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ORNL researchers are perfecting ways to use drones to check remote parts of the electric grid for dangerous electrical arcing that could start wildfires. Credit: ORNL, U.S. Dept. of Energy

As climate change leads to larger and more frequent wildfires, researchers at ORNL are using sensors, drones and machine learning to both prevent fires and reduce their damage to the electric grid.

Melton Hill Dam

To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.

The AI-driven HyperCT platform has three primary points of articulation that can rotate a sample in almost any direction, eliminating the need for human intervention and significantly reducing lengthy experiment times. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT.

ORNL identity science researcher Nell Barber works on a facial recognition camera. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.

Burak Ozpineci, a Corporate Fellow and section head of Vehicle and Mobility Systems Research at Oak Ridge National Laboratory, is one of six international recipients of the eighth Nagamori Award recognizing his contributions to electrification in transportation. Credit: ORNL, U.S. Dept. of Energy

Burak Ozpineci, a Corporate Fellow and section head for Vehicle and Mobility Systems Research at Oak Ridge National Laboratory, is one of six international recipients of the eighth Nagamori Award.

ORNL’s Bruce Pint, left, and Marie Romedenne review experiment results. Credit: ORNL, U.S. Dept. of Energy

Practical fusion energy is not just a dream at ORNL. Experts in fusion and material science are working together to develop solutions that will make a fusion pilot plant — and ultimately carbon-free, abundant fusion electricity — possible.

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.

Frontier has arrived, and ORNL is preparing for science on Day One. Credit: Carlos Jones/ORNL, Dept. of Energy

The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.

Logan Sturm, Alvin M. Weinberg Fellow at ORNL, creates a mashup between additive manufacturing and cybersecurity research. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components

A team of fusion scientists and engineers stand in front of ORNL’s Helium Flow Loop device. From back left to front right: Chris Crawford, Fayaz Rasheed, Joy Fan, Michael Morrow, Charles Kessel, Adam Carroll, and Cody Wiggins. Not pictured: Dennis Youchison and Monica Gehrig. Credit: Carlos Jones/ORNL.

To achieve practical energy from fusion, extreme heat from the fusion system “blanket” component must be extracted safely and efficiently. ORNL fusion experts are exploring how tiny 3D-printed obstacles placed inside the narrow pipes of a custom-made cooling system could be a solution for removing heat from the blanket.