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Oak Ridge National Laboratory researchers, in collaboration with Cincinnati Inc., demonstrated the potential for using multimaterials and recycled composites in large-scale applications by 3D printing a mold that replicated a single facet of a
A newly released dataset that tracks the movement of everything from food to gasoline across the United States by air, water, truck, rail and pipeline showed the value and tonnage of those goods rose significantly between 2012 and 2017.
Scientists at Oak Ridge National Laboratory successfully demonstrated a technique to heal dendrites that formed in a solid electrolyte, resolving an issue that can hamper the performance of high energy-density, solid-state batteries.
Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
Fuel economy can take a tumble when temperatures plummet, according to the Department of Energy’s 2021 Fuel Economy Guide. Compiled by researchers at Oak Ridge National Laboratory, the guide includes several tips to improve a vehicle’s fuel performance.
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.
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.