Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
Over the past decade, teams of engineers, chemists and biologists have analyzed the physical and chemical properties of cicada wings, hoping to unlock the secret of their ability to kill microbes on contact. If this function of nature can be replicated by science, it may lead to products with inherently antibacterial surfaces that are more effective than current chemical treatments.
Creating energy the way the sun and stars do — through nuclear fusion — is one of the grand challenges facing science and technology. What’s easy for the sun and its billions of relatives turns out to be particularly difficult on Earth.
As a result of largescale 3D supernova simulations conducted on the Oak Ridge Leadership Computing Facility’s Summit supercomputer by researchers from the University of Tennessee and Oak Ridge National Laboratory, astrophysicists now have the most complete picture yet of what gravitational waves from exploding stars look like.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
Simulations performed on the Summit supercomputer at ORNL revealed new insights into the role of turbulence in mixing fluids and could open new possibilities for projecting climate change and studying fluid dynamics.
ORNL will team up with six of eight companies that are advancing designs and research and development for fusion power plants with the mission to achieve a pilot-scale demonstration of fusion within a decade.
Nature-based solutions are an effective tool to combat climate change triggered by rising carbon emissions, whether it’s by clearing the skies with bio-based aviation fuels or boosting natural carbon sinks.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.