Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (12)
- Clean Energy (23)
- Computer Science (1)
- Fusion and Fission (4)
- Isotope Development and Production (1)
- Isotopes (1)
- Materials (54)
- Materials Characterization (1)
- Materials for Computing (6)
- Materials Under Extremes (1)
- National Security (8)
- Neutron Science (48)
- Nuclear Science and Technology (2)
- Supercomputing (16)
News Type
News Topics
- (-) Machine Learning (20)
- (-) Materials Science (66)
- (-) Neutron Science (60)
- 3-D Printing/Advanced Manufacturing (58)
- Advanced Reactors (13)
- Artificial Intelligence (40)
- Big Data (15)
- Bioenergy (40)
- Biology (44)
- Biomedical (28)
- Biotechnology (12)
- Buildings (25)
- Chemical Sciences (41)
- Clean Water (9)
- Climate Change (38)
- Composites (14)
- Computer Science (74)
- Coronavirus (23)
- Critical Materials (13)
- Cybersecurity (23)
- Decarbonization (36)
- Education (3)
- Element Discovery (1)
- Energy Storage (57)
- Environment (74)
- Exascale Computing (13)
- Fossil Energy (1)
- Frontier (18)
- Fusion (24)
- Grid (23)
- High-Performance Computing (39)
- Hydropower (2)
- Isotopes (30)
- ITER (3)
- Materials (68)
- Mathematics (5)
- Mercury (6)
- Microelectronics (1)
- Microscopy (25)
- Molten Salt (3)
- Nanotechnology (32)
- National Security (34)
- Net Zero (5)
- Nuclear Energy (42)
- Partnerships (30)
- Physics (40)
- Polymers (17)
- Quantum Computing (12)
- Quantum Science (30)
- Renewable Energy (1)
- Security (18)
- Simulation (14)
- Space Exploration (3)
- Statistics (1)
- Summit (23)
- Sustainable Energy (44)
- Transformational Challenge Reactor (4)
- Transportation (37)
Media Contacts
A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.
Distinguished materials scientist Takeshi Egami has spent his career revealing the complex atomic structure of metallic glass and other liquids — sometimes sharing theories with initially resistant minds in the scientific community.
Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.
ORNL’s Matthew Loyd will receive a Department of Energy Office of Science Early Career Research award.
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.
As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance.
DOE commissioned a neutron imaging instrument, VENUS, at the Spallation Neutron Source in July. VENUS instrument scientists will use AI to deliver 3D models to researchers in half the time it typically takes.
Seven entrepreneurs comprise the next cohort of Innovation Crossroads, a DOE Lab-Embedded Entrepreneurship Program node based at ORNL. The program provides energy-related startup founders from across the nation with access to ORNL’s unique scientific resources and capabilities, as well as connect them with experts, mentors and networks to accelerate their efforts to take their world-changing ideas to the marketplace.
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.
Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.