Filter News
Area of Research
News Topics
- (-) Grid (2)
- (-) Machine Learning (5)
- (-) Microscopy (2)
- (-) Nanotechnology (3)
- (-) Quantum Computing (7)
- (-) Quantum Science (4)
- (-) Space Exploration (1)
- Artificial Intelligence (7)
- Big Data (3)
- Bioenergy (2)
- Biology (5)
- Biomedical (4)
- Buildings (3)
- Chemical Sciences (2)
- Climate Change (4)
- Computer Science (10)
- Coronavirus (3)
- Critical Materials (1)
- Cybersecurity (1)
- Decarbonization (2)
- Energy Storage (3)
- Environment (3)
- Exascale Computing (6)
- Frontier (7)
- High-Performance Computing (8)
- Materials (8)
- Materials Science (5)
- National Security (3)
- Neutron Science (1)
- Partnerships (1)
- Physics (1)
- Security (2)
- Simulation (5)
- Summit (7)
- Sustainable Energy (2)
Media Contacts
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Lawrence Berkeley National Laboratory physicists Christian Bauer, Marat Freytsis and Benjamin Nachman have leveraged an IBM Q quantum computer through the Oak Ridge Leadership Computing Facility’s Quantum Computing User Program to capture part of a
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.
Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
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 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.