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Media Contacts
At the National Center for Computational Sciences, Ashley Barker enjoys one of the least complicated–sounding job titles at ORNL: section head of operations. But within that seemingly ordinary designation lurks a multitude of demanding roles as she oversees the complete user experience for NCCS computer systems.
Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.
A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.
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.
ORNL has entered a strategic research partnership with the United Kingdom Atomic Energy Authority, or UKAEA, to investigate how different types of materials behave under the influence of high-energy neutron sources. The $4 million project is part of UKAEA's roadmap program, which aims to produce electricity from fusion.
A scientific instrument at ORNL could help create a noninvasive cancer treatment derived from a common tropical plant.
Warming a crystal of the mineral fresnoite, ORNL scientists discovered that excitations called phasons carried heat three times farther and faster than phonons, the excitations that usually carry heat through a material.
Paul Langan will join ORNL in the spring as associate laboratory director for the Biological and Environmental Systems Science Directorate.
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.