[Professor] Shunsuke Fukami
Nano-Spin Materials and Devices
[Assistant Professor] Shun Kanai
[Assistant Professor] Justin Llandro
[Assistant Professor] Chaoliang Zhang
Our research activities aim to deepen the understanding of spin-related phenomena in novel spintronics materials and structures and apply the obtained insights to develop advanced spintronics devices, where electron charge, spin, and magnetization in solids are controlled. We also work on high-performance and ultralow-power spintronics devices to be used in integrated circuits, information processing and communication systems, brain-inspired computing, and quantum computing. Our studies include development of advanced materials and nanoscale devices, establishment of novel means to control magnetization with electric current or field, and related techniques for nano-fabrication and electrical characterization of the developed devices.
Nano-Spin Materials and Devices(Assoc. Prof. Fukami)
To realize high-performance and ultralow-power integrated circuits with spintronics, we are working to establish technologies for controlling the magnetization in nanoscale magnetic devices. We also aim to open up new paradigms for spintronics such as spintronics-based brain-inspired computing. Our recent research topics include current-induced control of magnetization via spin-orbit interactions, elucidation of static and dynamic properties of nano-scale magnets and magnetic textures such as domain walls, development of ultra-small magnetic tunnel junction devices, enhancement of nonvolatile spintronics memory technologies, and development of analog spintronics devices for artificial neural networks.
- Electrical and spin properties of spintronic materials/devices and their applications.
- Control of magnetization utilizing spin-orbit interactions.
- Dynamics of magnetic domains and domain walls in nanoscale magnets.
- Development of high-performance and low-power spintronic memory devices.
- Applications of metallic spintronics devices for nonvolatile memories, logic integrated circuits and brain-inspired computing.