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Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
An international team of scientists, led by the University of Manchester, has developed a metal-organic framework, or MOF, material
Scientists at the U.S. Department of Energy’s Brookhaven National Laboratory have new experimental evidence and a predictive theory that solves a long-standing materials science mystery: why certain crystalline materials shrink when heated.
Two of the researchers who share the Nobel Prize in Chemistry announced Wednesday—John B. Goodenough of the University of Texas at Austin and M. Stanley Whittingham of Binghamton University in New York—have research ties to ORNL.
Researchers at Oak Ridge National Laboratory demonstrated that metal foam enhances the evaporation process in thermal conversion systems and enables the development of compact HVAC&R units.
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source and High Flux Isotope Reactor to better understand how certain cells in human tissue bond together.
Using the Titan supercomputer and the Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory, scientists have created the most accurate 3D model yet of an intrinsically disordered protein, revealing the ensemble of its atomic-level structures.
Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.