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Nathaly Santiesteban, assistant professor of physics and astronomy.

�鶹�� physicist Nathaly Santiesteban has received funding from the Department of Energy’s highly competitive Genesis Mission to explore using artificial intelligence to better understand spin and the fundamental structure of matter, addressing questions at the heart of modern nuclear physics. 

Santiesteban’s project was one of just 278 selected from over 5,000 proposals to the Genesis Mission, which aims to accelerate breakthroughs and double the nation’s scientific productivity with AI-enabled workflows.

“This research addresses a fundamental question: How does matter acquire the properties we observe? Most visible matter is made of protons and neutrons, yet we still do not fully understand how their internal components produce properties such as spin,” says Santiesteban, assistant professor of physics and astronomy.

Santiesteban’s project will use artificial intelligence to make polarized-target systems — specialized experimental setups used in nuclear and particle physics to align the spin axes of atomic nuclei — easier to operate, more reliable, and more responsive to changing experimental conditions. She and her �鶹�� co-principal investigators, Karl Slifer, professor of physics and astronomy, and Elena Long, associate professor of physics and astronomy, will use the polarized-target laboratory at �鶹�� as the project’s primary testing site.

Funded with $750,000 for the first nine-month phase and up to $15 million for the three-year phase two, Santiesteban will collaborate with researchers from the Department of Energy’s Jefferson Lab and the University of Virginia, the University of Tennessee, and New Mexico State University.

Karl Slifer, professor of physics and astronomy and Elena Long, associate professor of physics and astronomy, will collaborate with Santiesteban (center) on �鶹��'s Genesis Mission project.

Polarized-target systems are highly complex. They operate at temperatures lower than those of outer space and combine powerful magnetic fields, microwaves, sophisticated radio-frequency equipment, and materials that require strict safety controls. Scientists direct a particle beam at the polarized material and study how the particles scatter. 

“The project could also demonstrate how AI can work safely with complex scientific equipment, with potential applications in other laboratories and advanced technologies,” Santiesteban says. “Running these experiments at research facilities is very demanding because every part of the system must be continuously monitored and carefully controlled to achieve and maintain the desired polarization. Our project aims to reduce the amount of manual intervention required and increase experimental efficiency by using artificial intelligence to monitor the system and optimize its operating variables in real time.”