Scientists at Oak Ridge National Laboratory used new techniques to create a composite that increases the electrical current capacity of copper wires, providing a new material that can be scaled for use in ultra-efficient, power-dense electric vehicle traction motors.
The combination of bioenergy with carbon capture and storage could cost-effectively sequester hundreds of millions of metric tons per year of carbon dioxide in the United States, making it a competitive solution for carbon management, according to a new analysis by ORNL scientists.
Prometheus Fuels has licensed an ethanol-to-jet-fuel conversion process developed by researchers at Oak Ridge National Laboratory. The ORNL technology will enable cost-competitive production of jet fuel and co-production of butadiene for use in renewable polymer synthesis.
ORNL scientists have modified a single microbe to simultaneously digest five of the most abundant components of lignocellulosic biomass, a big step forward in the development of a cost-effective biochemical conversion process to turn plants into
Kübra Yeter-Aydeniz, a postdoctoral researcher, was recently named the Turkish Women in Science group’s “Scientist of the Week.”
Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.
Scientists at Oak Ridge National Laboratory and Ohio State University discovered a new microbial pathway that produces ethylene, providing a potential avenue for biomanufacturing a common component of plastics, adhesives, coolants and other
The Department of Energy has selected Oak Ridge National Laboratory to lead a collaboration charged with developing quantum technologies that will usher in a new era of innovation.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have a powerful new tool in the quest to produce better plants for biofuels, bioproducts and agriculture.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.