Filter News
Area of Research
- (-) Clean Energy (77)
- (-) Supercomputing (42)
- Advanced Manufacturing (3)
- Biological Systems (1)
- Biology and Environment (25)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (1)
- Electricity and Smart Grid (2)
- Functional Materials for Energy (1)
- Fusion and Fission (6)
- Isotope Development and Production (1)
- Isotopes (7)
- Materials (48)
- Materials for Computing (9)
- National Security (22)
- Neutron Science (79)
- Nuclear Science and Technology (7)
News Type
News Topics
- (-) Biomedical (17)
- (-) Grid (27)
- (-) Machine Learning (16)
- (-) Neutron Science (20)
- (-) Space Exploration (3)
- (-) Transportation (43)
- 3-D Printing/Advanced Manufacturing (57)
- Advanced Reactors (6)
- Artificial Intelligence (39)
- Big Data (19)
- Bioenergy (27)
- Biology (16)
- Biotechnology (5)
- Buildings (24)
- Chemical Sciences (14)
- Clean Water (4)
- Climate Change (28)
- Composites (8)
- Computer Science (84)
- Coronavirus (21)
- Critical Materials (5)
- Cybersecurity (14)
- Decarbonization (31)
- Energy Storage (53)
- Environment (51)
- Exascale Computing (22)
- Fossil Energy (2)
- Frontier (27)
- Fusion (1)
- High-Performance Computing (36)
- Isotopes (1)
- Materials (32)
- Materials Science (30)
- Mathematics (2)
- Mercury (2)
- Microelectronics (1)
- Microscopy (12)
- Molten Salt (1)
- Nanotechnology (13)
- National Security (11)
- Net Zero (3)
- Nuclear Energy (9)
- Partnerships (12)
- Physics (7)
- Polymers (6)
- Quantum Computing (15)
- Quantum Science (22)
- Renewable Energy (1)
- Security (9)
- Simulation (14)
- Software (1)
- Summit (37)
- Sustainable Energy (43)
- Transformational Challenge Reactor (3)
Media Contacts
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
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.
ORNL and the Tennessee Valley Authority, or TVA, are joining forces to advance decarbonization technologies from discovery through deployment through a new memorandum of understanding, or MOU.
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.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
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.
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.
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.
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.