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Media Contacts
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’s Matthew Loyd will receive a Department of Energy Office of Science Early Career Research award.
Scientists using high-resolution aerial scans and computational modeling concluded that wildfires, storms and selective logging have become key drivers behind rainforest carbon emissions, outpacing clear-cutting practices.
A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.
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.
Researchers for the first time documented the specific chemistry dynamics and structure of high-temperature liquid uranium trichloride salt, a potential nuclear fuel source for next-generation reactors.
DOE commissioned a neutron imaging instrument, VENUS, at the Spallation Neutron Source in July. VENUS instrument scientists will use AI to deliver 3D models to researchers in half the time it typically takes.
John joined the MPEX project in 2019 and has served as project manager for several organizations within ORNL.
A research team led by the Department of Energy’s Oak Ridge National Laboratory demonstrated an effective and reliable new way to identify and quantify polyethylene glycols in various samples.
To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.