Filter News
Area of Research
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (56)
- Building Technologies (1)
- Computational Engineering (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Energy Science (63)
- Energy Sciences (1)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (19)
- Fusion Energy (3)
- Isotope Development and Production (1)
- Isotopes (15)
- Materials (76)
- Materials Characterization (2)
- Materials Under Extremes (1)
- National Security (26)
- Neutron Science (32)
- Nuclear Science and Technology (2)
- Supercomputing (73)
News Type
Date
News Topics
- 3-D Printing/Advanced Manufacturing (20)
- Advanced Reactors (3)
- Artificial Intelligence (26)
- Big Data (10)
- Bioenergy (22)
- Biology (29)
- Biomedical (7)
- Biotechnology (6)
- Buildings (14)
- Chemical Sciences (24)
- Clean Water (5)
- Composites (6)
- Computer Science (23)
- Coronavirus (4)
- Critical Materials (6)
- Cybersecurity (9)
- Education (3)
- Emergency (1)
- Energy Storage (21)
- Environment (43)
- Exascale Computing (15)
- Fossil Energy (2)
- Frontier (19)
- Fusion (9)
- Grid (16)
- High-Performance Computing (33)
- Hydropower (3)
- Irradiation (2)
- Isotopes (11)
- Machine Learning (15)
- Materials (59)
- Materials Science (16)
- Mathematics (2)
- Mercury (2)
- Microelectronics (2)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (7)
- National Security (21)
- Neutron Science (32)
- Nuclear Energy (21)
- Partnerships (24)
- Physics (14)
- Polymers (4)
- Quantum Computing (12)
- Quantum Science (9)
- Security (3)
- Simulation (29)
- Software (1)
- Space Exploration (4)
- Summit (9)
- Transportation (18)
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.
11 - 20 of 371 Results

ORNL Environmental Sciences Division Director Eric Pierce presented the division’s 2023 Distinguished Achievement Awards at the organization’s December all-hands meeting.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.

A team of researchers from the University of Southern California, the Renaissance Computing Institute at the University of North Carolina, and Oak Ridge, Lawrence Berkeley and Argonne National Laboratories have received a grant from the U.S. Department of Energy to develop the fundamentals of a computational platform that is fault tolerant, robust to various environmental conditions and adaptive to workloads and resource availability.

Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role. From helping to drive fundamental and applied AI research from the field’s early days focused on expert systems, computer programs that rely on AI, to more recent developments in deep learning, a form of AI that enables machines to make evidence-based decisions, the lab’s AI research spans the spectrum.

Drawing from his experience during the pandemic, Domenick Leto recognizes the need for the United States to have inexpensive, reliable capabilities to combat any type of disruption to national security, including nationwide medical emergencies. Leto and colleagues received a patent for a simple, inexpensive way to sterilize masks, plastic, and medical equipment from the COVID-19 virus.

Researchers at ORNL became the first to 3D-print large rotating steam turbine blades for generating energy in power plants.

For years, Duane Starr led workshops at ORNL to help others from across the U.S. government understand uranium processing technologies. After his retirement, Starr donated a 5-foot-tall working model, built in his garage, that demonstrates vibration harmonics, consistent with operation of a super critical gas centrifuge rotor, a valuable resource to ongoing ORNL-led workshops.



A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.