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.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
Timothy Gray of ORNL led a study that may have revealed an unexpected change in the shape of an atomic nucleus. The surprise finding could affect our understanding of what holds nuclei together, how protons and neutrons interact and how elements form.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
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.
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.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
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.
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.