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Three ORNL researchers receive Outstanding Young Manufacturing Engineer Award

The Society of Manufacturing Engineers has honored three Oak Ridge National Laboratory researchers with the 2024 SME Susan Smyth Outstanding Young Manufacturing Engineer Award. 

ORNL

Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition. 

2023 Battelle Distinguished Inventors

Four scientists affiliated with ORNL were named Battelle Distinguished Inventors during the lab’s annual Innovation Awards on Dec. 1 in recognition of being granted 14 or more United States patents.

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.

Logo that reads U.S. Department of Energy INCITE Leadership Computing

The Department of Energy’s Office of Science has allocated supercomputer access to a record-breaking 75 computational science projects for 2024 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program. DOE is awarding 60% of the available time on the leadership-class supercomputers at DOE’s Argonne and Oak Ridge National Laboratories to accelerate discovery and innovation. 

Michael McGuire received the Director's Award for Outstanding Individual Accomplishment in Science and Technology at the 2023 Awards Night. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Michael McGuire’s recognition as the Oak Ridge National Laboratory's top scientist headlined the annual awards. ORNL Director Stephen Streiffer also presented Director’s Awards to two teams, for operational performance and continuous improvement, and to the night’s science communicator awardee

SM2ART team members receive the CAMX Combined Strength Award at the Georgia World Congress Center in Atlanta. Pictured here are, from left, ORNL’s Dan Coughlin, Sana Elyas, Halil Tekinalp, Amber Hubbard, Soydan Ozcan; University of Maine’s Susan MacKay, Angelina Buzzelli, Scott Tomlinson, Wesley Bisson; and ORNL’s Matt Korey and Vlastimil Kunc. Credit: University of Maine

The Hub & Spoke Sustainable Materials & Manufacturing Alliance for Renewable Technologies, or SM2ART, program has been honored with the composites industry’s Combined Strength Award at the Composites and Advanced Materials Expo, or CAMX, 2023 in Atlanta. This distinction goes to the team that applies their knowledge, resources and talent to solve a problem by making the best use of composites materials.

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.  

Oak Ridge National Laboratory entrance sign

The Department of Energy’s Office of Science has selected three ORNL research teams to receive funding through DOE’s new Biopreparedness Research Virtual Environment initiative.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine