![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
News Type
News Topics
- (-) Artificial Intelligence (7)
- (-) Composites (3)
- (-) Polymers (2)
- (-) Security (2)
- (-) Space Exploration (3)
- (-) Transportation (5)
- 3-D Printing/Advanced Manufacturing (6)
- Advanced Reactors (1)
- Big Data (7)
- Bioenergy (17)
- Biology (21)
- Biomedical (5)
- Biotechnology (2)
- Buildings (12)
- Chemical Sciences (6)
- Clean Water (5)
- Climate Change (24)
- Computer Science (13)
- Coronavirus (7)
- Critical Materials (3)
- Cybersecurity (3)
- Decarbonization (15)
- Energy Storage (8)
- Environment (30)
- Exascale Computing (4)
- Frontier (4)
- Fusion (4)
- Grid (6)
- High-Performance Computing (11)
- Hydropower (8)
- Irradiation (1)
- Isotopes (2)
- ITER (1)
- Machine Learning (6)
- Materials (19)
- Materials Science (7)
- Mercury (1)
- Microscopy (10)
- Nanotechnology (5)
- National Security (10)
- Net Zero (2)
- Neutron Science (5)
- Nuclear Energy (3)
- Partnerships (2)
- Physics (3)
- Quantum Computing (5)
- Quantum Science (5)
- Simulation (5)
- Summit (5)
- Sustainable Energy (19)
Media Contacts
![Jim Szybist, Propulsion Science section head at ORNL, is applying his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Picture1_6.jpg?h=b67478d5&itok=3BWDWSU8)
What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.
![TEDB](/sites/default/files/styles/list_page_thumbnail/public/2022-05/bookcover_graphic-012_sized.jpg?h=97102f31&itok=5gMgkI9L)
It’s been referenced in Popular Science and Newsweek, cited in the Economic Report of the President, and used by agencies to create countless federal regulations.
![The online Fuel Economy Guide, compiled by ORNL researchers, provides simple tips to save at the pump including the Trip Calculator tool to better navigate vehicle choice and estimate mileage. Credit: Storyblocks](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Transportation%20Thumbnail.jpeg?h=e91a75a9&itok=xL-iJely)
Oak Ridge National Laboratory researchers determined that for every 5 miles per hour that drivers travel over a 50-mph speed limit, fuel economy decreases by 7% and equates to paying an extra 28 cents per gallon at current.
![Physicist Charles Havener uses the NASA end station at ORNL’s Multicharged Ion Research Facility to simulate the origin of X-ray emissions from space. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/2021-P08920_0.jpg?h=c6980913&itok=zfXx31gD)
Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.
![Oak Ridge National Laboratory researchers built an Earth-to-space communications system to work with private and government partners with the goal of directly connecting data downlinks to high performance computing. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Ground%20station%20satellite%20tip_0.jpg?h=9f252dc3&itok=p9Mk-hwp)
Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.
![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.
![Samples of four unique materials hitched a ride to space as part of an effort by ORNL scientists to evaluate how each fares under space conditions. Credit: Zac Ward/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-02/unlabeled_0.jpg?h=06058838&itok=4F9H5cRo)
To study how space radiation affects materials for spacecraft and satellites, Oak Ridge National Laboratory scientists sent samples to the International Space Station. The results will inform design of radiation-resistant magnetic and electronic systems.
![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.