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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. 

Light moves through a fiber and stimulates the metal electrons in nanotip into collective oscillations called surface plasmons, assisting electrons to leave the tip. This simple electron nano-gun can be made more versatile via different forms of material composition and structuring. Credit: Ali Passian/ORNL, U.S. Dept. of Energy

Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.

ORNL researchers developed a quantum, or squeezed, light approach for atomic force microscopy that enables measurement of signals otherwise buried by noise. Credit: Raphael Pooser/ORNL, U.S. Dept. of Energy

Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.