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Oak Ridge National Laboratory materials scientist Zhili Feng, left, looks on as senior technician Doug Kyle operates a welding robot inside a robotic welding cell. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

The U.S. Departments of Energy and Defense teamed up to create a series of weld filler materials that could dramatically improve high-strength steel repair in vehicles, bridges and pipelines.

Field emission scanning electron microscopy reveals the microstructure of the porous activated carbon that can confine hydrogen at the nanoscale. Credit: Joaquin Silvestre-Albero

Neutron scattering techniques were used as part of a study of a novel nanoreactor material that grows crystalline hydrogen clathrates, or HCs, capable of storing hydrogen.

ORNL’s Tomás Rush explores the secret lives of fungi and plants for insights into the interactions that determine plant health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.

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 probed the chemistry of radium to gain key insights on advancing cancer treatments using radiation therapy. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.

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

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

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.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.