Filter News
Area of Research
- (-) Fusion and Fission (8)
- (-) Supercomputing (55)
- Advanced Manufacturing (3)
- Biological Systems (1)
- Biology and Environment (78)
- Biology and Soft Matter (1)
- Clean Energy (60)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Materials (15)
- Materials for Computing (2)
- National Security (14)
- Neutron Science (11)
- Nuclear Science and Technology (4)
- Quantum information Science (1)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (4)
- (-) Artificial Intelligence (21)
- (-) Bioenergy (4)
- (-) Buildings (3)
- (-) Composites (1)
- (-) Coronavirus (7)
- (-) Environment (14)
- (-) Exascale Computing (13)
- (-) Frontier (14)
- (-) Simulation (12)
- Advanced Reactors (2)
- Big Data (13)
- Biology (6)
- Biomedical (7)
- Biotechnology (1)
- Chemical Sciences (3)
- Climate Change (12)
- Computer Science (45)
- Cybersecurity (2)
- Decarbonization (4)
- Energy Storage (2)
- Fusion (12)
- Grid (2)
- High-Performance Computing (21)
- ITER (2)
- Machine Learning (7)
- Materials (4)
- Materials Science (8)
- Mathematics (1)
- Microscopy (2)
- Nanotechnology (5)
- National Security (3)
- Net Zero (2)
- Neutron Science (6)
- Nuclear Energy (19)
- Partnerships (1)
- Physics (4)
- Quantum Computing (10)
- Quantum Science (10)
- Security (1)
- Software (1)
- Space Exploration (1)
- Summit (21)
- Sustainable Energy (5)
- Transportation (4)
Media Contacts
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
Every day, hundreds of thousands of commuters across the country travel from houses, apartments and other residential spaces to commercial buildings — from offices and schools to gyms and grocery stores.
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 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.
The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.
An international problem like climate change needs solutions that cross boundaries, both on maps and among disciplines. Oak Ridge National Laboratory computational scientist Deeksha Rastogi embodies that approach.
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