Millions of miles of pipelines and conduits across the United States make up an intricate network of waterways used for municipal, agricultural and industrial purposes.
Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
ORNL has provided hydropower operators with new data to better prepare for extreme weather events and shifts in seasonal energy demands caused by climate change.
A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.
Chemical and environmental engineer Samarthya Bhagia is focused on achieving carbon neutrality and a circular economy by designing new plant-based materials for a range of applications from energy storage devices and sensors to environmentally friendly bioplastics.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
The rapid pace of global climate change has added urgency to developing technologies that reduce the carbon footprint of transportation technologies, especially in sectors that are difficult to electrify.
A team of researchers working within the Center for Bioenergy Innovation at ORNL has discovered a pathway to encourage a type of lignin formation in plants that could make the processing of crops grown for products such as sustainable jet fuels easier and less costly.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.