Filter News
Area of Research
News Topics
- (-) Artificial Intelligence (48)
- (-) Nanotechnology (16)
- 3-D Printing/Advanced Manufacturing (42)
- Advanced Reactors (8)
- Big Data (27)
- Bioenergy (51)
- Biology (60)
- Biomedical (29)
- Biotechnology (12)
- Buildings (20)
- Chemical Sciences (27)
- Clean Water (14)
- Climate Change (51)
- Composites (8)
- Computer Science (87)
- Coronavirus (17)
- Critical Materials (5)
- Cybersecurity (14)
- Decarbonization (46)
- Education (1)
- Emergency (2)
- Energy Storage (30)
- Environment (105)
- Exascale Computing (27)
- Fossil Energy (4)
- Frontier (25)
- Fusion (31)
- Grid (25)
- High-Performance Computing (45)
- Hydropower (5)
- Isotopes (28)
- ITER (2)
- Machine Learning (22)
- Materials (44)
- Materials Science (47)
- Mathematics (7)
- Mercury (7)
- Microelectronics (3)
- Microscopy (20)
- Molten Salt (1)
- National Security (42)
- Net Zero (8)
- Neutron Science (49)
- Nuclear Energy (56)
- Partnerships (19)
- Physics (30)
- Polymers (8)
- Quantum Computing (21)
- Quantum Science (31)
- Renewable Energy (1)
- Security (11)
- Simulation (32)
- Software (1)
- Space Exploration (12)
- Statistics (1)
- Summit (31)
- Sustainable Energy (47)
- Transformational Challenge Reactor (3)
- Transportation (27)
Media Contacts
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.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
Through a consortium of Department of Energy national laboratories, ORNL scientists are applying their expertise to provide solutions that enable the commercialization of emission-free hydrogen fuel cell technology for heavy-duty
The Accelerating Therapeutics for Opportunities in Medicine , or ATOM, consortium today announced the U.S. Department of Energy’s Oak Ridge, Argonne and Brookhaven national laboratories are joining the consortium to further develop ATOM’s artificial intelligence, or AI-driven, drug discovery platform.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and the University of Tennessee are automating the search for new materials to advance solar energy technologies.
ORNL and three partnering institutions have received $4.2 million over three years to apply artificial intelligence to the advancement of complex systems in which human decision making could be enhanced via technology.
Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.
From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.