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Media Contacts
If air taxis become a viable mode of transportation, Oak Ridge National Laboratory researchers have estimated they could reduce fuel consumption significantly while alleviating traffic congestion.
As ORNL’s fuel properties technical lead for the U.S. Department of Energy’s Co-Optimization of Fuel and Engines, or Co-Optima, initiative, Jim Szybist has been on a quest for the past few years to identify the most significant indicators for predicting how a fuel will perform in engines designed for light-duty vehicles such as passenger cars and pickup trucks.
The University of Texas at San Antonio (UTSA) has formally launched the Cybersecurity Manufacturing Innovation Institute (CyManII), a $111 million public-private partnership.
The Transformational Challenge Reactor, or TCR, a microreactor built using 3D printing and other new advanced technologies, could be operational by 2024.
Radioactive isotopes power some of NASA’s best-known spacecraft. But predicting how radiation emitted from these isotopes might affect nearby materials is tricky
Oak Ridge National Laboratory researchers used additive manufacturing to build a first-of-its kind smart wall called EMPOWER.
A developing method to gauge the occurrence of a nuclear reactor anomaly has the potential to save millions of dollars.
As CASL ends and transitions to VERA Users Group, ORNL looks at the history of the program and its impact on the nuclear industry.
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.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.