Gina Tourassi has been appointed as director of the National Center for Computational Sciences, a division of the Computing and Computational Sciences Directorate at Oak Ridge National Laboratory.
Oak Ridge National Laboratory will give college students the chance to practice cybersecurity skills in a real-world setting as a host of the Department of Energy’s fifth collegiate CyberForce Competition on Nov. 16. The event brings together student teams from across the country to compete at 10 of DOE’s national laboratories.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
The U.S. Department of Energy announced funding for 12 projects with private industry to enable collaboration with DOE national laboratories on overcoming challenges in fusion energy development.
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.
Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network
Ask Tyler Gerczak to find a negative in working at the Department of Energy’s Oak Ridge National Laboratory, and his only complaint is the summer weather. It is not as forgiving as the summers in Pulaski, Wisconsin, his hometown.
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.
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.