Filter News
Area of Research
News Type
News Topics
- (-) Energy Storage (1)
- (-) Grid (1)
- (-) High-Performance Computing (4)
- (-) Materials Science (7)
- (-) Physics (2)
- (-) Quantum Science (3)
- Artificial Intelligence (3)
- Big Data (1)
- Bioenergy (2)
- Biology (3)
- Biomedical (3)
- Buildings (1)
- Chemical Sciences (1)
- Clean Water (1)
- Climate Change (3)
- Composites (1)
- Computer Science (6)
- Coronavirus (2)
- Decarbonization (1)
- Environment (3)
- Exascale Computing (1)
- Frontier (3)
- Fusion (1)
- Isotopes (3)
- Machine Learning (2)
- Materials (6)
- Microscopy (4)
- Nanotechnology (4)
- National Security (1)
- Neutron Science (3)
- Nuclear Energy (1)
- Polymers (2)
- Quantum Computing (5)
- Simulation (3)
- Summit (4)
- Sustainable Energy (1)
- Transportation (2)
Media Contacts
Gang Seob “GS” Jung has known from the time he was in middle school that he was interested in science.
Five National Quantum Information Science Research Centers are leveraging the behavior of nature at the smallest scales to develop technologies for science’s most complex problems.
Travis Humble has been named director of the Quantum Science Center headquartered at ORNL. The QSC is a multi-institutional partnership that spans industry, academia and government institutions and is tasked with uncovering the full potential of quantum materials, sensors and algorithms.
Two decades in the making, a new flagship facility for nuclear physics opened on May 2, and scientists from the Department of Energy’s Oak Ridge National Laboratory have a hand in 10 of its first 34 experiments.
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.
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.
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.
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