Spintronics is one of the most promising next generation information technology, which uses the spins of electrons as information carriers and possesses potential advantage in speeding up data processing with high circuit integration density and low energy consumption. Despite its great potential advantages, spintronics now faces a number of challenges, such as generation of fully spin-polarized carriers (pure spins) and injection of spin into devices, long distance spin transport, and manipulation and detection of carriers’ spin orientation. To solve the above issues, diverse spintronics materials have been designed such as magnetic metals, magnetic topological materials, and magnetic semiconductors.
Although lots of spintronics materials have been proposed previously, most of them are far from practical applications due to a number of problems such as the destruction of half-metallicity by spin-flip transitions, low magnetic ordering temperature, difficulty in synthesis, and bad controllability. To design spintronics materials that work at room temperature and that can be easily manipulated in experiments is the key to bring spintronics to real life.
In this regard, first-principles calculation provides us a powerful and cheap tool. Experimental materials design is a trial-and-error task, which is both time- and energy-intensive and inevitably causes a waste of experimental resources. For first-principles calculation, no real sample is needed and it can be performed even for materials that have not been synthesized yet. With the help of first-principles, the properties of materials can be routinely predicted, based on which promising materials can be selected and confirmed through experiments. Such a procedure can largely reduce the period of materials design.
In this Research Topic, we will focus on computational modeling of spintronics. We encourage researchers working in these fields to submit their latest Original Research, Mini Review/Review, or Perspective articles dealing with themes that include, but are not limited to:
• Computational modeling of magnetic metals, including ferromagnetic metals, and half-metals.
• Computational modeling of magnetic topological materials, for example, magnetic materials with Weyl nodal lines.
• Computational modeling of magnetic semiconductors, diluted magnetic semiconductors, spin-gapless semiconductors, half-semiconductors, bipolar magnetic materials, and asymmetric antiferriomagentic semiconductors.
• Frontiers in computational modeling of materials phenomena.
Spintronics is one of the most promising next generation information technology, which uses the spins of electrons as information carriers and possesses potential advantage in speeding up data processing with high circuit integration density and low energy consumption. Despite its great potential advantages, spintronics now faces a number of challenges, such as generation of fully spin-polarized carriers (pure spins) and injection of spin into devices, long distance spin transport, and manipulation and detection of carriers’ spin orientation. To solve the above issues, diverse spintronics materials have been designed such as magnetic metals, magnetic topological materials, and magnetic semiconductors.
Although lots of spintronics materials have been proposed previously, most of them are far from practical applications due to a number of problems such as the destruction of half-metallicity by spin-flip transitions, low magnetic ordering temperature, difficulty in synthesis, and bad controllability. To design spintronics materials that work at room temperature and that can be easily manipulated in experiments is the key to bring spintronics to real life.
In this regard, first-principles calculation provides us a powerful and cheap tool. Experimental materials design is a trial-and-error task, which is both time- and energy-intensive and inevitably causes a waste of experimental resources. For first-principles calculation, no real sample is needed and it can be performed even for materials that have not been synthesized yet. With the help of first-principles, the properties of materials can be routinely predicted, based on which promising materials can be selected and confirmed through experiments. Such a procedure can largely reduce the period of materials design.
In this Research Topic, we will focus on computational modeling of spintronics. We encourage researchers working in these fields to submit their latest Original Research, Mini Review/Review, or Perspective articles dealing with themes that include, but are not limited to:
• Computational modeling of magnetic metals, including ferromagnetic metals, and half-metals.
• Computational modeling of magnetic topological materials, for example, magnetic materials with Weyl nodal lines.
• Computational modeling of magnetic semiconductors, diluted magnetic semiconductors, spin-gapless semiconductors, half-semiconductors, bipolar magnetic materials, and asymmetric antiferriomagentic semiconductors.
• Frontiers in computational modeling of materials phenomena.
