The BIO-SANS instrument, located at Oak Ridge National Laboratory’s High Flux Isotope Reactor, is the latest neutron scattering instrument to be retrofitted with state-of-the-art robotics and custom software. The sophisticated upgrade quadruples the number of samples the instrument can measure automatically and significantly reduces the need for human assistance.
Plans to unite the capabilities of two cutting-edge technological facilities funded by the Department of Energy’s Office of Science promise to usher in a new era of dynamic structural biology. Through DOE’s Integrated Research Infrastructure, or IRI, initiative, the facilities will complement each other’s technologies in the pursuit of science despite being nearly 2,500 miles apart.
ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S.
Rigoberto “Gobet” Advincula, a scientist with joint appointments at ORNL and the University of Tennessee, has been named a Fellow of the American Institute for Medical and Biological Engineering.
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.
Chelsea Chen, a polymer physicist at ORNL, is studying ion transport in solid electrolytes that could help electric vehicle battery charges last longer.
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.
“Three-Dimensional Breast Cancer Spheroids” submitted by radiotherapeutics researcher Debjani Pal is stunning. Brilliant blue dots pop from an electric sphere threaded with bright colors: greens, aqua, hot pink and red.
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.