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Media Contacts
Phani Ratna Vanamali Marthi, an R&D associate in the Power Systems Resilience group at ORNL, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers, the world’s largest technical professional organization
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.
Researchers at ORNL are developing battery technologies to fight climate change in two ways, by expanding the use of renewable energy and capturing airborne carbon dioxide.
Howard Wilson explores how to accelerate the delivery of fusion energy as Fusion Pilot Plant R&D lead at ORNL. Wilson envisions a fusion hub with ORNL at the center, bringing together the lab's unique expertise and capabilities with domestic and international partnerships to realize the potential of fusion energy.
Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air.
Chuck Greenfield, former assistant director of the DIII-D National Fusion Program at General Atomics, has joined ORNL as ITER R&D Lead.
Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition.
Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.