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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 AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE

A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules. 

Luiz Leal portrait

ORNL’s Luiz Leal of the Department of Energy’s Oak Ridge National Laboratory is the recipient of the 2023 Seaborg Medal from the American Nuclear Society.

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.  

JungHyun Bae portrait

JungHyun Bae is a nuclear scientist studying applications of particles that have some beneficial properties: They are everywhere, they are unlimited, they are safe.

CFM’s RISE open fan engine architecture. Image: GE Aerospace

To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.

An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL

Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.

Oak Ridge National Laboratory led a team of scientists to design a molecule that disrupts the infection mechanism of the SARS-CoV-2 coronavirus and could be used to develop new treatments for COVID-19 and future virus outbreaks. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory designed a molecule that disrupts the infection mechanism of the SARS-CoV-2 coronavirus and could be used to develop new treatments for COVID-19 and other viral diseases.

Oak Ridge National Laboratory’s software suite AutoBEM is being used in the architecture, city planning, real estate and home efficiency industries. Users take advantage of the suite’s energy modeling of almost all U.S. buildings. Credit: ORNL, U.S. Dept. of Energy

Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.

Solar panels funded by the Honnold Foundation are installed in Adjuntas, Puerto Rico. Credit: Fabio Andrade

When Hurricane Maria battered Puerto Rico in 2017, winds snapped trees and destroyed homes, while heavy rains transformed streets into rivers. But after the storm passed, the human toll continued to grow as residents struggled without electricity for months. Five years later, power outages remain long and frequent.