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ORNL recognized the small businesses that have made a positive impact on ORNL’s operations at the virtual 2020 Small Business Awards. Credit: ORNL, U.S. Dept. of Energy

Thirty-two Oak Ridge National Laboratory employees were named among teams recognized by former DOE Secretary Dan Brouillette with Secretary’s Honor Awards as he completed his term. Four teams received new awards that reflect DOE responses to the coronavirus pandemic.

Merlin Theodore holding N95 mask filtration material produced at DOE's Carbon Fiber Technology Facility

Three technologies developed by ORNL researchers have won National Technology Transfer Awards from the Federal Laboratory Consortium. One of the awards went to a team that adapted melt-blowing capabilities at DOE’s Carbon Fiber Technology Facility to enable the production of filter material for N95 masks in the fight against COVID-19.

Researchers at ORNL’s Center for Nanophase Materials Sciences and the University of Tennessee Health Science Center partnered to design a COVID-19 screening whistle for convenient home testing. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Collaborators at Oak Ridge National Laboratory and the University of Tennessee Health Science Center are developing a breath-sampling whistle that could make COVID-19 screening easy to do at home.

The TRITON model provides a detailed visualization of the flooding that resulted when Hurricane Harvey stalled over Houston for four days in 2017. Credit: Mario Morales-Hernández/ORNL, U.S. Dept. of Energy

A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.

An international research team used scanning tunneling microscopy at ORNL to send and receive single molecules across a surface on an atomically precise track. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences contributed to a groundbreaking experiment published in Science that tracks the real-time transport of individual molecules.

An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy

Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.