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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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In situ monitoring to evaluate nickel-based superalloys as they are printing gave Mike Kirka, an ORNL materials scientist, the ability to see potential weaknesses that could lead to part failure. Credit: ORNL/U.S. Dept. of Energy

Mike Kirka: Turning up the heat on additive manufacturing materials

Growing up in the heart of the American automobile industry near Detroit, Oak Ridge National Laboratory materials scientist Mike Kirka was no stranger to manufacturing.

The 2021 Fuel Economy Guide, compiled by ORNL researchers, provides tips for keeping fuel costs down and helps consumers find the most fuel-efficient vehicle. Credit: ORNL/U.S. Dept. of Energy

Transportation – Easy on the pedals

Fuel economy can take a tumble when temperatures plummet, according to the Department of Energy’s 2021 Fuel Economy Guide. Compiled by researchers at Oak Ridge National Laboratory, the guide includes several tips to improve a vehicle’s fuel performance.

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.