University of Minnesota researchers, along with a team at the National Institute of Standards and Technology (NIST), recently developed a novel process for making spintronic devices that may have the potential to become the new industry standard for semiconductors chips that are essential to computers, smartphones and many other electronics. The new process will allow for faster, more efficient spintronics devices that can be scaled down smaller than ever before. ​​

“We believe we’ve found a material and a device that will allow the semiconducting industry to move forward with more opportunities in spintronics that weren’t there before for memory and computing applications,” said Jian-Ping Wang, senior author of the paper and professor in the College of Science and Engineering.

Materials scientists from the University of Groningen describe in two separate papers how complex oxides can be used to create very energy-efficient magneto-electric spin-orbit (MESO) devices and memristive devices with reduced dimensions.

The big challenges in next-gen microchips design are to design chips that are more energy efficient and to design devices that combine memory and logic (memristors). Tamalika Banerjee, Professor of Spintronics of Functional Materials at the Zernike Institute for Advanced Materials, University of Groningen, is looking at a range of quantum materials to create new devices. "Our approach is to study these materials and their interfaces, but always with an eye on applications, such as memory or the combination of memory and logic".

Scientists at the North Carolina State University, the University of North Carolina at Chapel Hill and Nanjing Normal University have made use of chiral phonons to transform wasted heat into spin information—without requiring magnetic materials.

This achievement could result in new classes of affordable and energy-efficient spintronic devices for use in applications from computational memory to power grids.

Researchers at MIT have proposed a new approach to making qubits and controlling them to read and write data. The method, which is theoretical at this stage, is based on measuring and controlling the spins of atomic nuclei, using beams of light from two lasers of slightly different colors. 

Nuclear spins have long been recognized as potential building blocks for quantum-based information processing and communications systems, and so have photons, the elementary particles that are discreet packets, or "quanta," of electromagnetic radiation. But coaxing these two quantum objects to work together was difficult because atomic nuclei and photons barely interact, and their natural frequencies differ by six to nine orders of magnitude. In the new process developed by the MIT team, the difference in the frequency of an incoming laser beam matches the transition frequencies of the nuclear spin, nudging the nuclear spin to flip a certain way.

An international research team led by the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) has developed a new method for the efficient coupling of terahertz waves with much shorter wavelengths, so-called spin waves.

The team's experiments, in combination with theoretical models, clarify the fundamental mechanisms of this process previously thought impossible. The results are an important step for the development of novel, energy-saving spin-based technologies for data processing.

Researchers at Switzerland EPFL, China's Anhui University, Germany's University of Cologne and University of New Hampshire in the US have developed a technique that can visualize and control the rotation of a handful of spins arranged in a vortex-like texture at the fastest speed ever achieved. The breakthrough can advance spintronics devices like computer memory, logic gates, and high-precision sensors.

"The visualization and deterministic control of very few spins has not yet been achieved at the ultrafast timescales," says Dr. Phoebe Tengdin, a postdoc at EPFL, pointing out the very tight timeframes that this control needs to happen for spintronics to ever make the leap into applications. Now, the team developed a new technique that can visualize and control the rotation of a handful of spins arranged in a vortex-like texture, a kind of spin "nano-whirlpool" called a skyrmion.

Researchers from Osaka Metropolitan University and Osaka City University have succeeded in measuring spin transport in a thin film of specific molecules - a material well-known in organic light emitting diodes (OLEDs) - at room temperature. 

They found that this thin molecular film has a spin diffusion length of approximately 62nm, a length that could have practical applications in developing spintronics technology. In addition, while electricity has been used to control spin transport in the past, the thin molecular film used in this study is photoconductive, allowing spin transport control using visible light.

A team led by researchers at the National Institute of Standards and Technology (NIST), the University of South Florida (USF), Harvey-Mudd College and the University of the District of Columbia has discovered a route toward reducing the sputter damage during growth of Nanolayered Pt/Co/Ir-based Synthetic Antiferromagnets that delivers significant improvements in perpendicular magnetic anisotropy and interlayer exchange coupling energy.

Synthetic antiferromagnets (SAFs) are a core component for top-pinned magnetic tunnel junction memory systems in semiconductor production. Establishing low-damage sputtering techniques to protect the multiple interfaces between sub-nm thick constituent layers delivers improved SAF properties could be key to data retention in high-density, sub-10 nm diameter magnetic memory arrays.

Researchers develop a super-hierarchical and explanatory analysis of magnetization reversal that could improve the reliability of spintronics devices. The researchers, led by Professor Masato Kotsugi from Japan's Tokyo University of Science, have developed an AI-based method for analyzing material functions in a more quantitative manner.

The team quantified the complexity of the magnetic domain structures using persistent homology, a mathematical tool used in computational topology that measures topological features of data persisting across multiple scales. The team further visualized the magnetization reversal process in two-dimensional space using principal component analysis, a data analysis procedure that summarizes large datasets by smaller “summary indices,” facilitating better visualization and analysis.

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.