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Artist’s conceptual drawing illustrates the novel energy filtering technique using neutrons that enabled researchers at ORNL to freeze moving germanium telluride atoms in an unblurred image. The images offered key insights into how the material produces its outstanding thermoelectric performance. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Scientists have long sought to better understand the “local structure” of materials, meaning the arrangement and activities of the neighboring particles around each atom. In crystals, which are used in electronics and many other applications, most of the atoms form highly ordered lattice patterns that repeat. But not all atoms conform to the pattern.

ORNL’s Tyler Spano examines a sample of uranyl nitrate solution that she uses as a precursor to many uranium oxide syntheses. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

The word “exotic” may not spark thoughts of uranium, but Tyler Spano’s investigations of exotic phases of uranium are bringing new knowledge to the nuclear nonproliferation industry.

Materials scientist Denise Antunes da Silva researches ways to reduce concrete’s embodied carbon in the Sustainable Building Materials Laboratory at ORNL, a research space dedicated to studying environmentally friendly building materials. Credit: ORNL, U.S. Dept. of Energy

Materials scientist Denise Antunes da Silva researches ways to reduce concrete’s embodied carbon in the Sustainable Building Materials Laboratory at ORNL, a research space dedicated to studying environmentally friendly building materials. Credit: ORNL, U.S. Dept. of Energy

Thomaz Carvalhaes. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.

The ORNL and Cummins CRADA led to the development of the R&D 100 Award-winning SpaciMS diagnostic tool that enabled researchers to gain a better understanding of reactor and catalytic chemistry. Credit: ORNL, U.S. Dept. of Energy

When Bill Partridge started working with industry partner Cummins in 1997, he was a postdoctoral researcher specializing in applied optical diagnostics and new to Oak Ridge National Laboratory.

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.

Jim Szybist, Propulsion Science section head at ORNL, is applying his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy.

What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.

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It’s been referenced in Popular Science and Newsweek, cited in the Economic Report of the President, and used by agencies to create countless federal regulations.

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.

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.