
Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (19)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (5)
- Energy Science (19)
- Fusion and Fission (2)
- Fusion Energy (6)
- Isotopes (3)
- Materials (10)
- Materials for Computing (2)
- Mathematics (1)
- National Security (2)
- Neutron Science (24)
- Nuclear Science and Technology (6)
- Quantum information Science (1)
- Supercomputing (10)
News Type
News Topics
- (-) Artificial Intelligence (16)
- (-) Biomedical (11)
- (-) Environment (48)
- (-) Fusion (9)
- (-) Isotopes (5)
- (-) Mercury (3)
- (-) Neutron Science (27)
- (-) Physics (4)
- (-) Security (1)
- (-) Space Exploration (10)
- 3-D Printing/Advanced Manufacturing (34)
- Advanced Reactors (13)
- Big Data (17)
- Bioenergy (17)
- Biology (21)
- Biotechnology (4)
- Buildings (21)
- Chemical Sciences (13)
- Clean Water (14)
- Composites (11)
- Computer Science (42)
- Coronavirus (11)
- Critical Materials (12)
- Cybersecurity (3)
- Emergency (1)
- Energy Storage (32)
- Exascale Computing (1)
- Fossil Energy (1)
- Frontier (1)
- Grid (22)
- High-Performance Computing (12)
- Hydropower (6)
- Irradiation (2)
- ITER (3)
- Machine Learning (14)
- Materials (36)
- Materials Science (34)
- Mathematics (3)
- Microscopy (11)
- Molten Salt (5)
- Nanotechnology (12)
- National Security (3)
- Nuclear Energy (19)
- Partnerships (2)
- Polymers (10)
- Quantum Computing (5)
- Quantum Science (12)
- Simulation (9)
- Statistics (1)
- Summit (8)
- Transportation (36)
Media Contacts

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.

Researchers at ORNL have developed a tool that gives builders a quick way to measure, correct and certify level foundations. FLAT, or the Flat and Level Analysis Tool, examines a 360-degree laser scan of a construction site using ORNL-developed segmentation algorithms and machine learning to locate uneven areas on a concrete slab.

The ForWarn visualization tool was co-developed by ORNL with the U.S. Forest Service. The tool captures and analyzes satellite imagery to track impacts such as storms, wildfire and pests on forests across the nation.

Researchers have identified a molecule essential for the microbial conversion of inorganic mercury into the neurotoxin methylmercury, moving closer to blocking the dangerous pollutant before it forms.

Oak Ridge National Laboratory researchers are using a new bioderived material to 3D print custom roosting structures for endangered bats.

In a game-changing study, ORNL scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition.

Scientists using high-resolution aerial scans and computational modeling concluded that wildfires, storms and selective logging have become key drivers behind rainforest carbon emissions, outpacing clear-cutting practices.

A research team led by the Department of Energy’s Oak Ridge National Laboratory demonstrated an effective and reliable new way to identify and quantify polyethylene glycols in various samples.

Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.

An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.