Building innovations from ORNL will be on display in Washington, D.C. on the National Mall June 7 to June 9, 2024, during the U.S. Department of Housing and Urban Development’s Innovation Housing Showcase. For the first time, ORNL’s real-time building evaluator was demonstrated outside of a laboratory setting and deployed for building construction.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed lubricant additives that protect both water turbine equipment and the surrounding environment.
The U.S. Environmental Protection Agency has approved the registration and use of a renewable gasoline blendstock developed by Vertimass LLC and ORNL that can significantly reduce the emissions profile of vehicles when added to conventional fuels.
Simulations performed on the Summit supercomputer at ORNL are cutting through that time and expense by helping researchers digitally customize the ideal alloy.
Rigoberto “Gobet” Advincula, a scientist with joint appointments at ORNL and the University of Tennessee, has been named a Fellow of the American Institute for Medical and Biological Engineering.
ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs.
An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.