Imagine a computer that works more like your brain—fast, smart, and able to learn from experience. Thanks to funding from the National Science Foundation, ECE Assistant Professor Yingying Wu is helping to make this dream a reality. Wu’s recently funded project, “Investigating Multiferroic Interface for Scalable and Energy-Efficient Control of Magnetic Skyrmions,” builds upon a relatively new computer architecture known as neuromorphic computing—an architecture inspired by how the human brain processes information—but adds a unique spin.
Unlike regular computers, which separate memory and processing, neuromorphic computers combine these functions, making them faster, more energy-efficient, and better at handling large amounts of data. A promising approach may be to include tiny, stable magnetic patterns that use very little energy called skyrmions to make these brain-like computers even better at learning and adapting. However, controlling skyrmions with electrical signals and making them work on a small scale remains a challenge. Wu’s team will work to solve these problems by exploring new materials and the ways in which they interface with other materials to improve skyrmion control. The hope is that the project will lead to more efficient, powerful computers, and provide hands-on learning opportunities for future scientists and engineers.
Neuromorphic systems, as they are inspired by biological neural networks, require advanced materials and device architectures to replicate brain-like functions. Magnetic skyrmions—nanoscale, topologically protected spin structures—offer promising characteristics such as low energy consumption, stability, and high information density. However, controlling and scaling skyrmion-based devices remains a technical challenge, particularly in conventional heavy metal/ferromagnet systems where energy consumption and limited tunability hinder practical implementation. Supported by NSF’s funding, Wu will explore new materials and their interface to enable precise and energy-efficient control of skyrmions.
By advancing the understanding of spintronic materials, the project will contribute to the development of next-generation computing technologies. Successful outcomes from this research could enable the development of more efficient, brain-inspired computing systems, fostering innovation in artificial intelligence and advanced data processing.