Filter News
Area of Research
News Topics
- (-) Grid (2)
- (-) Isotopes (1)
- (-) Machine Learning (4)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (4)
- Big Data (4)
- Bioenergy (13)
- Biology (16)
- Biomedical (3)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (4)
- Clean Water (2)
- Climate Change (21)
- Composites (1)
- Computer Science (9)
- Coronavirus (3)
- Cybersecurity (3)
- Decarbonization (14)
- Energy Storage (2)
- Environment (25)
- Exascale Computing (3)
- Frontier (4)
- Fusion (4)
- High-Performance Computing (7)
- Hydropower (3)
- ITER (1)
- Materials (8)
- Materials Science (4)
- Mercury (1)
- Microscopy (7)
- Nanotechnology (3)
- National Security (7)
- Net Zero (2)
- Neutron Science (3)
- Nuclear Energy (3)
- Partnerships (1)
- Physics (2)
- Polymers (1)
- Quantum Computing (5)
- Quantum Science (3)
- Security (2)
- Simulation (3)
- Summit (4)
- Sustainable Energy (13)
- Transportation (3)
Media Contacts
Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.
In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
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.
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.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.