Filter News
Area of Research
- (-) Fusion Energy (4)
- (-) Isotopes (2)
- (-) Materials Under Extremes (1)
- (-) Supercomputing (73)
- Advanced Manufacturing (10)
- Biology and Environment (54)
- Building Technologies (2)
- Clean Energy (101)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (7)
- Electricity and Smart Grid (1)
- Energy Sciences (1)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Isotope Development and Production (1)
- Materials (95)
- Materials Characterization (1)
- Materials for Computing (20)
- National Security (12)
- Neutron Science (31)
- Nuclear Science and Technology (4)
- Quantum information Science (1)
- Transportation Systems (1)
News Topics
- (-) Big Data (19)
- (-) Materials Science (20)
- (-) Polymers (2)
- (-) Summit (42)
- (-) Sustainable Energy (11)
- 3-D Printing/Advanced Manufacturing (6)
- Advanced Reactors (8)
- Artificial Intelligence (36)
- Bioenergy (9)
- Biology (11)
- Biomedical (22)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (18)
- Computer Science (96)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (9)
- Environment (22)
- Exascale Computing (22)
- Frontier (28)
- Fusion (13)
- Grid (5)
- High-Performance Computing (38)
- Irradiation (1)
- Isotopes (25)
- Machine Learning (14)
- Materials (21)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (9)
- Net Zero (1)
- Neutron Science (13)
- Nuclear Energy (17)
- Partnerships (1)
- Physics (7)
- Quantum Computing (19)
- Quantum Science (24)
- Security (5)
- Simulation (14)
- Software (1)
- Space Exploration (6)
- Transportation (6)
Media Contacts
![Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn](/sites/default/files/styles/list_page_thumbnail/public/2022-02/Graves-AD_0.jpg?h=46d8a70d&itok=77AW7Swv)
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
![An international team of researchers used Summit to model spin, charge and pair-density waves in cuprates, a type of copper alloy, to explore the materials’ superconducting properties. The results revealed new insights into the relationships between these dynamics as superconductivity develops. Credit: Jason Smith/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2022-02/MaierSpinBanner.png?h=ae114f5c&itok=rdZETb8v)
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
![Mars Rover 2020](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Mars_0.jpg?h=c44fcfa1&itok=gSstQOJO)
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
![An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/sars_cov_2_bk.png?h=05c2797f&itok=jQ2D9aTr)
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
![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.
![Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/image001_0.png?h=11d99c73&itok=sdREw4na)
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant
![INCITE_narrow_logo](/sites/default/files/styles/list_page_thumbnail/public/2021-11/incite_narrow_1.png?h=a08abdbb&itok=2O5LBHgQ)
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
![A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Quantum%20Illustration%20V3_0.png?h=2e111cc1&itok=Bth5wkD4)
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
![As part of the Next-Generation Ecosystem Experiments Arctic project, scientists are gathering and incorporating new data about the Alaskan tundra into global models that predict the future of our planet. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-08/NGEE_eddy%20covariance%20Busey.jpg?h=2d5be524&itok=VFtVDdzq)
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
![ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-05/KalininVasudevan_2017-P03014_0.jpg?h=1116cd87&itok=KEEOB4hi)
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.