Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Collaborators at Oak Ridge National Laboratory and the University of Tennessee Health Science Center are developing a breath-sampling whistle that could make COVID-19 screening easy to do at home.
In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.
Scientists at Oak Ridge National Laboratory and the University of Tennessee designed and demonstrated a method to make carbon-based materials that can be used as electrodes compatible with a specific semiconductor circuitry.
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.
Kübra Yeter-Aydeniz, a postdoctoral researcher, was recently named the Turkish Women in Science group’s “Scientist of the Week.”
Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed a new method to peer deep into the nanostructure of biomaterials without damaging the sample. This novel technique can confirm structural features in starch, a carbohydrate important in biofuel production.
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.