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Media Contacts
Early career scientist Frankie White's was part of two major isotope projects at the same time he was preparing to be a father. As co-lead on a team that achieved the first synthesis and characterization of a radium compound using single crystal X-ray diffraction and part of a team that characterized the properties of promethium, White reflects on the life-changing timeline at work, and at home.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
Students from the first class of ORNL and Pellissippi State Community College's joint Chemical Radiation Technology Pathway toured isotope facilities at ORNL.
Researchers tackling national security challenges at ORNL are upholding an 80-year legacy of leadership in all things nuclear. Today, they’re developing the next generation of technologies that will help reduce global nuclear risk and enable safe, secure, peaceful use of nuclear materials, worldwide.
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 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.
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.