Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (20)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (4)
- Electricity and Smart Grid (1)
- Energy Science (18)
- Functional Materials for Energy (1)
- Materials (8)
- Materials for Computing (3)
- National Security (14)
- Neutron Science (12)
- Nuclear Science and Technology (1)
- Supercomputing (26)
News Topics
- (-) Coronavirus (48)
- (-) Machine Learning (67)
- 3-D Printing/Advanced Manufacturing (144)
- Advanced Reactors (40)
- Artificial Intelligence (125)
- Big Data (77)
- Bioenergy (110)
- Biology (126)
- Biomedical (73)
- Biotechnology (37)
- Buildings (73)
- Chemical Sciences (84)
- Clean Water (32)
- Composites (34)
- Computer Science (223)
- Critical Materials (29)
- Cybersecurity (35)
- Education (5)
- Element Discovery (1)
- Emergency (4)
- Energy Storage (114)
- Environment (217)
- Exascale Computing (64)
- Fossil Energy (8)
- Frontier (62)
- Fusion (65)
- Grid (74)
- High-Performance Computing (128)
- Hydropower (12)
- Irradiation (3)
- Isotopes (62)
- ITER (9)
- Materials (156)
- Materials Science (156)
- Mathematics (12)
- Mercury (12)
- Microelectronics (4)
- Microscopy (56)
- Molten Salt (10)
- Nanotechnology (62)
- National Security (86)
- Neutron Science (169)
- Nuclear Energy (121)
- Partnerships (66)
- Physics (68)
- Polymers (35)
- Quantum Computing (52)
- Quantum Science (88)
- Security (30)
- Simulation (64)
- Software (1)
- Space Exploration (26)
- Statistics (4)
- Summit (70)
- Transportation (102)
ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.
61 - 70 of 110 Results

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.

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.

Oak Ridge National Laboratory researchers have retrofitted a commercial refrigeration container designed to ensure COVID-19 vaccines remain at ultra-low temperatures during long transport and while locally stored.

A study by Department of Energy researchers detailed a potential method to detect the novel coronavirus

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.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

When COVID-19 was declared a pandemic in March 2020, Oak Ridge National Laboratory’s Parans Paranthaman suddenly found himself working from home like millions of others.

When Kashif Nawaz looks at a satellite map of the U.S., he sees millions of buildings that could hold a potential solution for the capture of carbon dioxide, a plentiful gas that can be harmful when excessive amounts are released into the atmosphere, raising the Earth’s temperature.