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ORNL researcher Louise Evans is working to ensure safeguards approaches and verification technologies are integrated early in the design process of advanced reactor technologies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
Decades of nuclear expertise guides global nonproliferation innovation
To turn carbon dioxide, or CO2, into methanol, or CH3OH, copper (shown in yellow) on a hydride-substituted support speeds reactions mediated by hydrides and catalyzed by hydrogen atoms (shown in black) from surface-adsorbed formate, HCOO*. Credit: Yang He/ORNL, U.S. Dept. of Energy
Ion swap improves CO2-defeating catalyst
Caption: The Na-CO2 battery developed at ORNL, consisting of two electrodes in a saltwater solution, pulls atmospheric carbon dioxide into its electrochemical reaction, and releases only valuable biproducts. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy
Carbon-capture batteries store renewable energy

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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.

Modified deep-learning algorithms unveil features of shape-shifting proteins

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.

(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.

New ORNL AI tool revolutionizes process for matching cancer patients with clinical trials

OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.

To develop complex materials with superior properties, Vera Bocharova uses diverse methods including broadband dielectric spectroscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards

Vera Bocharova: Advancing the frontiers of knowledge about soft materials

Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.

ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La

Commuting—Oh, the places you’ll go

Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.