Filter News
Area of Research
- (-) Computational Biology (1)
- (-) Computational Engineering (1)
- (-) Functional Materials for Energy (1)
- (-) Quantum information Science (1)
- Advanced Manufacturing (3)
- Biology and Environment (23)
- Clean Energy (115)
- Computer Science (9)
- Electricity and Smart Grid (3)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (46)
- Fusion Energy (15)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (49)
- Materials for Computing (6)
- National Security (36)
- Neutron Science (19)
- Nuclear Science and Technology (36)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Sensors and Controls (2)
- Supercomputing (75)
- Transportation Systems (2)
News Type
News Topics
- (-) Artificial Intelligence (3)
- (-) Frontier (1)
- (-) Grid (2)
- (-) Machine Learning (2)
- Big Data (1)
- Bioenergy (1)
- Biology (2)
- Biomedical (3)
- Buildings (1)
- Clean Water (1)
- Climate Change (1)
- Computer Science (10)
- Coronavirus (1)
- Cybersecurity (2)
- Decarbonization (1)
- Energy Storage (2)
- Environment (2)
- High-Performance Computing (4)
- Materials (2)
- Materials Science (1)
- Mathematics (1)
- Microscopy (2)
- Nanotechnology (1)
- Neutron Science (1)
- Physics (1)
- Quantum Science (9)
- Simulation (1)
- Summit (2)
- Sustainable Energy (2)
Media Contacts
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
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.
Scientists at Oak Ridge National Laboratory studying quantum communications have discovered a more practical way to share secret messages among three parties, which could ultimately lead to better cybersecurity for the electric grid
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool