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low-cost material can be used as an additive to increase thermal insulation performance

Quanex Building Products has signed a non-exclusive agreement to license a method to produce insulating material from ORNL. The low-cost material can be used as an additive to increase thermal insulation performance and improve energy efficiency when applied to a variety of building products.

As part of DOE’s HPC4Mobility initiative ORNL researchers developed machine learning algorithms that can control smart traffic lights at intersections to facilitate the smooth flow of traffic and increase fuel efficiency.

A modern, healthy transportation system is vital to the nation’s economic security and the American standard of living. The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) is engaged in a broad portfolio of scientific research for improved mobility

Ethan Coon uses math and computational science to model the flow of above and belowground water in watersheds.

As a computational hydrologist at Oak Ridge National Laboratory, Ethan Coon combines his talent for math with his love of coding to solve big science questions about water quality, water availability for energy production, climate change, and the

Electro-Active Tech license signing ceremony

Electro-Active Technologies, Inc., of Knoxville, Tenn., has exclusively licensed two biorefinery technologies invented and patented by the startup’s co-founders while working at the Department of Energy’s Oak Ridge National Laboratory. The technologies work as a system that converts organic waste into renewable hydrogen gas for use as a biofuel.

Laccaria bicolor is fruiting aboveground and colonizing the Populus deltoides plant root system belowground in a greenhouse setting.

A team of scientists led by Oak Ridge National Laboratory have discovered the specific gene that controls an important symbiotic relationship between plants and soil fungi, and successfully facilitated the symbiosis in a plant that

Snowflakes indicate phases of super-cold ice

An ORNL-led team's observation of certain crystalline ice phases challenges accepted theories about super-cooled water and non-crystalline ice. Their findings, reported in the journal Nature, will also lead to better understanding of ice and its various phases found on other planets, moons and elsewhere in space.

U.S. Department of Energy and Cray to Deliver Record-Setting Frontier Supercomputer at ORNL

OAK RIDGE, Tenn., May 7, 2019—The U.S. Department of Energy today announced a contract with Cray Inc. to build the Frontier supercomputer at Oak Ridge National Laboratory, which is anticipated to debut in 2021 as the world’s most powerful computer with a performance of greater than 1.5 exaflops.

ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.

The illustrations show how the correlation between lattice distortion and proton binding energy in a material affects proton conduction in different environments. Mitigating this interaction could help researchers improve the ionic conductivity of solid materials.

Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.