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In this artist’s conception of the process, an automated deposition system places a new material onto a base material (purple beam, right) as the last sample that was made is analyzed and sent to the AI (green beams, brain, left). The AI tells the pulsed laser deposition machine what to do next (data cable, bottom).
Researchers harness AI for autonomous discovery and optimization of materials
Students gather at a poster session
Students acquire skills at Quantum Science Center
Rectangular box being lifted by a red pully system up the left side of the building
Researchers make ‘green’ floor to replace steel

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Elizabeth Herndon uses spectroscopic techniques at ORNL to analyze the chemical composition of leaves and other environmental samples to better understand the soil carbon cycle. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

ORNL scientists dig into role of manganese in soil carbon and climate change

ORNL biogeochemist Elizabeth Herndon is working with colleagues to investigate a piece of the puzzle that has received little attention thus far: the role of manganese in the carbon cycle.

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.