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Media Contacts
![Frances Pleasonton seals a vacuum chamber in 1951.](/sites/default/files/styles/list_page_thumbnail/public/2023-03/Pleasonton20616_16x9_1678989753589_0.jpg?h=d1cb525d&itok=s-itGaqM)
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](/sites/default/files/styles/list_page_thumbnail/public/2023-03/2-MJD-Guiseppe%20in%20front%20of%20shield_4.jpeg?h=a141e9ea&itok=URbl8Trd)
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](/sites/default/files/styles/list_page_thumbnail/public/2023-03/2022-P14758_0.jpg?h=c6980913&itok=YJLFDsPp)
A scientific instrument at ORNL could help create a noninvasive cancer treatment derived from a common tropical plant.
![Larry Allard](/sites/default/files/styles/list_page_thumbnail/public/2022-08/Allard.png?h=748cb951&itok=GvagcEmh)
Larry Allard, a distinguished research staff member at Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society.
![Scattering-type scanning near-field optical microscopy, a nondestructive technique in which the tip of the probe of a microscope scatters pulses of light to generate a picture of a sample, allowed the team to obtain insights into the composition of plant cell walls. Credit: Ali Passian/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/Picture1_0.jpg?h=da2f9885&itok=_QN9qoqF)
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
![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](/sites/default/files/styles/list_page_thumbnail/public/2022-06/FRIB1.jpg?h=429981e8&itok=sFq0uTlk)
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](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
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.](/sites/default/files/styles/list_page_thumbnail/public/2022-04/CCSD_NeuralNetworkBanner.png?h=b16f811b&itok=fxqDEvs_)
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
![This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2022-03/FerroicHalidePerovskite.jpg?h=b803af89&itok=eBzxpb4b)
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.