ORNL's Communications team works with news media seeking information about the laboratory. Media may use the resources listed below or send questions to news@ornl.gov.
411 - 420 of 979 Results
Friederike (Rike) Bostelmann, who began her career in Germany, chose to come to ORNL to become part of the Lab’s efforts to shape the future of nuclear energy.
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
Jennifer Morrell-Falvey’s interest in visualizing the science behind natural processes was what drew her to ORNL in what she expected to be a short stint some 18 years ago.
To achieve practical energy from fusion, extreme heat from the fusion system “blanket” component must be extracted safely and efficiently. ORNL fusion experts are exploring how tiny 3D-printed obstacles placed inside the narrow pipes of a custom-made cooling system could be a solution for removing heat from the blanket.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.
The Center of Science and Industry, the number-one science center in the country by USA Today’s 10Best, Oak Ridge National Laboratory, the U.S. Department of Energy and the Tennessee STEM Innovation Network have kicked off a new program in Tennessee
It’s been referenced in Popular Science and Newsweek, cited in the Economic Report of the President, and used by agencies to create countless federal regulations.
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.