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Media Contacts
ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline — exposing more of the material to light for increased photo-activation and better photochemistry data capture.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
A team of researchers including a member of the Quantum Science Center at ORNL has published a review paper on the state of the field of Majorana research. The paper primarily describes four major platforms that are capable of hosting these particles, as well as the progress made over the past decade in this area.
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
ORNL researchers have produced the most comprehensive power outage dataset ever compiled for the United States. This dataset, showing electricity outages from 2014-22 in the 50 U.S. states, Washington D.C. and Puerto Rico, details outages at 15-minute intervals for up to 92% of customers for the eight-year period.
Joseph Chapman, a research scientist in quantum communications at ORNL, was given the Physical Review Applied Reviewer Excellence 2024 award for his work as a peer reviewer for the journal Physical Review Applied.
ORNL researchers have teamed up with other national labs to develop a free platform called Open Energy Data Initiative Solar Systems Integration Data and Modeling to better analyze the behavior of electric grids incorporating many solar projects.
ORNL scientists are working on a project to engineer and develop a cryogenic ion trap apparatus to simulate quantum spin liquids, a key research area in materials science and neutron scattering studies.
Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear security culture and resilience strategies and techniques.
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.