Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (18)
- Biology and Soft Matter (1)
- Clean Energy (82)
- Computational Engineering (1)
- Computer Science (4)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (6)
- Materials (47)
- Materials for Computing (8)
- National Security (16)
- Neutron Science (10)
- Supercomputing (23)
- Transportation Systems (2)
News Topics
- (-) Chemical Sciences (65)
- (-) Machine Learning (48)
- (-) Transportation (97)
- 3-D Printing/Advanced Manufacturing (122)
- Advanced Reactors (34)
- Artificial Intelligence (91)
- Big Data (55)
- Bioenergy (92)
- Biology (99)
- Biomedical (58)
- Biotechnology (22)
- Buildings (57)
- Clean Water (30)
- Climate Change (101)
- Composites (26)
- Computer Science (190)
- Coronavirus (46)
- Critical Materials (26)
- Cybersecurity (35)
- Decarbonization (80)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (109)
- Environment (196)
- Exascale Computing (38)
- Fossil Energy (6)
- Frontier (42)
- Fusion (55)
- Grid (63)
- High-Performance Computing (86)
- Hydropower (11)
- Irradiation (3)
- Isotopes (53)
- ITER (7)
- Materials (144)
- Materials Science (141)
- Mathematics (9)
- Mercury (12)
- Microelectronics (3)
- Microscopy (51)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (63)
- Net Zero (14)
- Neutron Science (131)
- Nuclear Energy (109)
- Partnerships (44)
- Physics (62)
- Polymers (33)
- Quantum Computing (35)
- Quantum Science (69)
- Renewable Energy (2)
- Security (24)
- Simulation (49)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (57)
- Sustainable Energy (126)
- Transformational Challenge Reactor (7)
Media Contacts
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
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.
Burak Ozpineci started out at ORNL working on a novel project: introducing silicon carbide into power electronics for more efficient electric vehicles. Twenty years later, the car he drives contains those same components.
Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges.
Oak Ridge National Laboratory has released the federal government’s new 2022 Fuel Economy Guide. The report provides the latest fuel efficiency stats and money-saving tips for new and used vehicles.
Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
Having co-developed the power electronics behind ORNL’s compact, high-level wireless power technology for automobiles, Erdem Asa is looking to the skies to apply the same breakthrough to aviation.
Research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2021 R&D 100 Awards, plus special recognition for a COVID-19-related project.
Analytical chemists at ORNL have developed a rapid way to measure isotopic ratios of uranium and plutonium collected on environmental swipes, which could help International Atomic Energy Agency analysts detect the presence of undeclared nuclear
Oak Ridge National Laboratory researchers developed and demonstrated algorithm-based controls for a hybrid electric bus that yielded up to 30% energy savings compared with existing controls.