Filter News
Area of Research
- Advanced Manufacturing (4)
- Biology and Environment (22)
- Building Technologies (1)
- Clean Energy (37)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (12)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (3)
- Fusion Energy (2)
- Isotopes (4)
- Materials (38)
- Materials for Computing (8)
- Mathematics (1)
- National Security (6)
- Neutron Science (6)
- Nuclear Science and Technology (1)
- Quantum information Science (4)
- Supercomputing (36)
News Type
News Topics
- (-) Big Data (25)
- (-) Biomedical (23)
- (-) Biotechnology (7)
- (-) Composites (15)
- (-) Computer Science (68)
- (-) Exascale Computing (7)
- (-) Frontier (7)
- (-) Nanotechnology (30)
- (-) Polymers (19)
- 3-D Printing/Advanced Manufacturing (61)
- Advanced Reactors (20)
- Artificial Intelligence (25)
- Bioenergy (38)
- Biology (45)
- Buildings (34)
- Chemical Sciences (29)
- Clean Water (19)
- Climate Change (44)
- Coronavirus (21)
- Critical Materials (14)
- Cybersecurity (15)
- Decarbonization (27)
- Energy Storage (61)
- Environment (95)
- Fusion (24)
- Grid (30)
- High-Performance Computing (32)
- Hydropower (8)
- Irradiation (3)
- Isotopes (22)
- ITER (5)
- Machine Learning (17)
- Materials (75)
- Materials Science (65)
- Mathematics (5)
- Mercury (7)
- Microscopy (29)
- Molten Salt (6)
- National Security (25)
- Net Zero (4)
- Neutron Science (49)
- Nuclear Energy (48)
- Partnerships (6)
- Physics (26)
- Quantum Computing (7)
- Quantum Science (16)
- Security (10)
- Simulation (16)
- Software (1)
- Space Exploration (11)
- Statistics (1)
- Summit (10)
- Sustainable Energy (66)
- Transformational Challenge Reactor (1)
- Transportation (58)
Media Contacts
Researchers at Oak Ridge National Laboratory have developed free data sets to estimate how much energy any building in the contiguous U.S. will use in 2100. These data sets provide planners a way to anticipate future energy needs as the climate changes.
Oak Ridge National Laboratory scientists ingeniously created a sustainable, soft material by combining rubber with woody reinforcements and incorporating “smart” linkages between the components that unlock on demand.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
Rigoberto “Gobet” Advincula, a scientist with joint appointments at ORNL and the University of Tennessee, has been named a Fellow of the American Institute for Medical and Biological Engineering.
Forrest Hoffman, a distinguished scientist at the Department of Energy’s Oak Ridge National Laboratory, has been named a senior member of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air.
Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition.