Filter News
Area of Research
- (-) Nuclear Science and Technology (16)
- (-) Supercomputing (19)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (17)
- Clean Energy (13)
- Computational Biology (1)
- Fusion and Fission (27)
- Fusion Energy (6)
- Isotopes (6)
- Materials (29)
- Materials for Computing (4)
- National Security (9)
- Neutron Science (12)
- Quantum information Science (2)
News Topics
- (-) Biomedical (7)
- (-) Fusion (6)
- (-) Materials Science (10)
- (-) Microscopy (2)
- (-) Nuclear Energy (18)
- (-) Security (1)
- 3-D Printing/Advanced Manufacturing (4)
- Advanced Reactors (4)
- Artificial Intelligence (21)
- Big Data (13)
- Bioenergy (3)
- Biology (6)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Climate Change (12)
- Computer Science (45)
- Coronavirus (7)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (1)
- Environment (13)
- Exascale Computing (12)
- Frontier (13)
- Grid (1)
- High-Performance Computing (20)
- Isotopes (2)
- Machine Learning (7)
- Materials (4)
- Mathematics (1)
- Molten Salt (1)
- Nanotechnology (5)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Physics (4)
- Quantum Computing (10)
- Quantum Science (10)
- Simulation (10)
- Software (1)
- Space Exploration (2)
- Summit (21)
- Sustainable Energy (3)
- Transformational Challenge Reactor (2)
- Transportation (3)
Media Contacts
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.
JungHyun Bae is a nuclear scientist studying applications of particles that have some beneficial properties: They are everywhere, they are unlimited, they are safe.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
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.
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.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant
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.