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Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.

Researchers at Oak Ridge National Laboratory demonstrated center-of-mass scanning transmission electron microscopy to observe lithium along with heavier elements in battery materials at atomic resolution. Credit: Chad Malone/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers demonstrated an electron microscopy technique for imaging lithium in energy storage materials, such as lithium ion batteries, at the atomic scale.

Results show change in annual aridity for the years 2071-2100 compared to 1985-2014. Brown shadings (negative numbers) indicate drier conditions. Black dots indicate statistical significance at the 90% confidence level. Credit: Jiafu Mao/ORNL, U.S. Dept. of Energy

A new analysis from Oak Ridge National Laboratory shows that intensified aridity, or drier atmospheric conditions, is caused by human-driven increases in greenhouse gas emissions. The findings point to an opportunity to address and potentially reverse the trend by reducing emissions.

ORNL’s Eva Zarkadoula seeks piezoelectric materials for sensors that can withstand irradiation, which causes cascading collisions that displace atoms and produces defects. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

To advance sensor technologies, Oak Ridge National Laboratory researchers studied piezoelectric materials, which convert mechanical stress into electrical energy, to see how they could handle bombardment with energetic neutrons.

Researchers used an atomic force microscope to test how easily particles of the novel coronavirus cling to certain surfaces, a property known as adhesion energy. Credit: Ali Passian/ORNL, U.S. Dept. of Energy

A study by Department of Energy researchers detailed a potential method to detect the novel coronavirus

An ORNL research team has incorporated important effects from microbially-active hot spots near streams into models that track the movement of nutrients and contaminants in river networks. The integrated model better tracks water quality indicators and facilitates new science. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

A new modeling capability developed at Oak Ridge National Laboratory incorporates important biogeochemical processes happening in river corridors for a clearer understanding of how water quality will be impacted by climate change, land use and

The first central solenoid module arrived at the ITER site in St. Paul-lez-Durance, France on Sept. 9. Credit: ITER Organization

Staff at Oak Ridge National Laboratory organized transport for a powerful component that is critical to the world’s largest experiment, the international ITER project.

Fine roots from a larch tree peek out from a pile of peat excavated from an experimental warming plot in the SPRUCE experiment in Northern Minnesota. Credit: Colleen Iversen/ORNL, U.S. Dept. of Energy

New data hosted by Oak Ridge National Laboratory is helping scientists around the world understand the secret lives of plant roots as well as their impact on the global carbon cycle and climate change.

Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.

Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.