Skip to main content
Illustration of melting point of lithium chloride, which is shown with green and blue structures in two rows.

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. 

A color-enhanced 3D laser scan of a large concrete slab in a housing development, showing surface variations in shades of blue, green, yellow, and purple. Surrounding structures and terrain are rendered in black and white. The image was captured using the FLAT tool’s 360-degree scanning technology.

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. 

A 3D printing nozzle wrapped in insulation extrudes black composite material into a small square mold on a green and white flat surface in a lab setting. Inset shows a close-up of a pressure gauge connected to brass valves and tubing.

Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces internal porosity by up to 75% in large-scale 3D-printed polymer parts. This new technique addresses the critical issue of porosity in large-scale prints but also paves the way for stronger composites. 

Animated graphic with a plant on the right, blue sphere on the left and blue glowing dots scattered throughout.

To help reduce the likelihood of losing future cultivated crops to drought and other seasonal hardships, researchers from ORNL, Budapest and Hungary are using neutrons, light microscopy and transmission electron microscopy to study the 'Never Never' plant, known for its ability to endure periods of little to no rain. 

Photo is a graphical representation of lithium ions (glowing orbs) move through a diffusion gate (gold triangle) in a solid-state electrolyte

A team of scientists led by a professor from Duke University discovered a way to help make batteries safer, charge faster and last longer. They relied on neutrons at ORNL to understand at the atomic scale how lithium moves in lithium phosphorus sulfur chloride, a promising new type of solid-state battery material known as a superionic compound. 

the foreground shows new macromolecules that could be made using a process invented by Oak Ridge National Laboratory chemists to upcycle the polymers from discarded plastics.

By editing the polymers of discarded plastics, ORNL chemists have found a way to generate new macromolecules with more valuable properties than those of the starting material.

Autonomous Configurable Component Evaluation Power Test platform, called ACCEPT, enabling automated characterization of semiconductor devices.

Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.

A graphic representation of AI

The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.

FAMU, FSU, FAMU-FSU College of Engineering, and Oak Ridge National Laboratory (ORNL) leadership

Oak Ridge National Laboratory has launched its Neutron Nexus pilot program with Florida Agricultural & Mechanical University and Florida State University through the FAMU-FSU College of Engineering. The first program of its kind nationwide, it’s aimed at broadening and diversifying the scientific user community with outreach to universities and colleges. 

This illustration demonstrates how atomic configurations with an equiatomic concentration of niobium (Nb), tantalum (Ta) and vanadium (V) can become disordered. The AI model helps researchers identify potential atomic configurations that can be used as shielding for housing fusion applications in a nuclear reactor. Credit: Massimiliano Lupo Pasini/ORNL, U.S. Dept. of Energy

A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.