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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.

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.

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.

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the

This isotropic, neodymium-iron-boron bonded permanent magnet was 3D-printed at DOE’s Manufacturing Demonstration Facility at Oak Ridge National Laboratory.

Researchers at the Department of Energy’s Oak Ridge National Laboratory have demonstrated that permanent magnets produced by additive manufacturing can outperform bonded magnets made using traditional techniques while conserving critical materials. Scientists fabric...

ORNL Director Thom Mason (left) and Thomas Roberts of Oddello Industries LLC sign a research and development agreement.

A process developed at Oak Ridge National Laboratory for large-scale recovery of rare earth magnets from used computer hard drives will undergo industrial testing under a new agreement between Oddello Industries LLC and ORNL, as part of the Department of Energy’s Crit...

Default image of ORNL entry sign

A new technology developed by the U.S. Department of Energy’s Critical Materials Institute that aids in the recycling, recovery and extraction of rare earth minerals has been licensed to U.S. Rare Earths, Inc.