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Media Contacts
Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
Craig Blue, Defense Manufacturing Program Director at the Department of Energy’s Oak Ridge National Laboratory, was recently elected to a two-year term on the Institute for Advanced Composites Manufacturing Innovation Consortium Council, a body of professionals from academia, state governments, and national laboratories that provides strategic direction and oversight to IACMI.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory designed a molecule that disrupts the infection mechanism of the SARS-CoV-2 coronavirus and could be used to develop new treatments for COVID-19 and other viral diseases.
A quest to understand how Sphagnum mosses facilitate the storage of vast amounts of carbon in peatlands led scientists to a surprising discovery: the plants have sex-based differences that appear to impact the carbon-storing process.
As part of a multi-institutional research project, scientists at ORNL leveraged their computational systems biology expertise and the largest, most diverse set of health data to date to explore the genetic basis of varicose veins.
Merlin Theodore is one of eight new board members announced by President Biden; she will join the 25-member board for a six-year term.
Paul Langan will join ORNL in the spring as associate laboratory director for the Biological and Environmental Systems Science Directorate.
Eight ORNL scientists are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.