Katy Bradford: Cassette approach offers compelling construction solution
Filter News
Area of Research
- (-) Computational Engineering (2)
- (-) Materials for Computing (1)
- Advanced Manufacturing (2)
- Biology and Environment (30)
- Clean Energy (61)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computer Science (9)
- Electricity and Smart Grid (3)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Fusion Energy (8)
- Materials (18)
- National Security (27)
- Neutron Science (13)
- Nuclear Science and Technology (11)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (1)
- Sensors and Controls (1)
- Supercomputing (76)
News Type
News Topics
- (-) Artificial Intelligence (1)
- (-) Machine Learning (1)
- (-) Summit (2)
- 3-D Printing/Advanced Manufacturing (4)
- Big Data (1)
- Bioenergy (1)
- Biology (1)
- Biomedical (3)
- Chemical Sciences (4)
- Clean Water (1)
- Climate Change (2)
- Composites (1)
- Computer Science (10)
- Coronavirus (3)
- Decarbonization (1)
- Energy Storage (4)
- Environment (2)
- High-Performance Computing (1)
- Isotopes (1)
- Materials (10)
- Materials Science (15)
- Mathematics (1)
- Microscopy (4)
- Nanotechnology (7)
- National Security (1)
- Neutron Science (5)
- Polymers (6)
- Quantum Computing (1)
- Quantum Science (3)
- Security (1)
- Simulation (1)
- Space Exploration (1)
- Sustainable Energy (5)
- Transportation (5)
Media Contacts
A team including researchers from the Department of Energy’s Oak Ridge National Laboratory has developed a digital tool to better monitor a condition known as Barrett’s esophagus, which affects more than 3 million people in the United States.
In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool