Scientists at ORNL have developed 3-D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
ORNL scientists have determined how to avoid costly and potentially irreparable damage to large metallic parts fabricated through additive manufacturing, also known as 3D printing, that is caused by residual stress in the material.
SkyNano, an Innovation Crossroads alumnus, held a ribbon-cutting for their new facility. SkyNano exemplifies using DOE resources to build a successful clean energy company, making valuable carbon nanotubes from waste CO2.
While government regulations are slowly coming, a group of cybersecurity professionals are sharing best practices to protect large language models powering these tools. Sean Oesch, a leader in emerging cyber technologies, recently contributed to the OWASP AI Security and Privacy Guide to inform global AI security standards and regulations.
In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
Marcel Demarteau is director of the Physics Division at the Department of Energy’s Oak Ridge National Laboratory. For topics from nuclear structure to astrophysics, he shapes ORNL’s physics research agenda.
As ORNL’s fuel properties technical lead for the U.S. Department of Energy’s Co-Optimization of Fuel and Engines, or Co-Optima, initiative, Jim Szybist has been on a quest for the past few years to identify the most significant indicators for predicting how a fuel will perform in engines designed for light-duty vehicles such as passenger cars and pickup trucks.