Vanderbilt University and ORNL announced a partnership to develop training, testing and evaluation methods that will accelerate the Department of Defense’s adoption of AI-based systems in operational environments.
ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline — exposing more of the material to light for increased photo-activation and better photochemistry data capture.
ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries.
ORNL researchers have produced the most comprehensive power outage dataset ever compiled for the United States. This dataset, showing electricity outages from 2014-22 in the 50 U.S. states, Washington D.C. and Puerto Rico, details outages at 15-minute intervals for up to 92% of customers for the eight-year period.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed lubricant additives that protect both water turbine equipment and the surrounding environment.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.
Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
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%.