ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
A modeling analysis led by ORNL gives the first detailed look at how geothermal energy can relieve the electric power system and reduce carbon emissions if widely implemented across the United States within the next few decades.
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.
ORNL researchers have developed a novel way to encapsulate salt hydrate phase-change materials within polymer fibers through a coaxial pulling process. The discovery could lead to the widespread use of the low-carbon materials as a source of insulation for a building’s envelope.
ORNL and the University of Tennessee, Knoxville, co-hosted the 2023 National Society of Black Physicists Annual Conference with the theme "Frontiers in Physics: From Quantum to Materials to the Cosmos.” As part of the three-day conference held near UT, attendees took a 30-mile trip to the ORNL campus for facility tours, science talks and workshops.
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.
ORNL will lead a new DOE-funded project designed to accelerate bringing fusion energy to the grid. The Accelerate award focuses on developing a fusion power plant design concept that supports remote maintenance and repair methods for the plasma-facing components in fusion power plants.
Two fusion energy leaders have joined ORNL in the Fusion and Fission Energy and Science Directorate, or FFESD.
ORNL is leading three research collaborations with fusion industry partners through the Innovation Network for FUSion Energy, or INFUSE, program that will focus on resolving technical challenges and developing innovative solutions to make practical fusion energy a reality.
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.