Filter News
Area of Research
- (-) Supercomputing (38)
- Advanced Manufacturing (1)
- Biology and Environment (23)
- Clean Energy (48)
- Computer Science (3)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (19)
- Fusion Energy (1)
- Isotopes (11)
- Materials (38)
- Materials for Computing (3)
- National Security (22)
- Neutron Science (39)
- Nuclear Science and Technology (2)
News Topics
- (-) Artificial Intelligence (21)
- (-) Computer Science (21)
- (-) Neutron Science (2)
- (-) Nuclear Energy (1)
- (-) Space Exploration (1)
- (-) Transportation (1)
- Big Data (6)
- Bioenergy (4)
- Biology (9)
- Biomedical (6)
- Biotechnology (2)
- Buildings (3)
- Chemical Sciences (3)
- Climate Change (13)
- Coronavirus (4)
- Critical Materials (2)
- Cybersecurity (2)
- Decarbonization (4)
- Energy Storage (4)
- Environment (8)
- Exascale Computing (18)
- Frontier (22)
- Grid (2)
- High-Performance Computing (26)
- Machine Learning (9)
- Materials (13)
- Materials Science (5)
- Microscopy (3)
- Nanotechnology (5)
- National Security (6)
- Net Zero (1)
- Partnerships (1)
- Physics (2)
- Quantum Computing (14)
- Quantum Science (8)
- Security (3)
- Simulation (14)
- Software (1)
- Summit (13)
- Sustainable Energy (3)
Media Contacts
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 study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
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.