Filter News
Area of Research
- (-) Supercomputing (61)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (23)
- Clean Energy (40)
- Computational Biology (2)
- Computational Engineering (1)
- Computer Science (8)
- Electricity and Smart Grid (2)
- Fusion and Fission (5)
- Fusion Energy (7)
- Isotopes (4)
- Materials (14)
- Materials for Computing (3)
- National Security (19)
- Neutron Science (14)
- Nuclear Science and Technology (12)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (7)
- Sensors and Controls (1)
News Topics
- (-) Advanced Reactors (1)
- (-) Artificial Intelligence (22)
- (-) Biomedical (11)
- (-) Grid (1)
- (-) Machine Learning (8)
- (-) Quantum Science (13)
- (-) Summit (27)
- 3-D Printing/Advanced Manufacturing (2)
- Big Data (17)
- Bioenergy (3)
- Biology (7)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (2)
- Climate Change (14)
- Computer Science (61)
- Coronavirus (9)
- Critical Materials (3)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (2)
- Environment (17)
- Exascale Computing (13)
- Frontier (14)
- Fusion (1)
- High-Performance Computing (23)
- Materials (5)
- Materials Science (9)
- Mathematics (1)
- Microscopy (2)
- Nanotechnology (6)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (3)
- Physics (3)
- Polymers (2)
- Quantum Computing (14)
- Security (1)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Sustainable Energy (4)
- Transportation (4)
Media Contacts
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
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.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
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.
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
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.