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.
While Tsouris’ water research is diverse in scope, its fundamentals are based on basic science principles that remain largely unchanged, particularly in a mature field like chemical engineering.
A joint research team from Google Inc., NASA Ames Research Center, and the Department of Energy’s Oak Ridge National Laboratory has demonstrated that a quantum computer can outperform a classical computer
The National Alliance for Water Innovation, a partnership of the Department of Energy’s Oak Ridge National Laboratory, other national labs, university and private sector partners, has been awarded a five-year, $100 million Energy-Water Desalination Hub by DOE to address water security issues in the United States.
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
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
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.
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
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.
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.