Dear Colleagues,

Our society has benefited tremendously from the rapid development of information technology in the past 30 years. However, many side effects of such fast growth have been neglected until recently, one of which is the greatly increased energy consumption in computing. According to the 2021 USA Semiconductor Research Corporation decadal plan, computing energy has increased exponentially over the past decade, reaching almost 10¹⁹J in 2020.  A substantial part of the energy consumption is related to the increase in standby power consumption when the CMOS transistors are shrunk to a few nanometers. Therein lies the advantage of spintronics as one of the best solutions to this problem: the magnetization produced by the localized spins in nanomagnets is intrinsically nonvolatile. Thus, the standby power consumption can be eliminated completely in spintronic devices. In addition, the theoretical dynamic switching energy of a nanomagnet can also be lower than that of a CMOS transistor. Therefore, spintronics is posited to provide a unique approach to increase the energy efficiency of future generation of digital devices. This Special Issue calls for the contribution of researchers from all areas of spintronics. The topics of interest include, but are not limited to:

• Magnetoresistive devices
• Spin-transfer torques and spin-orbit torques
• Magnon and spin waves
• Ultrafast magnetization switching by optical or electrical excitations
• Electrical (voltage or current) control of magnetic anisotropy and magnetization
• Electrical (voltage or current) control of antiferromagnetism and ferrimagnetism
• Domain walls and skyrmions in ferromagnets, antiferromagnets, and ferrimagnets
• Fabrication of magnetic thinfilms and spintronics nanodevices
• Study of magnetic thin films and new materials such as topological insulators and Weyl semimetals
• Spin-dependent transport in organic or hybrid structures
• Chiral-induced spin selectivity
• Spin-orbitronic devices and integrated applications
• Futuristic spin-orbit logic, magnonic, topotronic, and skyrmionic materials and devices
• Spintronics towards emerging applications of in-memory computing and quantum probabilistic computing
• Neuromorphic computing involving spin-based devices
• Theory or modeling of spintronic devices and systems
• Design, fabrication, and characterization of advanced spintronic devices, circuits, and systems

Dr. Weigang Wang
Prof. Dr. Guozhong Xing
Guest Editors

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