Filter News
Area of Research
News Topics
- (-) Exascale Computing (64)
- (-) Simulation (64)
- 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)
- Coronavirus (48)
- Critical Materials (29)
- Cybersecurity (35)
- Education (5)
- Element Discovery (1)
- Emergency (4)
- Energy Storage (114)
- Environment (217)
- Fossil Energy (8)
- Frontier (62)
- Fusion (65)
- Grid (74)
- High-Performance Computing (128)
- Hydropower (12)
- Irradiation (3)
- Isotopes (62)
- ITER (9)
- Machine Learning (67)
- 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)
- 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.
31 - 40 of 112 Results

A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.

Office of Science to announce a new research and development opportunity led by ORNL to advance technologies and drive new capabilities for future supercomputers. This industry research program worth $23 million, called New Frontiers, will initiate partnerships with multiple companies to accelerate the R&D of critical technologies with renewed emphasis on energy efficiency for the next generation of post-exascale computing in the 2029 and beyond time frame.

Nuclear physicists at the Department of Energy’s Oak Ridge National Laboratory recently used Frontier, the world’s most powerful supercomputer, to calculate the magnetic properties of calcium-48’s atomic nucleus.

A study by more than a dozen scientists at the Department of Energy’s Oak Ridge National Laboratory examines potential strategies to integrate quantum computing with the world’s most powerful supercomputing systems in the pursuit of science.

The world’s fastest supercomputer helped researchers simulate synthesizing a material harder and tougher than a diamond — or any other substance on Earth. The study used Frontier to predict the likeliest strategy to synthesize such a material, thought to exist so far only within the interiors of giant exoplanets, or planets beyond our solar system.

Researchers conduct largest, most accurate molecular dynamics simulations to date of two million correlated electrons using Frontier, the world’s fastest supercomputer. The simulation, which exceed an exaflop using full double precision, is 1,000 times greater in size and speed than any quantum chemistry simulation of it's kind.

In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.

Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.

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.

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.