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Media Contacts
The Department of Energy’s Office of Science has allocated supercomputer access to a record-breaking 75 computational science projects for 2024 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program. DOE is awarding 60% of the available time on the leadership-class supercomputers at DOE’s Argonne and Oak Ridge National Laboratories to accelerate discovery and innovation.
A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
Lawrence Livermore National Laboratory’s Lori Diachin will take over as director of the Department of Energy’s Exascale Computing Project on June 1, guiding the successful, multi-institutional high-performance computing effort through its final stages.
A study led by Oak Ridge National Laboratory researchers identifies a new potential application in quantum computing that could be part of the next computational revolution.
ORNL has named Michael Parks director of the Computer Science and Mathematics Division within ORNL’s Computing and Computational Sciences Directorate. His hiring became effective March 13.
A study by Oak Ridge National Laboratory researchers has demonstrated how satellites could enable more efficient, secure quantum networks.
Three researchers at ORNL have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.