Quantum precision reached in modeling molten salt behavior
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.”
A team of scientists led by a professor from Duke University discovered a way to help make batteries safer, charge faster and last longer. They relied on neutrons at ORNL to understand at the atomic scale how lithium moves in lithium phosphorus sulfur chloride, a promising new type of solid-state battery material known as a superionic compound.
P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.
Joel Brogan, who leads the Multimodal Sensor Analytics group at Oak Ridge National Laboratory, has been elevated to senior membership in the Institute of Electrical and Electronics Engineers.
Seven scientists affiliated with ORNL have been named Battelle Distinguished Inventors in recognition of being granted 14 or more United States patents. Since Battelle began managing ORNL in 2000, 104 ORNL researchers have reached this milestone.
ORNL has been recognized in the 21st edition of the HPCwire Readers’ and Editors’ Choice Awards, presented at the 2024 International Conference for High Performance Computing, Networking, Storage and Analysis in Atlanta, Georgia.
Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.
Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.
A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.
A multi-institutional team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, has been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize for Climate Modelling.