Filter News
Area of Research
News Topics
- (-) Physics (9)
- 3-D Printing/Advanced Manufacturing (30)
- Advanced Reactors (5)
- Artificial Intelligence (45)
- Big Data (28)
- Bioenergy (16)
- Biology (22)
- Biomedical (13)
- Biotechnology (10)
- Buildings (29)
- Chemical Sciences (30)
- Clean Water (6)
- Composites (11)
- Computer Science (46)
- Critical Materials (7)
- Education (2)
- Emergency (3)
- Energy Storage (15)
- Environment (38)
- Exascale Computing (25)
- Fossil Energy (4)
- Frontier (21)
- Fusion (12)
- Grid (16)
- High-Performance Computing (45)
- Hydropower (1)
- Isotopes (17)
- ITER (2)
- Machine Learning (23)
- Materials (24)
- Materials Science (26)
- Mathematics (7)
- Microelectronics (2)
- Microscopy (4)
- Molten Salt (1)
- Nanotechnology (2)
- National Security (34)
- Neutron Science (23)
- Nuclear Energy (15)
- Partnerships (29)
- Polymers (5)
- Quantum Computing (20)
- Quantum Science (22)
- Security (8)
- Simulation (24)
- Space Exploration (3)
- Statistics (3)
- Summit (14)
- Transportation (15)
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.
1 - 10 of 32 Results

The Department of Energy’s Office of Electricity, in partnership with ORNL, has launched an experimental platform for energy sector-related data with enhanced emphasis on governance and usability.

Researchers used the Summit supercomputer at ORNL to answer one of fission’s big questions: What exactly happens during the nucleus’s “neck rupture” as it splits in two? Scission neutrons have been theorized to be among those particles emitted during neck rupture, although their exact characteristics have been debated due to a lack of conclusive experimental evidence of their existence.

Researchers led by the University of Melbourne, Australia, have been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize in supercomputing for conducting a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.

The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.

A new Global Biomass Resource Assessment developed by ORNL scientists gathered data from 55 countries resulting in a first-of-its kind compilation of current and future sustainable biomass supply estimates around the world.

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.

Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.

Scientists have determined that a rare element found in some of the oldest solids in the solar system, such as meteorites, and previously thought to have been forged in supernova explosions, actually predate such cosmic events, challenging long-held theories about its origin.

Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.

Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.