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Media Contacts
ORNL researchers are working to make EV charging more resilient by developing algorithms to deal with both internal and external triggers of charger failure. This will help charging stations remain available to traveling EV drivers, reducing range anxiety.
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
Alyssa Carrell started her science career studying the tallest inhabitants in the forest, but today is focused on some of its smallest — the microbial organisms that play an outsized role in plant health.
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.
Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air.
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
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.
Chelsea Chen, a polymer physicist at ORNL, is studying ion transport in solid electrolytes that could help electric vehicle battery charges last longer.
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.