Filter News
Area of Research
News Topics
- (-) Exascale Computing (2)
- (-) Machine Learning (2)
- (-) Microscopy (1)
- (-) Space Exploration (1)
- Artificial Intelligence (7)
- Big Data (3)
- Bioenergy (2)
- Biology (3)
- Biomedical (3)
- Buildings (1)
- Climate Change (3)
- Computer Science (13)
- Coronavirus (2)
- Decarbonization (1)
- Environment (3)
- Frontier (3)
- High-Performance Computing (4)
- Materials (4)
- Materials Science (3)
- Nanotechnology (3)
- National Security (1)
- Neutron Science (1)
- Nuclear Energy (1)
- Quantum Computing (5)
- Quantum Science (4)
- Simulation (3)
- Summit (8)
- Sustainable Energy (1)
Media Contacts
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
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.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
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.
For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.