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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. 

Illustration of a real-time simulation showing a metallic nanoparticle’s optical response to light using RT-TDDFT. The image depicts electron oscillations and surrounding electromagnetic fields. Four inset panels represent applications: plasmon-enhanced biosensing, quantum computing, photochemical catalysis, and cancer detection through photothermal therapy.

A research team from the Department of Energy’s Oak Ridge National Laboratory, in collaboration with North Carolina State University, has developed a simulation capable of predicting how tens of thousands of electrons move in materials in real time, or natural time rather than compute time.

Two cabinets of ORNL's Frontier supercomputer are open to show the blue and red cords on the inside.

Working in collaboration with researchers from Oak Ridge National Laboratory, D-Wave Quantum Inc., a quantum computing systems, software and services provider, has shown its annealing quantum computing prototype has the potential to operate faster than the leading supercomputing systems. 

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. 

Illustration of a quantum experiment: atoms in a lattice (inset) with entanglement effects radiating from a central particle on a textured surface.

Working at nanoscale dimensions, billionths of a meter in size, a team of scientists led by ORNL revealed a new way to measure high-speed fluctuations in magnetic materials. Knowledge obtained by these new measurements could be used to advance technologies ranging from traditional computing to the emerging field of quantum computing. 

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. 

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.

quantum network illustration

Researchers at ORNL joined forces with EPB of Chattanooga and the University of Tennessee at Chattanooga to demonstrate the first transmission of an entangled quantum signal using multiple wavelength channels and automatic polarization stabilization over a commercial network with no downtime.

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.