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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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Distinguished staff fellow Gang Seob “GS” Jung knew from an early age he wanted to be a scientist. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Gang Seob “GS” Jung: Solving scientific puzzles using computational models

Gang Seob “GS” Jung has known from the time he was in middle school that he was interested in science.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

ORNL neural network study harnesses made-to-order design to pair properties to materials

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

ORNL multimodal study sheds new light on promising photovoltaic material

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Artificially altered material could accelerate neuromorphic device development

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant

A selfie from the Curiosity rover as it explores the surface of Mars. Like many spacecraft, Curiosity uses a radioisotope power system to help fuel its mission. Credit: NASA/JPL-Caltech/MSSS

Radioisotope power systems for future missions may benefit from ORNL simulations

Radioactive isotopes power some of NASA’s best-known spacecraft. But predicting how radiation emitted from these isotopes might affect nearby materials is tricky

The electromagnetic isotope separator system operates by vaporizing an element such as ruthenium into the gas phase, converting the molecules into an ion beam, and then channeling the beam through magnets to separate out the different isotopes.

ORNL produces rare ruthenium isotope for atom smashing experiment

A tiny vial of gray powder produced at the Department of Energy’s Oak Ridge National Laboratory is the backbone of a new experiment to study the intense magnetic fields created in nuclear collisions.