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.
Drawing from his experience during the pandemic, Domenick Leto recognizes the need for the United States to have inexpensive, reliable capabilities to combat any type of disruption to national security, including nationwide medical emergencies. Leto and colleagues received a patent for a simple, inexpensive way to sterilize masks, plastic, and medical equipment from the COVID-19 virus.
For years, Duane Starr led workshops at ORNL to help others from across the U.S. government understand uranium processing technologies. After his retirement, Starr donated a 5-foot-tall working model, built in his garage, that demonstrates vibration harmonics, consistent with operation of a super critical gas centrifuge rotor, a valuable resource to ongoing ORNL-led workshops.
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
On Nov. 1, about 250 employees at Oak Ridge National Laboratory gathered in person and online for Quantum on the Quad, an event designed to collect input for a quantum roadmap currently in development. This document will guide the laboratory's efforts in quantum science and technology, including strategies for expanding its expertise to all facets of the field.
Four researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
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.
Effective Dec. 4, Gina Tourassi will assume responsibilities as associate laboratory director for the Computing and Computational Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory.
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.