Filter News
Area of Research
- (-) Computational Biology (1)
- (-) National Security (25)
- Advanced Manufacturing (1)
- Biology and Environment (47)
- Biology and Soft Matter (1)
- Clean Energy (64)
- Climate and Environmental Systems (2)
- Computational Engineering (2)
- Computer Science (6)
- Energy Sciences (1)
- Fusion and Fission (4)
- Fusion Energy (1)
- Isotopes (20)
- Materials (24)
- Materials for Computing (3)
- Mathematics (1)
- Neutron Science (10)
- Nuclear Science and Technology (5)
- Quantum information Science (1)
- Supercomputing (62)
News Type
News Topics
- (-) Big Data (6)
- (-) Climate Change (4)
- (-) Cybersecurity (9)
- (-) Energy Storage (1)
- (-) Machine Learning (8)
- (-) Summit (3)
- 3-D Printing/Advanced Manufacturing (1)
- Artificial Intelligence (7)
- Bioenergy (2)
- Biology (5)
- Biomedical (3)
- Biotechnology (1)
- Buildings (1)
- Computer Science (12)
- Coronavirus (3)
- Decarbonization (2)
- Environment (4)
- Grid (5)
- High-Performance Computing (5)
- Materials (1)
- Materials Science (2)
- Nanotechnology (1)
- National Security (22)
- Neutron Science (3)
- Nuclear Energy (2)
- Quantum Science (1)
- Security (6)
- Simulation (1)
- Sustainable Energy (2)
- Transportation (1)
Media Contacts
Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.
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.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
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.
Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences
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.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.