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.
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.
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
ORNL, TVA and TNECD were recognized by the Federal Laboratory Consortium for their impactful partnership that resulted in a record $2.3 billion investment by Ultium Cells, a General Motors and LG Energy Solution joint venture, to build a battery cell manufacturing plant in Spring Hill, Tennessee.
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.