Filter News
Area of Research
- (-) National Security (9)
- Biology and Environment (37)
- Biology and Soft Matter (1)
- Clean Energy (14)
- Computational Biology (1)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (9)
- Isotopes (1)
- Materials (20)
- Materials for Computing (3)
- Neutron Science (10)
- Supercomputing (18)
News Topics
- (-) Big Data (2)
- (-) Bioenergy (2)
- (-) Biomedical (2)
- (-) Environment (1)
- (-) Exascale Computing (1)
- (-) Neutron Science (2)
- (-) Partnerships (1)
- 3-D Printing/Advanced Manufacturing (1)
- Artificial Intelligence (3)
- Biology (4)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (2)
- Climate Change (4)
- Computer Science (7)
- Coronavirus (1)
- Cybersecurity (5)
- Decarbonization (1)
- Energy Storage (1)
- Frontier (1)
- Grid (3)
- High-Performance Computing (1)
- Machine Learning (4)
- Materials (1)
- National Security (13)
- Physics (1)
- Security (3)
- Simulation (1)
- Summit (1)
- Sustainable Energy (1)
Media Contacts
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.