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Despite strong regulations and robust international safeguards, authorities routinely interdict nuclear materials outside of regulatory control. Researchers at ORNL are exploring a new method that would give authorities the ability to analyze intercepted nuclear material and determine where it originated. 

Colorful circles with symbols of Vc, Vh and Vt inside. Blue, Orange and Pink

Researchers used quantum simulations to obtain new insights into the nature of neutrinos — the mysterious subatomic particles that abound throughout the universe — and their role in the deaths of massive stars.

Woman is standing at podium holding a gavel in the air.

In May, the Department of Energy’s Oak Ridge and Brookhaven national laboratories co-hosted the 15th annual International Particle Accelerator Conference, or IPAC, at the Music City Center in Nashville, Tennessee. 

Caption: Participants gather for a group photo after discussing securing AI systems for critical national security data and applications.  Photo by Liz Neunsinger/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data. 

Frontier supercomputer sets new standard in molecular simulation

When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.

Mohamad Zineddin

Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear security culture and resilience strategies and techniques.

Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.

Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection

To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.

Credit: Tyler Spano/ORNL, U.S. Dept. of Energy

Nuclear nonproliferation scientists at ORNL have published the Compendium of Uranium Raman and Infrared Experimental Spectra, a public database and analysis of structure-spectral relationships for uranium minerals. This first-of-its-kind dataset and corresponding analysis fill a key gap in the existing body of knowledge for mineralogists and actinide scientists. 

A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science

ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.