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ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

A simulation of the planet from the DOE Energy Exascale Earth System Model, one of the large-scale models incorporated in the Earth System Grid Federation led by DOE’s Oak Ridge, Argonne and Lawrence Livermore national laboratories. Credit: LLNL, U.S. Dept. of Energy

The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.

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 has known from the time he was in middle school that he was interested in science.

From left to right, Cortney Piper, executive director of the Tennessee Advanced Energy Business Council; Susan Hubbard, ORNL deputy for science and technology; Dan Miller, innovation Crossroads program lead; and Mike Paulus, ORNL director of technology transfer, attend the Innovation Crossroads Showcase at the Knoxville Chamber on Sept. 22. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A crowd of investors and supporters turned out for last week’s Innovation Crossroads Showcase at the Knoxville Chamber as part of Innov865 Week. Sponsored by ORNL and the Tennessee Advanced Energy Business Council, the event celebrated deep-tech entrepreneurs and the Oak Ridge Corridor as a growing energy innovation hub for the nation.

Researchers at Oak Ridge National Laboratory designed an adsorbent material to rapidly remove toxic chromium and arsenic simultaneously from water resources. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are tackling a global water challenge with a unique material designed to target not one, but two toxic, heavy metal pollutants for simultaneous removal.

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.

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

LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy

It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.

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.

Oak Ridge National Laboratory researchers built an Earth-to-space communications system to work with private and government partners with the goal of directly connecting data downlinks to high performance computing. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.