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Media Contacts
In the Physics Division of the Department of Energy’s Oak Ridge National Laboratory, James (“Mitch”) Allmond conducts experiments and uses theoretical models to advance our understanding of the structure of atomic nuclei, which are made of various combinations of protons and neutrons (nucleons).
Scientists at Oak Ridge National Laboratory used a focused beam of electrons to stitch platinum-silicon molecules into graphene, marking the first deliberate insertion of artificial molecules into a graphene host matrix.
Energy storage startup SPARKZ Inc. has exclusively licensed five battery technologies from the Department of Energy’s Oak Ridge National Laboratory designed to eliminate cobalt metal in lithium-ion batteries. The advancement is aimed at accelerating the production of electric vehicles and energy storage solutions for the power grid.
Liam Collins was drawn to study physics to understand “hidden things” and honed his expertise in microscopy so that he could bring them to light.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
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.
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
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.
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.