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Media Contacts
Led by Kelly Chipps of ORNL, scientists working in the lab have produced a signature nuclear reaction that occurs on the surface of a neutron star gobbling mass from a companion star. Their achievement improves understanding of stellar processes generating diverse nuclear isotopes.
With the world’s first exascale supercomputing system now open to full user operations, research teams are harnessing Frontier’s power and speed to tackle some of the most challenging problems in modern science.
Kelly Chipps, a nuclear astrophysicist at ORNL, has been appointed to the Nuclear Science Advisory Committee, or NSAC. The committee provides official advice to DOE and the National Science Foundation, or NSF, about issues relating to the national program for basic nuclear science research.
Anne Campbell, an R&D associate at ORNL, has been selected for an Emerging Professional award from ASTM International. ASTM, formerly the American Society for Testing and Materials, is an international standards organization that develops and publishes voluntary consensus technical standards for a wide range of materials, products, systems and services.
Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences in recognition of his distinguished and continuing achievements in original research.
A method using augmented reality to create accurate visual representations of ionizing radiation, developed at ORNL, has been licensed by Teletrix, a firm that creates advanced simulation tools to train the nation’s radiation control workforce.
Valentino “Tino” Cooper, a scientist at ORNL, has been appointed to DOE’s Basic Energy Sciences Advisory Committee for a three-year term. Cooper’s research elucidates the fundamental understanding of advanced materials for next-generation energy and information technologies.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Marm Dixit, a Weinberg Distinguished Staff Fellow at ORNL has received the 2023 Rosalind Franklin Young Investigator Award.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.