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Strain-tolerant, triangular, monolayer crystals of WS2 were grown on SiO2 substrates patterned with donut-shaped pillars, as shown in scanning electron microscope (bottom) and atomic force microscope (middle) image elements.

A team led by scientists at the Department of Energy’s Oak Ridge National Laboratory explored how atomically thin two-dimensional (2D) crystals can grow over 3D objects and how the curvature of those objects can stretch and strain the 

Materials—Engineering heat transport

Scientists have discovered a way to alter heat transport in thermoelectric materials, a finding that may ultimately improve energy efficiency as the materials

The researchers used the new model to accurately identify clusters of gene mutations (spheres), which helped them study the emergence of various genetic diseases. Image credit: Ivaylo Ivanov, Georgia State University.

Environmental conditions, lifestyle choices, chemical exposure, and foodborne and airborne pathogens are among the external factors that can cause disease. In contrast, internal genetic factors can be responsible for the onset and progression of diseases ranging from degenerative neurological disorders to some cancers.

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.

Pictured in this early conceptual drawing, the Translational Research Capability planned for Oak Ridge National Laboratory will follow the design of research facilities constructed during the laboratory’s modernization campaign.

OAK RIDGE, Tenn., May 7, 2019—Energy Secretary Rick Perry, Congressman Chuck Fleischmann and lab officials today broke ground on a multipurpose research facility that will provide state-of-the-art laboratory space 

Virtual universes

Using Summit, the world’s most powerful supercomputer housed at Oak Ridge National Laboratory, a team led by Argonne National Laboratory ran three of the largest cosmological simulations known to date.

Small modular reactor computer simulation

In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.

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.

ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL

Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.

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.