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3D printed “Frankenstein design” collimator show the “scars” where the individual parts are joined

Scientists at ORNL have developed 3D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments

The 25th annual National School on Neutron and X-ray Scattering was held August 6–18. Each year, graduate students visit Oak Ridge and Argonne National Laboratories to learn how to use neutrons and X-rays to study energy and materials. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

In 2023, the National School on X-ray and Neutron Scattering, or NXS, marked its 25th year during its annual program, held August 6–18 at the Department of Energy’s Oak Ridge and Argonne National Laboratories.   

Researchers at the Department of Energy’s Oak Ridge National Laboratory were the first to use neutron reflectometry to peer inside a working solid-state battery and monitor its electrochemistry.

Researchers at the Department of Energy’s Oak Ridge National Laboratory were the first to use neutron reflectometry to peer inside a working solid-state battery and monitor its electrochemistry.

Artist’s conceptual drawing illustrates the novel energy filtering technique using neutrons that enabled researchers at ORNL to freeze moving germanium telluride atoms in an unblurred image. The images offered key insights into how the material produces its outstanding thermoelectric performance. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Scientists have long sought to better understand the “local structure” of materials, meaning the arrangement and activities of the neighboring particles around each atom. In crystals, which are used in electronics and many other applications, most of the atoms form highly ordered lattice patterns that repeat. But not all atoms conform to the pattern.

Distinguished staff fellow Gang Seob “GS” Jung knew from an early age he wanted to be a scientist. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Gang Seob “GS” Jung has known from the time he was in middle school that he was interested in science.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant

Small, 3D-printed neutron collimators, designed by ORNL’s Jamie Molaison, yield reduced costs and manufacturing times and could enable new types of experiments. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The ExOne Company, the global leader in industrial sand and metal 3D printers using binder jetting technology, announced it has reached a commercial license agreement with Oak Ridge National Laboratory to 3D print parts in aluminum-infiltrated boron carbide.