ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
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.
Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.
Quanex Building Products has signed a non-exclusive agreement to license a method to produce insulating material from ORNL. The low-cost material can be used as an additive to increase thermal insulation performance and improve energy efficiency when applied to a variety of building products.
Scientists at the US Department of Energy’s Oak Ridge National Laboratory have demonstrated a method to insert genes into a variety of microorganisms that previously would not accept foreign DNA, with the goal of creating custom microbes to break down plants for bioenergy.
Researchers at Oak Ridge National Laboratory proved that a certain class of ionic liquids, when mixed with commercially available oils, can make gears run more efficiently with less noise and better durability.
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source to probe the structure of a colorful new material that may pave the way for improved sensors and vivid displays.
A team including Oak Ridge National Laboratory and University of Tennessee researchers demonstrated a novel 3D printing approach called Z-pinning that can increase the material’s strength and toughness by more than three and a half times compared to conventional additive manufacturing processes.
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.