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Marthi receives IEEE senior member honor
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Keeping aging structures safe
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Building energy around changing climate

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Researchers at ORNL and the University of Tennessee developed an automated workflow that combines chemical robotics and machine learning to speed the search for stable perovskites. Credit: Jaimee Janiga/ORNL, U.S. Dept of Energy

Automated chemistry sets new pace for materials discovery

Researchers at the Department of Energy’s Oak Ridge National Laboratory and the University of Tennessee are automating the search for new materials to advance solar energy technologies.

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

ORNL employees recognized with DOE Secretary’s Honor Awards

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.

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

Manufacturing – Defect detection

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.