Oak Ridge National Laboratory scientists designed a recyclable polymer for carbon-fiber composites to enable circular manufacturing of parts that boost energy efficiency in automotive, wind power and aerospace applications.
Nine student physicists and engineers from the #1-ranked Nuclear Engineering and Radiological Sciences Program at the University of Michigan, or UM, attended a scintillation detector workshop at Oak Ridge National Laboratory Oct. 10-13.
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.
Sheng Dai, a Corporate Fellow and section head at the Department of Energy’s Oak Ridge National Laboratory, has been selected by the DOE Office of Science as a 2023 Distinguished Scientist Fellow.
Rama Vasudevan, a research scientist at the Department of Energy’s Oak Ridge National Laboratory, has been elected a Fellow of the American Physical Society, or APS. The honor recognizes members who have made significant contributions to physics and its application to science and technology.
Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.
Oak Ridge National Laboratory scientists recently demonstrated a low-temperature, safe route to purifying molten chloride salts that minimizes their ability to corrode metals. This method could make the salts useful for storing energy generated from the sun’s heat.
Researchers at ORNL and the University of Tennessee, Knoxville, discovered a key material needed for fast-charging lithium-ion batteries. The commercially relevant approach opens a potential pathway to improve charging speeds for electric vehicles.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
Researchers from ORNL, the University of Tennessee at Chattanooga and Tuskegee University used mathematics to predict which areas of the SARS-CoV-2 spike protein are most likely to mutate.