An international team of scientists, led by the University of Manchester, has developed a metal-organic framework, or MOF, material
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
Oak Ridge National Laboratory will give college students the chance to practice cybersecurity skills in a real-world setting as a host of the Department of Energy’s fifth collegiate CyberForce Competition on Nov. 16. The event brings together student teams from across the country to compete at 10 of DOE’s national laboratories.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
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.
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.