Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Elizabeth Herndon believes in going the distance whether she is preparing to compete in the 2020 Olympic marathon trials or examining how metals move through the environment as a geochemist at the Department of Energy’s Oak Ridge National Laboratory.
In the vast frozen whiteness of the central Arctic, the Polarstern, a German research vessel, has settled into the ice for a yearlong float.
Two of the researchers who share the Nobel Prize in Chemistry announced Wednesday—John B. Goodenough of the University of Texas at Austin and M. Stanley Whittingham of Binghamton University in New York—have research ties to ORNL.
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
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.
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.
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.
The use of lithium-ion batteries has surged in recent years, starting with electronics and expanding into many applications, including the growing electric and hybrid vehicle industry. But the technologies to optimize recycling of these batteries have not kept pace.