Integrated Nano Computing Lab
At the INC Lab, led by Prof. Jean Anne Incorvia at the University of Texas at Austin, we develop practical nano-devices for the future of computing. We study the fundamental physics and materials properties of emerging materials, and work to bridge the gap from test structures to practical devices to circuits and systems. This vertical approach includes theoretical and experimental work at the materials, devices, and circuits levels. We seek to understand the materials properties, and then show how they can be designed into devices that do not just stand alone, but can perform useful computing tasks. Our cross-disciplinary work has been supported by the state and federal government as well as by strong partnerships with national labs and the semiconductor industry.
We are facing a time when we are reaching the limits of scaling improvements using current technology. Current transistors waste energy both while switching and when idle, which ends up as wasted heat in our computers. On the other end of the spectrum, we are facing new big-data applications for computing that require large, dense memories that are distributed with logic, and applications like artificial intelligence and neuromorphic computing that require massive parallel in-memory computation.
New physics and materials, such as magnetic materials and 2D materials, have the potential for more energy efficient computing. They also have novel physical properties that can be utilized, such as naturally low-dimensional sizes for ultra-scaled electronics, non-volatility (keeping its state when off), tunable dynamics, device-to-device interactions, low to no idle power dissipation, low-temperature fabrication, and in-memory computing possibilities. This is an exciting time where we have the tools to apply new types of physics and materials to real-world devices, with a strong motivation to do so.
We also investigate other applications of nanotechnology, such as quantum computing, quantum materials for health, and in-sensor computing for precision agriculture.