Astrophysicists at the State University of New York, Stony Brook and University of California, Berkeley, used the Oak Ridge Leadership Computing Facility’s Summit supercomputer to compare models of X-ray bursts in 2D and 3D.
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.
An experiment by researchers at the Department of Energy’s Oak Ridge National Laboratory demonstrated advanced quantum-based cybersecurity can be realized in a deployed fiber link.
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.
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.
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.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
Louise Stevenson uses her expertise as an environmental toxicologist to evaluate the effects of stressors such as chemicals and other contaminants on aquatic systems.
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.