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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.

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

Earth Day

Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time. 

Dongarra in 2019 with Oak Ridge National Laboratory's Summit supercomputer

A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.

An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

Miaofang Chi, a scientist in the Center for Nanophase Materials Sciences, received the 2021 Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy

A world-leading researcher in solid electrolytes and sophisticated electron microscopy methods received Oak Ridge National Laboratory’s top science honor today for her work in developing new materials for batteries. The announcement was made during a livestreamed Director’s Awards event hosted by ORNL Director Thomas Zacharia.

In a study, ORNL researchers concluded that the most direct path to plastic upcycling is through designing polymers specifically for reuse, which would allow the material to be converted into high-value products. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers determined that designing polymers specifically with upcycling in mind could reduce future plastic waste considerably and facilitate a circular economy where the material is used repeatedly.

ORNL researchers developed a novel process for manufacturing extreme heat resistant carbon-carbon composites at a faster rate and produced fins or strakes made of the materials for testing on a U.S. Navy rocket launching with NASA. Credit: ORNL, Sandia/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers have developed a novel process to manufacture extreme heat resistant carbon-carbon composites. The performance of these materials will be tested in a U.S. Navy rocket that NASA will launch this fall.

A 3D printed thermal protection shield, produced by ORNL researchers for NASA, is part of a cargo spacecraft bound for the International Space Station. The shield was printed at the Department of Energy’s Manufacturing Demonstration Facility at ORNL. Credit: ORNL, U.S. Dept. of Energy

A research team at Oak Ridge National Laboratory have 3D printed a thermal protection shield, or TPS, for a capsule that will launch with the Cygnus cargo spacecraft as part of the supply mission to the International Space Station.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.