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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

Researchers used Frontier, the world’s first exascale supercomputer, to simulate a magnesium system of nearly 75,000 atoms and the National Energy Research Computing Center’s Perlmutter supercomputer to simulate a quasicrystal structure, above, in a ytterbium-cadmium alloy. Credit: Vikram Gavini

Researchers used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.

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.   

Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.  

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.

ORNL’s RapidCure improves lithium-ion electrode production by producing electrodes faster, reducing the energy necessary for manufacturing and eliminating the need for a solvent recycling unit. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.

Adrian Sabau

Adrian Sabau of the Department of Energy’s Oak Ridge National Laboratory has been named an ASM International Fellow.

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.