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Media Contacts
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
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.
ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source and High Flux Isotope Reactor to better understand how certain cells in human tissue bond together.
Using the Titan supercomputer and the Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory, scientists have created the most accurate 3D model yet of an intrinsically disordered protein, revealing the ensemble of its atomic-level structures.
Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.
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
Scientists at the US Department of Energy’s Oak Ridge National Laboratory have demonstrated a method to insert genes into a variety of microorganisms that previously would not accept foreign DNA, with the goal of creating custom microbes to break down plants for bioenergy.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.