Filter News
Area of Research
News Topics
- (-) Clean Water (3)
- (-) Climate Change (3)
- (-) Machine Learning (2)
- 3-D Printing/Advanced Manufacturing (4)
- Advanced Reactors (1)
- Artificial Intelligence (3)
- Big Data (3)
- Bioenergy (4)
- Biology (5)
- Biomedical (2)
- Buildings (8)
- Chemical Sciences (2)
- Composites (2)
- Computer Science (4)
- Coronavirus (4)
- Critical Materials (3)
- Decarbonization (1)
- Energy Storage (6)
- Environment (5)
- Exascale Computing (1)
- Grid (4)
- High-Performance Computing (4)
- Hydropower (5)
- Irradiation (1)
- Isotopes (1)
- Materials (11)
- Materials Science (3)
- Microscopy (3)
- Nanotechnology (2)
- National Security (3)
- Neutron Science (2)
- Partnerships (1)
- Physics (1)
- Polymers (1)
- Quantum Science (2)
- Simulation (2)
- Space Exploration (3)
- Summit (1)
- Sustainable Energy (6)
- Transportation (2)
Media Contacts
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
Measuring water quality throughout river networks with precision, speed and at lower cost than traditional methods is now possible with AquaBOT, an aquatic drone developed by Oak Ridge National Laboratory.
Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.
A new analysis from Oak Ridge National Laboratory shows that intensified aridity, or drier atmospheric conditions, is caused by human-driven increases in greenhouse gas emissions. The findings point to an opportunity to address and potentially reverse the trend by reducing emissions.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.