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Media Contacts
A new technology to continuously place individual atoms exactly where they are needed could lead to new materials for devices that address critical needs for the field of quantum computing and communication that cannot be produced by conventional means.
A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.
ORNL is the lead partner on five research collaborations with private fusion companies in the 2024 cohort of the Innovation Network for FUSion Energy, or INFUSE, program. These collaborative projects are intended to resolve technical hurdles and develop enabling technologies to accelerate fusion energy research in the private sector.
A study by more than a dozen scientists at the Department of Energy’s Oak Ridge National Laboratory examines potential strategies to integrate quantum computing with the world’s most powerful supercomputing systems in the pursuit of science.
John joined the MPEX project in 2019 and has served as project manager for several organizations within ORNL.
The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.
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%.