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Next-Generation Computing using Spin-Based and 2D Materials

Jean Anne Incorvia


We are at a time where the electronics industry is feeling pressure from two sides: on the small scale we are facing the fundamental physical limits of silicon, and on the large scale we are facing new big-data applications, such as for the internet of things. The future of computing will require both more energy-efficient electronics and more big-data-driven, application-specific designs.

Magnetic devices are a promising candidate for future electronics, due to their low voltage operation, nonvolatility and low thermal budget, which can open up new energy-efficient, normally-off, memory-in-computing, 3D monolithic architectures. Magnetic materials are one of the few materials systems that can be more energy efficient than silicon transistors for memory and logic, and have been shown to be more energy efficient and faster than other emerging resistive memories.

Additionally, the emerging class of 2D materials, such as graphene and transition metal dichalcogenides (TMDs), have little to no surface roughness with monolayer thickness, and thus 2D transistors can be scaled without sacrificing mobility. They have the benefits of flexibility and low thermal budget, and new physics we can utilize such as the valley Hall effect. Thus, spin-based and 2D materials are very important classes of materials to explore for beyond-CMOS devices and systems.

I will present experimental results using three-terminal spin switches to build practical magnetic logic devices and circuits and show they satisfy the requirements for beyond-CMOS devices. We show a single device can act as an inverter, and we are able to propagate bits between the spin switches to build up circuits. I will also show our work on voltage control of the spin and valley Hall effect in TMD materials, which could be used for future 2D-magnetic hybrid devices. I will discuss the future directions of this work, including building energy-efficient 3D monolithic systems of these emerging technologies, and looking further to quantum computing.


Jean Anne C. Incorvia is a postdoctoral research fellow at Stanford University in electrical engineering and a visiting scholar at UC Berkeley electrical engineering and computer science. She received her Ph.D. in physics from Harvard University in 2015, cross-registered at MIT, where she was a Department of Energy Graduate Student Fellow. She received her bachelor’s in physics from UC Berkeley in 2008. Her research focuses on emerging materials and devices for nanoelectronics.

Jean Anne Incorvia Headshot
Jean Anne Incorvia
Stanford University
EEB 105
7 Feb 2017, 10:30am until 11:20am