Three staff members in ORNL’s Fusion and Fission Energy and Science Directorate have moved into newly established roles facilitating communication and program management with sponsors of the directorate’s Nuclear Energy and Fuel Cycle Division.
In a win for chemistry, inventors at ORNL have designed a closed-loop path for synthesizing an exceptionally tough carbon-fiber-reinforced polymer, or CFRP, and later recovering all of its starting materials.
Scientists at ORNL are looking for a happy medium to enable the grid of the future, filling a gap between high and low voltages for power electronics technology that underpins the modern U.S. electric grid.
Four ORNL teams and one researcher were recognized for excellence in technology transfer and technology transfer innovation.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
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.
The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.
Scientists at ORNL have developed a technique for recovering and recycling critical materials that has garnered special recognition from a peer-reviewed materials journal and received a new phase of funding for research and development.
Nuclear engineering students from the United States Military Academy and United States Naval Academy are working with researchers at ORNL to complete design concepts for a nuclear propulsion rocket to go to space in 2027 as part of the Defense Advanced Research Projects Agency DRACO program.
Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii – and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.