Skip to main content
Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.

 Using the ASGarD mathematical framework, scientists can model and visualize the electric fields, shown as arrows, circling around magnetic fields that are colorized to represent field magnitude of a fusion plasma. Credit: David Green/ORNL

Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.

This simulation of a fusion plasma calculation result shows the interaction of two counter-streaming beams of super-heated gas. Credit: David L. Green/Oak Ridge National Laboratory, U.S. Dept. of Energy

The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.

CellSight allows for rapid mass spectrometry of individual cells. Credit: John Cahill, Oak Ridge National Laboratory/U.S. Dept of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.

Layering on the strength

A team including Oak Ridge National Laboratory and University of Tennessee researchers demonstrated a novel 3D printing approach called Z-pinning that can increase the material’s strength and toughness by more than three and a half times compared to conventional additive manufacturing processes.

Heat impact map

A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns