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. 

Using a toolpath strategy for weight reduction, two near-net shape dies were manufactured using a gas metal arc welding additive manufacturing process at the Lincoln Electric Additive Solutions facility. Credit: Lincoln Electric

Recent advancements at ORNL show that 3D-printed metal molds offer a faster, more cost-effective and flexible approach to producing large composite components for mass-produced vehicles than traditional tooling methods.

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.

Illustration of the GRETA detector, a spherical array of metal cylinders. The detector is divided into two halves to show the inside of the machine. Both halves are attached to metal harnesses, displayed against a black and green cyber-themed background.

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.  

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. 

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. 

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. 

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.

Photo is a high aerial view of lake superior through the clouds

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast. 

A silicon-carbide-based thermal protection system developed by ORNL and Sierra Space researchers will be used on the Sierra Space DC100 Dream Chaser.

Researchers with the Department of Energy’s Oak Ridge National Laboratory and Sierra Space Corporation have developed a new silicon-carbide-based thermal protection system, or TPS, for reusable commercial spacecraft.