Quantum precision reached in modeling molten salt behavior
Training nuclear safety experts to measure the unseen: ORNL’s course enhances nuclear accountability
Professionals from government and industry gathered at ORNL for the Nondestructive Assay Holdup Measurements Training Course for Nuclear Criticality Safety, a hands-on training in nondestructive assay, a technique for detecting and quantifying holdup without disturbing operations.
ORNL took part in the “1,000 Scientists AI Jam Session,” a first-of-its-kind virtual event that brought together leading scientists from nine national laboratories to test generative artificial intelligence models for their functionality in scientific research.
During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”
Using the Frontier supercomputer at ORNL, researchers have developed a new technique that predicts nuclear properties in record detail. The study revealed how the structure of a nucleus relates to the force that holds it together. This understanding could advance efforts in quantum physics and across a variety of sectors, from to energy production to national security.
A workshop led by scientists at ORNL sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories.
Not only did ORNL take home top honors at the 2024 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24), but the lab’s computing staff also shared career advice and expertise with students eager to enter the world of supercomputing.
Scientists at ORNL are using advanced germanium detectors to explore fundamental questions in nuclear physics, such as the nature of neutrinos and the matter-antimatter imbalance. The ongoing LEGEND project, an international collaboration, aims to discover neutrinoless double beta decay, which could significantly advance the understanding of the universe.
In a major milestone for cancer research, the Department of Energy’s Oak Ridge National Laboratory helped reduce the time between cancer diagnosis and pathology report processing from 22 months to just 14 months, utilizing advanced artificial
Massimiliano (Max) Lupo Pasini, an R&D data scientist from ORNL, was awarded the National Energy Research Scientific Computing Center’s High Performance Computing Achievement Award for High Impact Scientific Achievement for his work in “Groundbreaking contributions to scientific machine learning, particularly through the development of HydraGNN.”
Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.