time, in an uncontrolled manner. Or the magnets are written individually, in a non-practical manner, using a scanning probe tip.

Now, scientists from the Norwegian University of Science and Technology have devised a new method called “astroid clocking” that uses a special external field sequence which is able to exactly switch only those elements which are at the border of two regions within the ASI with different states. Thus, it is possible to finely control the state of the ASI array.

The method takes its name from the Stoner–Wohlfarth astroid, a curve that characterizes the critical switching field of a nanomagnet as a function of the angle of the applied magnetic field.  By using this information, the method introduced by the research team make use of the magnetic properties of the individual magnets (the Stoner-Wohlfarth astroid) and the interaction between them (dipolar interaction). This approach enables precise targeting of only the border magnets in a given clock cycle. As the border advances in each cycle, the whole array can be addressed.

Read more on ALBA website

More Brain-like Computers Could Cut IT Energy Costs

More Brain-like Computers Could Cut IT Energy Costs

The dynamics of magnetic metamaterials offer a path to low-energy, next-gen computing

The public launch of OpenAI’s ChatGPT in November 2022 caused a media sensation and kicked off a rapid proliferation of similar Large Language Models (LLMs). However, the computing power needed to train and run these LLMs and other artificial intelligence (AI) systems is colossal, and the energy requirements are staggering. Training the GPT-3 model behind ChatGPT, for example, required 355 years of single-processor computing time and consumed 284,000 kWh of energy1. This is one example of a task that the human brain handles much more efficiently than a traditional computer, and researchers are investigating the potential of more brain-like (neuromorphic) computing methods that may prove to be more energy efficient. Physical reservoir computing is one such method, using the natural, complex responses of materials to perform challenging computations. Researchers from the University of Sheffield are investigating the use of magnetic metamaterials – structured at the nanoscale to exhibit complex and emergent properties – to perform such computations. In work recently published in Communications Physics, they have demonstrated an ability to tune the system to achieve state-of-the-art performance in different types of computation. Their results show that an array of interconnected magnetic nanorings is a promising architecture for neuromorphic computing systems.

Emergence Could Power More Brain-Like Computers

Anyone who has witnessed the majestic and mesmerising flight of a murmuration of starlings has no doubt wondered how a flock of birds can achieve such synchronised behaviour. This is an example of emergence, where the interactions of simple things lead to complex collective behaviours. But emergence doesn’t only occur in the natural world, and a group at the University of Sheffield is investigating how the emergent behaviour can be engineered in magnetic materials when they are patterned to have nanoscale dimensions.

Dr Tom Hayward, Senior Lecturer in Materials Physics at the University of Sheffield and author of this paper says,

Life is inherently emergent – with simple entities connecting together to give complex behaviours that a single element would not have. It’s exciting because we can take simple things – which hypothetically can be very energy efficient – and make them manifest the kind of complexity we see in the brain. Material computation relies on the fact that many materials that exhibit some form of memory can take an input and transform it into a different output – precisely the properties we need to perform computation. Our system connects a series of tiny magnetic rings into a big ensemble. One individual ring in isolation shows quite simple behaviours. But when we connect them, they interact with each other to give complex behaviours.

Magnets have a number of properties that make them interesting for these kinds of applications: 

  • Firstly, they are non-volatile, with inherent memory – if you stick a magnet to your fridge, it stays put.
  • Brains (and brain-like computers) need to have non-linear responses, taking simple information and performing complicated transforms, and that’s something magnets are naturally good at.
  • There are plenty of ways to make magnets change state and perform computations that use very little energy.
  • And magnets are a well-established technology (used, for example, in hard drives and Magnetoresistive random-access memory (MRAM)), and so there are existing routes to technology integration.

XPEEM Highlights the Underlying Magnetic Dynamics

Key to this research is understanding what’s happening to these magnetic nanorings when they’re connected together – the way that emergence changes the way they change magnetic states.

Read more on Diamond website