Filter News
Area of Research
- (-) Nuclear Science and Technology (5)
- (-) Supercomputing (110)
- Advanced Manufacturing (5)
- Biological Systems (1)
- Biology and Environment (71)
- Building Technologies (2)
- Clean Energy (110)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (3)
- Computer Science (15)
- Electricity and Smart Grid (1)
- Energy Sciences (1)
- Functional Materials for Energy (1)
- Fusion and Fission (7)
- Fusion Energy (3)
- Isotopes (7)
- Materials (72)
- Materials for Computing (18)
- Mathematics (1)
- National Security (27)
- Neutron Science (26)
- Quantum information Science (8)
- Sensors and Controls (1)
News Topics
- (-) Biomedical (19)
- (-) Computer Science (96)
- (-) Microscopy (7)
- (-) Polymers (2)
- (-) Security (5)
- (-) Sustainable Energy (10)
- 3-D Printing/Advanced Manufacturing (8)
- Advanced Reactors (12)
- Artificial Intelligence (36)
- Big Data (20)
- Bioenergy (9)
- Biology (11)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (17)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (9)
- Decarbonization (5)
- Energy Storage (8)
- Environment (22)
- Exascale Computing (24)
- Frontier (29)
- Fusion (9)
- Grid (5)
- High-Performance Computing (40)
- Isotopes (7)
- Machine Learning (14)
- Materials (15)
- Materials Science (19)
- Mathematics (1)
- Molten Salt (5)
- Nanotechnology (11)
- National Security (8)
- Net Zero (1)
- Neutron Science (17)
- Nuclear Energy (39)
- Partnerships (1)
- Physics (10)
- Quantum Computing (19)
- Quantum Science (24)
- Simulation (15)
- Software (1)
- Space Exploration (8)
- Summit (43)
- Transformational Challenge Reactor (3)
- Transportation (6)
Media Contacts
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
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.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
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.
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.
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.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
The world is full of “huge, gnarly problems,” as ORNL research scientist and musician Melissa Allen-Dumas puts it — no matter what line of work you’re in. That was certainly the case when she would wrestle with a tough piece of music.