Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (3)
- Electricity and Smart Grid (1)
- Energy Science (5)
- Functional Materials for Energy (1)
- Fusion and Fission (2)
- Fusion Energy (1)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (5)
- Materials for Computing (1)
- National Security (1)
- Neutron Science (4)
- Nuclear Science and Technology (5)
- Supercomputing (35)
News Topics
- (-) Frontier (61)
- (-) Space Exploration (26)
- 3-D Printing/Advanced Manufacturing (141)
- Advanced Reactors (40)
- Artificial Intelligence (123)
- Big Data (77)
- Bioenergy (104)
- Biology (119)
- Biomedical (71)
- Biotechnology (31)
- Buildings (73)
- Chemical Sciences (84)
- Clean Water (32)
- Composites (33)
- Computer Science (221)
- Coronavirus (48)
- Critical Materials (29)
- Cybersecurity (35)
- Education (5)
- Element Discovery (1)
- Emergency (4)
- Energy Storage (114)
- Environment (217)
- Exascale Computing (62)
- Fossil Energy (8)
- Fusion (65)
- Grid (73)
- High-Performance Computing (126)
- Hydropower (12)
- Irradiation (3)
- Isotopes (62)
- ITER (9)
- Machine Learning (66)
- Materials (156)
- Materials Science (154)
- Mathematics (12)
- Mercury (12)
- Microelectronics (4)
- Microscopy (55)
- Molten Salt (10)
- Nanotechnology (62)
- National Security (85)
- Neutron Science (169)
- Nuclear Energy (121)
- Partnerships (64)
- Physics (68)
- Polymers (34)
- Quantum Computing (49)
- Quantum Science (85)
- Security (30)
- Simulation (63)
- Software (1)
- Statistics (4)
- Summit (70)
- Transportation (102)
Media Contacts
Connect with ORNL
Get ORNL News

John Lagergren, a staff scientist in 91°µÍø’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.

Researchers set a new benchmark for future experiments making materials in space rather than for space. They discovered that many kinds of glass have similar atomic structure and arrangements and can successfully be made in space. Scientists from nine institutions in government, academia and industry participated in this 5-year study.

A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.

When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.

Scientists at 91°µÍø and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions.
Integral to the functionality of ORNL's Frontier supercomputer is its ability to store the vast amounts of data it produces onto its file system, Orion. But even more important to the computational scientists running simulations on Frontier is their capability to quickly write and read to Orion along with effectively analyzing all that data. And that’s where ADIOS comes in.

College intern Noah Miller is on his 3rd consecutive internship at ORNL, currently working on developing an automated pellet inspection system for 91°µÍø’s Plutonium-238 Supply Program. Along with his success at ORNL, Miller is also focusing on becoming a mentor for kids, giving back to the place where he discovered his passion and developed his skills.

Since 2019, a team of NASA scientists and their partners have been using NASA’s FUN3D software on supercomputers located at the Department of Energy’s Oak Ridge Leadership Computing Facility to conduct computational fluid dynamics simulations of a human-scale Mars lander. The team’s ongoing research project is a first step in determining how to safely land a vehicle with humans onboard onto the surface of Mars.

In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
