ABSTRACT

The rapid development of artificial intelligence relies on modern computing technologies. However, the existing von Neumann-based technology suffers from high energy consumption for data-intensive tasks. This high energy consumption may limit the future adoption of artificial intelligence technologies. Inspired by the biological brain, neuromorphic computing provides the promising technological capability to tackle this challenge by creating superior energy-efficient hardware for information processing. This research project exploits the superior nonlinear nonvolatile spin-related responses in quantum materials. The key challenge to implementing neuromorphic computing is to create artificial neurons and synapses with great energy efficiency. Spintronics study the interplay between electron spin transport and charge transport, so they naturally couple electronic and magnetic configurations, thus offering non-volatility and nonlinearity. Nonvolatile spintronics memory devices can emulate artificial synapses and nonlinear spin-torque nano-oscillators can emulate artificial neurons. The proposed research activities will provide a unique opportunity for students at the University of Alabama at Birmingham to gain computation skills and collaborate with distinguished scientists at the National Institute of Standards and Technology (NIST). Additionally, as a part of this project, the PI will develop a new advanced physics course about artificial intelligence and how to implement it with physical devices.

This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows (RII Track-4) project would provide a fellowship to an Assistant Professor and training for a postdoctoral fellow at the University of Alabama at Birmingham (UAB). Brain-inspired neuromorphic computing offers appealing technology capability for artificial intelligence applications. Spintronics devices, which couple electronic and magnetic configurations, can emulate synapses and neurons in an energy-efficient compact manner. The magnetic random-access memory can serve as the synapses and the spin-torque nano-oscillators can serve as the neurons. The quantum materials provide additional appealing features including more efficient control of magnetization and new functionalities due to the coupling of spin, orbital, and magnetization degrees of freedom. Understanding and modeling microscopic mechanisms with state-of-art first-principles methods of neuromorphic spintronics with quantum materials is the main goal of this proposal. The two main thrusts focus on utilizing the superior spin-orbitronics properties in quantum materials for artificial synapses and neurons. By collaborating with the experts at the NIST, the project will apply first-principles methods to calculate the band structures and spin dynamics in spin-orbit coupled quantum materials. This allows for the understanding of the microscopic mechanism of spin-orbit torque switching and dynamics and provides a pathway to improve the figure of merits. Project outcomes will also include illustration of how to utilize these nonlinear nonvolatile properties of spintronics devices into emulating neurons and synapses for neuromorphic computing. The proposed work will provide the physics foundation for implementing neuromorphic spintronics devices with emerging quantum materials such as two-dimensional materials and topological materials.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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