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ORNL

ORNL took home the top honors in three categories at the second annual DOE Geospatial Science Poster competition, held on National GIS Day. For the second year in a row, DOE awarded ORNL top prize as Best Geospatial Program. Additionally, ORNL geospatial researchers took home first place prizes for their posters in the Best Departmental Element Alignment and Best Cartography categories.

LCDR Rich Harvey, pictured on the left, poses with two colleagues at the 2023 POST Conference. Credit: Rich Harvey

Lieutenant Commander Rich Harvey has spent the last three decades of his career serving his country. Harvey's efforts supporting the Office of Naval Research has earned him the 2023 Junior Scientist Officer of the Year award for coordination and computer modeling support for a project called TALISMAN, his leadership roles and other exemplary service markers. 

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.

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.  

State and Local Economic Development Award

A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.

Ilias Belharouak, Grace Burke and Phil Snyder represent ORNL’s strengths in battery technology, materials science and fusion energy research.

Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.

From left, Craig Moss, Major Micah McCracken, Tim Delk and Lt. Col. Jessica Critcher pose with awards given at a small ceremony recognizing ORNL’s 2022 military fellows. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

In front of family and friends, Lt. Col. Jessica Critcher and Maj. Micah McCracken gave their final report on their eye-opening year as ORNL military fellows.

Oak Ridge National Laboratory researchers quantified human behaviors during the early days of COVID-19, which could be useful for disaster response or city planning. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have empirically quantified the shifts in routine daytime activities, such as getting a morning coffee or takeaway dinner, following safer at home orders during the early days of the COVID-19 pandemic.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.