Tohoku University

Researchers from Tohoku University, University of Tokyo, Australian Nuclear Science and Technology Organization, High Energy Accelerator Research Organization and Comprehensive Research Organization for Science and Society have found that the spin current signal changes direction at a certain magnetic temperature and diminishes at lower temperatures.

Spintronics uses electrons’ intrinsic spin, which is vital to the field, to regulate the flow of the spin degree of freedom, that is, spin currents. Scientists are continually exploring new ways to manage spintronics for future uses. Detecting spin currents is quite complicated and necessitates the use of macroscopic voltage measurement, which examines the entire voltage fluctuations across a material. However, a major stumbling block has been a lack of understanding of how the spin current flows or propagates inside the material.

Researchers from Tohoku University and Toho University have demonstrated chirality switching by electric current pulses at room temperature in a thin-film MnAu₂ helimagnetic conductor. The team also succeeded in detecting the chirality at zero magnetic fields by means of simple transverse resistance measurement utilizing the spin Berry phase in a bilayer device composed of MnAu₂ and a spin Hall material Pt. These results may pave the way to helimagnet-based spintronics. 

Helimagnetic structures, in which the magnetic moments are spirally ordered, host an internal degree of freedom called chirality corresponding to the handedness of the helix. The chirality seems quite robust against disturbances and is therefore promising for next-generation magnetic memory. While the chirality control was recently achieved by the magnetic field sweep with the application of an electric current at low temperature in a conducting helimagnet, problems such as low working temperature and cumbersome control and detection methods have to be solved in practical applications.

Researchers from Tohoku University have developed a theoretical model for high-performance spin wave reservoir computing (RC) that utilizes spintronics technology. This achievement could push scientists closer to realizing energy-efficient, nanoscale computing with unparalleled computational power.

Scientists are constantly striving to create neuromorphic devices that mimic the brain's processing capabilities, low power consumption, and its ability to adapt to neural networks. The development of neuromorphic computing is revolutionary, allowing scientists to explore nanoscale realms, GHz speed, with low energy consumption. In recent years, many advances in computational models inspired by the brain have been made. These artificial neural networks have demonstrated extraordinary performances in various tasks. However, current technologies are software-based; their computational speed, size, and energy consumption remain constrained by the properties of conventional electric computers.

One way of processing information in spintronics is to use the magnetic vortices called skyrmions or, alternatively, their still little understood and rarer cousins called 'merons'. Both are collective topological structures formed of numerous individual spins. Merons have to date only been observed in natural antiferromagnets, where they are difficult to both analyze and manipulate.

Working in collaboration with teams at Tohoku University in Japan and the ALBA Synchrotron Light Facility in Spain, researchers of Johannes Gutenberg University Mainz (JGU) have been the first to demonstrate the presence of merons in synthetic antiferromagnets and thus in materials that can be produced using standard deposition techniques.

Researchers at Tohoku University and the University of California, Santa Barbara, have shown a proof-of-concept energy-efficient computer compatible with current AI. It utilizes a stochastic behavior of nanoscale spintronics devices and is particularly suitable for probabilistic computation problems such as inference and sampling.

The team presented the results at the IEEE International Electron Devices Meeting (IEDM 2023) on December 12, 2023.

Researchers from Tohoku University, Chinese Academy of Sciences (CAS), Guangxi Normal University, Kyushu University and Japan Atomic Energy Agency have reported a significant breakthrough which could revolutionize next-generation electronics by enabling non-volatility, large-scale integration, low power consumption, high speed, and high reliability in spintronic devices.

Spintronic devices, such as magnetic random access memory (MRAM), utilize the magnetization direction of ferromagnetic materials for information storage and rely on spin current, a flow of spin angular momentum, for reading and writing data. Conventional semiconductor electronics have faced limitations in achieving these qualities. However, the emergence of three-terminal spintronic devices, which employ separate current paths for writing and reading information, presents a solution with reduced writing errors and increased writing speed. Nevertheless, the challenge of reducing energy consumption during information writing, specifically magnetization switching, remains a critical concern.

Researchers from Tohoku University in Japan, University of California Riverside and the Massachusetts Institute of Technology detail a decade of research advancements in the emerging field of antiferromagnetic spintronics that holds the promise of moving beyond today’s world of electrons moving through semiconductors.

As computers and other electronic devices become faster and more powerful, they are coming closer to a physical limitation caused by heat generated by the electrons that carry information as they move through semiconductors. “Making heat is a fundamental limit that will prevent the further development of electronic devices. So, we are basically hitting a bottleneck because our computers are way faster than they used to be two decades ago,” said Ran Cheng, an assistant professor of electrical and computer engineering with UCR’s Bourns College of Engineering. Workarounds like cooling systems can go only so far as artificial intelligence, machine learning, video streaming, and other applications demand faster and faster computer processing and memory retrievals.

Researchers have found that lasers can generate stable patterns of electron spins in a thin layer of semiconductor material, a discovery that may help lead to advanced spin-based memory and computing. The scientists have revealed that lasers could generate complex stable patterns of electron spins called “spin textures” in thin films of semiconductors. These spin textures could help lead to what may be the holy grail of spintronics, a superefficient spin-based transistor.

The new findings are based on how light has momentum, just as a physical object moving through space does, even though light does not have mass. This means that light shining on an object can exert a force. Whereas the linear momentum of light supplies a push in the direction that light is moving, the angular momentum of light applies torque.

Researchers from Tohoku University, University of California Riverside and Massachusetts Institute of Technology (MIT) have highlighted a series of critical achievements in antiferromagnetic spintronics (including their own contributions), revealing an emerging frontier distinguished by the coherent spin dynamics of antiferromagnets. 

Within antiferromagnetic spintronics, scientists have exerted a lot of efforts on the switching and readout of static magnetic order. But coherent spin dynamics, the key to exploring the wave features of spins and integrating spintronics with quantum and neuromorphic technologies, has only received attention very recently. "The coherent spin dynamics of antiferromagnets exhibits a lot more intriguing features than that of ferromagnets," says Jiahao Han, a JSPS Research Fellow working at the Research Institute of Electrical Communication (RIEC), Tohoku University. "By harnessing this unique property, the team has been pursuing breakthroughs that eventually form a new chapter named coherent antiferromagnetic spintronics."

Researchers at Tohoku University, the University of Messina and the University of California, Santa Barbara (UCSB) have developed a scaled-up version of a probabilistic computer (p-computer) with stochastic spintronic devices that is suitable for hard computational problems like combinatorial optimization and machine learning.

The constructed heterogeneous p-computer consisting of stochastic magnetic tunnel junction (sMTJ) based probabilistic bit (p-bit) and field-programmable gate array (FPGA). ©Kerem Camsari, Giovanni Finocchio, and Shunsuke Fukami et al.

A p-computer harnesses naturally stochastic building blocks called probabilistic bits (p-bits). Unlike bits in traditional computers, p-bits oscillate between states. A p-computer can operate at room-temperature and acts as a domain-specific computer for a wide variety of applications in machine learning and artificial intelligence. Just like quantum computers try to solve inherently quantum problems in quantum chemistry, p-computers attempt to tackle probabilistic algorithms, widely used for complicated computational problems in combinatorial optimization and sampling.