Updated software improves slicing for large-format 3D printing
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
Researchers at ORNL used polymer chemistry to transform a common household plastic into a reusable adhesive with a rare combination of strength and ductility, making it one of the toughest materials ever reported.
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
ORNL’s Budhendra “Budhu” Bhaduri has been elected a fellow of the American Association of Geographers. The honor recognizes Bhaduri as “a world leader in innovation, development and application of research in human dynamics, geographic data science, remote sensing and scalable geocomputation.”
When Brian Fricke walks into a supermarket, evidence of his scientific achievement is all around in the refrigerated cases housing the fresh fruits and vegetables. As an Oak Ridge National Laboratory building equipment researcher, Fricke has a long history of making sure that produce is kept fresh in an energy efficient and environmentally sound manner.
Energy and sustainability experts from ORNL, industry, universities and the federal government recently identified key focus areas to meet the challenge of successfully decarbonizing the agriculture sector
A novel method to 3D print components for nuclear reactors, developed by the Department of Energy’s Oak Ridge National Laboratory, has been licensed by Ultra Safe Nuclear Corporation.
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.