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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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ORNL researchers observed that atomic vibrations in a twisted crystal result in winding energetic waves that govern heat transport, which may help new materials better manage heat. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Materials – Fresh twist on heat

A discovery by Oak Ridge National Laboratory researchers may aid the design of materials that better manage heat.

An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Energy – Building a better thermostat

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

Transition metals stitched into graphene with an electron beam form promising quantum building blocks. Credit: Ondrej Dyck, Andrew Lupini and Jacob Swett/ORNL, U.S. Dept. of Energy

Materials – Quantum building blocks

Oak Ridge National Laboratory scientists demonstrated that an electron microscope can be used to selectively remove carbon atoms from graphene’s atomically thin lattice and stitch transition-metal dopant atoms in their place.