Integrated Nano Computing Lab

At the INC Lab, 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.

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 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), oscillatory 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 are also interested in other applications of nanotechnology, such as quantum computing and medicine.


Check out a May 2021 article on a trio of papers from our group!

Brain-like Computing Takes a Step Forward with New Discoveries Using Magnetism

Prof. Incorvia gave a talk on implementing advanced biological functions in artificial magnetic neurons and synapses to the Petaspin lecture series. It is available on YouTube.

Prof. Incorvia gave a talk on domain wall-magnetic tunnel junction devices for in-memory and neuromorphic computing to the Online Spintronics Seminar series. Check it out here.

Our work “Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing” was published today in Applied Physics Letters, as part of the Special Topic on Spin-Orbit Torque (SOT): Materials, Physics and Devices. Calling out the hard work of all the authors, and especially Mahshid Alamdar and Thomas Leonard who share first-authorship.

We have two students with awards to congratulate! Congratulations to Can Cui for receiving the Bruton Graduate Student Fellowship in recognition of her research excellence. And congratulations to Mahshid Alamdar for receiving a 2021 American Physical Society March Meeting Award for excellence in graduate research, give to 7-10 graduate students out of > 10,000 attendees.

Check out the Nov. 2020 issue of the Texas ECE Magazine, with INC Lab featured on p. 15!

Our group’s work on lateral inhibition in magnetic neurons, led by graduate student Can Cui, was published in IOP Nanotechnology in 202o. The results have reach broader audiences through the UT Austin Cockrell School Website,, and

Prof. Incorvia answers five questions about computing like the brain in an interview with the Cockrell School of Engineering.

Dr. Incorvia received the 2020 IEEE Magnetics Society Early Career Award, awarded to one person internationally in her field a year. Read more about the award here.

Congratulations to Thomas Leonard for receiving the 2020 NSF Graduate Research Fellowship!

Dr. Incorvia received the National Science Foundation Faculty Early Career Development Program CAREER award, starting March 2020

CAREER Announcement

2018 interview discussing the research going on in the INC Lab

Interview with Dr. Incorvia at the 2019 American Graphene Summit

Our work on designing magnetic devices as synapses with spike-timing-dependent plasticity has been published in Sept. 2019!

Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity

Research Highlights

Magnetic Logic Devices and Circuits

We are researching new device and circuit designs for computation using magnetic materials.

Neuromorphic Computing

We work on designing and building magnetic resistive devices for analog/neuromorphic/bio-inspired computing.

Spintronics using 2D TMD Materials

2D transition metal dichalcogenide (TMD) materials have emerging applications for spintronics. We are studying the spin and valley Hall effect in TMD transistors such as WSe2 and WS2.

Materials for Magnetic Tunnel Junctions

We are investigating new materials for both the electrodes and tunnel barrier to improve the on/off ratio and functionality of magnetic tunnel junctions.

Ultra-Scaled Transistors using 2D Materials

We are investigating 2D transistors with materials such as TMDs and black phosphorus.

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New Spintronic 2D Materials

We are studying new types of low-dimensional materials with promising applications in spintronics.