We are focused on new device and circuit designs for computation using magnetic materials. These materials have the benefits of very low switching energy, non-volalility, back-end-of-the-line compatible temperatures, and rich physics that can be applied to new computing paradigms.
For logic applications, we are interested in devices and circuits that can satisfy the requirements for beyond-CMOS computing, including gain, fanout, concatenability to build circuits, feedback prevention, and compatibility with CMOS circuits and processing. We are investigating three-terminal magnetic tunnel junction (3T-MTJ) logic devices with mobile domain walls. A SEM image of a 3T-MTJ is shown above, along with a three-inverters circuit that showed bit propagation and concatenability, built at MIT. Example paper 1 | Example paper 2
For brain-inspired neuromorphic computing applications, we are interested in devices that can, as closely as possible, capture the biological behavior of the brain. Brain-inspired computing is a revolution in computing that is already seeing applications in a myriad of areas, from image recognition to developing learning rules that allow computers to intelligently process big data sets. This field is inspired by the human brain, which is very efficient at certain tasks. For example, the brain can recognize a face or voice using a million times less power than a modern supercomputer. But, so far machine learning has largely focused on restructuring how the computer is put together, but where the building blocks themselves are silicon transistors. Neuroscientists have recognized certain behaviors of neurons and synapses that are central to processing and learning. This is an opportunity to use new materials and new physics to capture the biological behavior of the brain in artificial neurons and synapses.
Like the brain, compared to traditional computers, magnetic materials have relatively slow switching but with low voltage, non-volatility, and with digital, analog, stochastic, and oscillatory behavior. We are investigated magnetic-based synapses, neurons, and neuromorphic circuits. Example paper 1 | Example paper 2 | Example paper 3
2D transition metal dichalcogenide (TMD) materials have emerging applications for spintronics. Space-reversal asymmetry in the monolayer films combined with heavy metal strong spin-orbit coupling leads to a combined spin and valley Hall effect (SVHE). We are studying this effect in TMD transistors such as WSe2 and WS2, especially focusing on electrical control for device applications. We use optical techniques such as magneto-optical Kerr effect (MOKE) to study the spin and valley behavior. Above is an example MOKE map of a WSe2 transistor, taken with collaborators at Stanford, showing distinct positive (red) and negative (blue) phase change across the device at 240 K, showing a SVHE at close to room temperatures.
As transistors scale down laterally, they must also scale down vertically to maintain gate control over the transistor channel. 2D materials are naturally atomically smooth and thin, making them exciting materials for future ultra-scaled electronics. We are investigating 2D transistors with materials such as TMDs and black phosphorus. Above is a transmission electron microscope image of a 6.5 nm black phosphorous transistor with Sc contacts, taken with collaborators at Stanford, where we investigated low-work-function contacts effect on the transistor IV behavior.
We are also investigating new materials for magnetic tunnel junction and 2D spintronics, along with new computing devices such as neuromorphic computing using magnetic resistive devices.