Filter News
Area of Research
- (-) Electricity and Smart Grid (2)
- (-) Supercomputing (31)
- Advanced Manufacturing (3)
- Biology and Environment (12)
- Clean Energy (38)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (6)
- Fusion and Fission (15)
- Fusion Energy (11)
- Materials (24)
- Materials for Computing (5)
- National Security (17)
- Neutron Science (58)
- Nuclear Science and Technology (13)
- Quantum information Science (1)
- Sensors and Controls (1)
News Topics
- (-) Coronavirus (9)
- (-) Fusion (1)
- (-) Grid (3)
- (-) Machine Learning (8)
- (-) Neutron Science (6)
- (-) Quantum Computing (14)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (1)
- Artificial Intelligence (22)
- Big Data (17)
- Bioenergy (3)
- Biology (7)
- Biomedical (11)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (2)
- Climate Change (14)
- Computer Science (61)
- Critical Materials (3)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (2)
- Environment (17)
- Exascale Computing (13)
- Frontier (14)
- High-Performance Computing (23)
- Materials (5)
- Materials Science (9)
- Mathematics (1)
- Microelectronics (1)
- Microscopy (2)
- Nanotechnology (6)
- National Security (3)
- Net Zero (1)
- Nuclear Energy (3)
- Physics (3)
- Polymers (2)
- Quantum Science (13)
- Security (1)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Summit (27)
- Sustainable Energy (4)
- Transportation (4)
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.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
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.
A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.
A multi-institutional team, led by a group of investigators at Oak Ridge National Laboratory, has been studying various SARS-CoV-2 protein targets, including the virus’s main protease. The feat has earned the team a finalist nomination for the Association of Computing Machinery, or ACM, Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.
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.
COVID-19 has upended nearly every aspect of our daily lives and forced us all to rethink how we can continue our work in a more physically isolated world.
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the