Strengthening the competitiveness of the U.S. transportation industry depends on developing domestic EV batteries that combine rapid charging with long-range performance — two goals that often conflict.
Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.
Massimiliano “Max” Lupo Pasini, a data scientist at the Department of Energy’s Oak Ridge National Laboratory, was named a senior member of the , the world’s larges
Mariam Kiran, a quantum research scientist at the Department of Energy’s Oak Ridge National Laboratory, was recently honored as a finalist at the British Council’s Study U.K. Alumni Awards 2025, which celebrate the achievements of U.K.
In a major milestone for cancer research, the Department of Energy’s Oak Ridge National Laboratory helped reduce the time between cancer diagnosis and pathology report processing from 22 months to just 14 months, utilizing advanced artificial
Massimiliano (Max) Lupo Pasini, an R&D data scientist from ORNL, was awarded the National Energy Research Scientific Computing Center’s High Performance Computing Achievement Award for High Impact Scientific Achievement fo
Researchers at ORNL joined forces with EPB of Chattanooga and the University of Tennessee at Chattanooga to demonstrate the first transmission of an entangled quantum signal using multiple wavelength channels and automatic polarization stabilization ove
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.