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Veda Galigekere is leading Oak Ridge National Laboratory’s work on fast, efficient, wireless charging of electric vehicles.

Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.

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.

Scott Smith holding machined aluminum part

When Scott Smith looks at a machine tool, he thinks not about what the powerful equipment used to shape metal can do – he’s imagining what it could do with the right added parts and strategies. As ORNL’s leader for a newly formed group, Machining and Machine Tool Research, Smith will have the opportunity to do just that.

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.

Alex Roschli in front of BAAM

Alex Roschli is no stranger to finding himself in unique situations. After all, the early career researcher in ORNL’s Manufacturing Systems Research group bears a last name that only 29 other people share in the United States, and he’s certain he’s the only Roschli (a moniker that hails from Switzerland) with the first name Alex.

The concrete parts are installed in a residential and commercial tower (above center and below) on the site of the Domino Sugar Factory along the waterfront in Brooklyn. Windows in the tower resemble sugar crystals. Image credit: Gate Precast

A residential and commercial tower under development in Brooklyn that is changing the New York City skyline has its roots in research at the Department of Energy’s Oak Ridge National Laboratory.

ORNL’s Manjunath Gorentla Venkata helped develop a new approach to analyze thousands of genetic samples by connecting powerful computing resources.

Computing experts at the Department of Energy’s Oak Ridge National Laboratory collaborated with a team of university researchers and software companies to develop a novel hybrid computational strategy to efficiently discover genetic variants