Researchers from the University of Missouri and Oak Ridge National Laboratory have discovered a new type of quasiparticle found in all magnetic materials, no matter their strength or temperature. These new properties shake up what researchers previously knew about magnetism, showing it’s not as static as once believed.

“We’ve all seen the bubbles that form in sparkling water or other carbonated drink products,” said Ullrich, Curators’ Distinguished Professor of Physics and Astronomy. “The quasiparticles are like those bubbles, and we found they can freely move around at remarkably fast speeds”. This discovery could help the development of a new generation of electronics that are faster, smarter and more energy efficient. But first, scientists need to determine how this finding could work into those processes.

Researchers at Tohoku University and the University of California, Santa Barbara, have developed new computing hardware that utilizes a Gaussian probabilistic bit made from a stochastic spintronics device. This innovation is expected to provide an energy-efficient platform for generative AI.

As Moore's Law slows down, domain-specific hardware architectures - such as probabilistic computing with naturally stochastic building blocks - are gaining prominence for addressing computationally hard problems. Similar to how quantum computers are suited for problems rooted in quantum mechanics, probabilistic computers are designed to handle inherently probabilistic algorithms. These algorithms have applications in areas like combinatorial optimization and statistical machine learning. 

Researchers from Kyoto University, Chiba University, The University of Tokyo, Osaka University and Tokai University have found that the direction of spins inside a special type of magnet can be changed rapidly - flipping about every trillionth of a second - without increasing the temperature. They achieved this by applying a strong magnetic field with an oscillation frequency in the terahertz range.

The background for this work, according to the scientists, is the ever-increasing amount of information handled by computers and communication devices, that is driving development of technologies using the terahertz band - around 1012 Hz, a frequency range beyond the conventional gigahertz range of 109 Hz - considered important for the post-5G era. Additionally, memory technologies based on spintronics are expected to use less power to store more information, with antiferromagnets attracting attention because their collective spin-motion mode frequency reaches the terahertz range, making it possible to control spins using terahertz waves. However, conventional spin excitation using electric-field pulses is accompanied by heating or carrier excitation effects that subside relatively slowly, making it difficult to achieve fast spin control. The team has now demonstrated non-thermal spin switching in a canted antiferromagnet by dynamically modifying the magnetic energy landscape using a strong multicycle terahertz magnetic near-field.

Researchers from Korea have designed a new MRAM structure, based on graphene, that offers higher efficiency (and lower heat generation) compared to existing MRAM solutions. The design of the MRAM device is based on a graphene layer sandwiched between a magnetic insulator (yttrium iron garnet) and a ferroelectric material (PVDF-TrFE). Upon application of a voltage pulse, the current flow through the graphene is altered, enabling the storage of binary data based on this current direction.

The recent study demonstrates non-volatile control of spin-charge conversion at room temperature in graphene-based heterostructures through Fermi level tuning. The team used a polymeric ferroelectric film to induce non-volatile charging in graphene. To demonstrate the switching of spin-to-charge conversion, the scientists performed ferromagnetic resonance and inverse Edelstein effect experiments. 

A team of researchers from CIC nanoGUNE, IKERBASQUE, IMEC and CNRS have reported a spintronic device that leverages proximity effects alone, specifically a 2D graphene-based spin valve. The functioning of this valve relies only on the proximity to the van der Waals magnet Cr₂Ge₂Te₆. Spin precession measurements showed that the graphene acquires both spin–orbit coupling and magnetic exchange coupling when interfaced with the Cr₂Ge₂Te₆. This leads to spin generation by both electrical spin injection and the spin Hall effect, while retaining spin transport. The simultaneous presence of spin–orbit coupling and magnetic exchange coupling also leads to a sizeable anomalous Hall effect.

The primary objective of this recent study was to tackle a long-standing research challenge, namely that of realizing the first-ever seamless 2D spintronic device. The spin valve they developed could enable the manipulation and transport of spin entirely in the 2D plane.

Researchers from the Tokyo University of Science have proposed a novel magnetic RAM-based architecture that leverages spintronics to realize smaller, more efficient AI-capable circuits.

