Filter News
Area of Research
- (-) Supercomputing (81)
- Advanced Manufacturing (5)
- Biological Systems (1)
- Biology and Environment (30)
- Building Technologies (1)
- Clean Energy (38)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (12)
- Fusion and Fission (3)
- Fusion Energy (4)
- Isotopes (5)
- Materials (61)
- Materials for Computing (14)
- Mathematics (1)
- National Security (16)
- Neutron Science (23)
- Nuclear Science and Technology (5)
- Quantum information Science (7)
- Transportation Systems (1)
News Type
News Topics
- (-) Artificial Intelligence (22)
- (-) Biomedical (11)
- (-) Computer Science (61)
- (-) Materials Science (9)
- (-) Microscopy (2)
- (-) Physics (3)
- (-) Quantum Science (13)
- (-) Security (1)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (1)
- Big Data (17)
- Bioenergy (3)
- Biology (7)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (2)
- Climate Change (14)
- Coronavirus (9)
- Critical Materials (3)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (2)
- Environment (17)
- Exascale Computing (13)
- Frontier (14)
- Fusion (1)
- Grid (1)
- High-Performance Computing (23)
- Machine Learning (8)
- Materials (5)
- Mathematics (1)
- Nanotechnology (6)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (3)
- Polymers (2)
- Quantum Computing (14)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Summit (27)
- Sustainable Energy (4)
- Transportation (4)
Media Contacts
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.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
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.
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.
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