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Andrea Delgado, Distinguished Staff Fellow at Oak Ridge National Laboratory, uses quantum computing to help elucidate the fundamental particles of the universe. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Andrea Delgado is looking for elementary particles that seem so abstract, there appears to be no obvious short-term benefit to her research.

Frances Pleasonton seals a vacuum chamber in 1951.

The old photos show her casually writing data in a logbook with stacks of lead bricks nearby, or sealing a vacuum chamber with a wrench. ORNL researcher Frances Pleasonton was instrumental in some of the earliest explorations of the properties of the neutron as the X-10 Site was finding its postwar footing as a research lab.

Vincente Guiseppe, co-spokesperson of the Majorana Collaboration and a research staff member at ORNL, in front of the Majorana Demonstrator shield on the 4850 Level of SURF. Credit: Nick Hubbard/Sanford Underground Research Facility

For nearly six years, the Majorana Demonstrator quietly listened to the universe. Nearly a mile underground at the Sanford Underground Research Facility, or SURF, in Lead, South Dakota, the experiment collected data that could answer one of the most perplexing questions in physics: Why is the universe filled with something instead of nothing?

From left are UWindsor students Isabelle Dib, Dominik Dziura, Stuart Castillo and Maksymilian Dziura at ORNL’s Neutron Spin Echo spectrometer. Their work advances studies on a natural cancer treatment. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

A scientific instrument at ORNL could help create a noninvasive cancer treatment derived from a common tropical plant.

Students from UC Merced collect water samples at Guadalupe Reservoir in Santa Clara County, California. Credit: UC Merced

Environmental scientists at ORNL have recently expanded collaborations with minority-serving institutions and historically Black colleges and universities across the nation to broaden the experiences and skills of student scientists while bringing fresh insights to the national lab’s missions.

ORNL will use its land surface modeling tools to determine Baltimore’s climate risk and analyze green infrastructure improvements that can help mitigate impacts on underserved communities as part of a DOE Urban Integrated Field Laboratory project. Source: Google Earth, accessed Sept. 12, 2022

ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.

Researchers at Oak Ridge National Laboratory designed an adsorbent material to rapidly remove toxic chromium and arsenic simultaneously from water resources. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.

Oak Ridge National Laboratory’s Mitch Allmond works with the Facility for Rare Isotope Beams Decay Station initiator, which combined diverse detectors for FRIB’s first experiment. Credit: Robert Grzywacz/ORNL, U.S. Dept. of Energy

Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.