(a) Structure of the proposed neural network, which uses three-valued gradients during backpropagation (training) rather than real numbers, thus minimizing computational complexity. (b) A novel magnetic RAM cell leveraging spintronics for implementing the proposed technique in a computing-in-memory architecture.   

Artificial intelligence (AI) and the Internet of Things (IoT) are two technological fields that have been developing at an increasingly fast pace over the past decade. By excelling at tasks such as data analysis, image recognition, and natural language processing, AI systems have become undeniably powerful tools in both academic and industry settings. Meanwhile, miniaturization and advances in electronics have made it possible to massively reduce the size of functional devices capable of connecting to the Internet. Engineers and researchers alike foresee a world where IoT devices are ubiquitous, comprising the foundation of a highly interconnected world. However, bringing AI capabilities to IoT edge devices presents a significant challenge. Artificial neural networks (ANNs)—one of the most important AI technologies—require substantial computational resources. Meanwhile, IoT edge devices are inherently small, with limited power, processing speed, and circuit space. Developing ANNs that can efficiently learn, deploy, and operate on edge devices is a major hurdle.

Quantum computers based on spin photons and diamond promise significant advantages over competing quantum computing technologies, such as lower cooling requirements, longer operating times and lower error rates. The consortium of the BMBF project SPINNING coordinated by Fraunhofer IAF has succeeded in advancing the development of spin-photon-based quantum computers. The partners recently presented the interim project results at the mid-term meeting of the BMBF funding measure Quantum Computer Demonstration Setups in Berlin.

There are still several competing approaches to realizing quantum computers, each with specific advantages and disadvantages in terms of hardware and software, ranging from reliability and energy consumption to compatibility with conventional systems. Under the coordination of the Fraunhofer Institute for Applied Solid State Physics IAF, a consortium of 28 partners is working on the project "SPINNING - Diamond spin-photon-based quantum computer" to develop a quantum computer based on spin photons and diamond. This should be characterized by lower cooling requirements, longer operating times and lower error rates than other quantum computing approaches. The hybrid concept of the spin-photon-based quantum computer also provides for greater scalability and connectivity, which enables flexible connection with conventional computers.

Researchers at the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) and the Center for Hybrid Organic Inorganic Semiconductors for Energy (CHOISE), an Energy Frontier Research Center (EFRC), University of Wisconsin-Madison, University of Colorado Boulder, Duke University and University of Utah have discovered a new process to induce chirality in halide perovskite semiconductors, which could open the door to cutting-edge electronic applications.

The development is the latest in a series of advancements made by the team involving the introduction and control of chirality. Chirality refers to a structure that cannot be superimposed on its mirror image, such as a hand, and allows greater control of electrons by directing their spin. The researchers have been able to create a spin-polarized LED using chiral perovskite semiconductor in the absence of extremely low temperatures and a magnetic field, as was previously reported. The newest advance accelerates the materials development process for spin control.

Magnetic skyrmions have so far been treated as two-dimensional spin structures characterized by a topological winding number. However, in real systems with the finite thickness of the device material being larger than the magnetic exchange length, the skyrmion spin texture extends into the third dimension and cannot be assumed as homogeneous.

A 3D reconstruction of a skyrmion derived from X-ray images. Credit: Berkeley Lab

Researchers at Lawrence Berkeley National Laboratory, Swiss Light Source (Paul Scherrer Institute) and Western Digital Research Center have used soft x-ray laminography to reconstruct, with about 20-nanometer spatial (voxel) size, the full three-dimensional spin texture of a skyrmion in an 800-nanometer-diameter and 95-nanometer-thin disk patterned into a 30× [iridium/cobalt/platinum] multilayered film.

In a recent sturdy, researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and Northern Illinois University discovered that they could use light to detect the spin state in a class of materials called perovskites (specifically in this research methylammonium lead iodide, or MAPbI₃). 

To understand spin, consider electrons orbiting the atomic nucleus. When atoms are close together, they can share some of their outer electrons, which creates a bond between them. Each bond contains two electrons that are ​“paired,” meaning they share an orbital — the region where they move. Now, each of these paired electrons has one of two possible spin states: spin up or spin down. If one electron is spin up, the other is spin down. Since we can’t know exactly which electron has which spin without looking at them, we say they exist in a quantum superposition — a state where they are both spin up and spin down until observed.