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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.

The transportation and industrial sectors together account for more than 50% of the country’s carbon footprint. Defossilization could help reduce new emissions from these and other difficult-to-electrify segments of the U.S. economy.

Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions. 

Chengyun Hua

The Quantum Voices series is designed to share the stories of the quantum researchers and technical experts behind the Quantum Science Center’s past, present and future accomplishments. Chengyun Hua is highlighted for this edition, talking about her role in the Quantum Science Center. 

Architects of the Adaptable IO System, seen here with Frontier's Orion file system: Scott Klasky, left, heads the ADIOS project and leads ORNL's Workflow Systems group, and Norbert Podhorszki, an ORNL computer scientist, oversees ADIOS's continuing development. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Integral to the functionality of ORNL's Frontier supercomputer is its ability to store the vast amounts of data it produces onto its file system, Orion. But even more important to the computational scientists running simulations on Frontier is their capability to quickly write and read to Orion along with effectively analyzing all that data. And that’s where ADIOS comes in.

Researchers relied on support from ORNL’s Quantum Computing User Program to simulate a key quantum state at one of the largest scales reported. The findings could mark a step toward improving quantum simulations.  Credit: Getty Images

Researchers simulated a key quantum state at one of the largest scales reported, with support from the Quantum Computing User Program, or QCUP, at ORNL. 

ORNL quantum researchers, from left, Brian Williams, Phil Evans, and Nick Peters work on their quantum key distribution system.

ORNL scientists have spent the past 20 years studying quantum photonic entanglement. Their partnership with colleagues at Los Alamos National Laboratory and private industry partner Qubitekk led to development of the nation’s first industry-led commercial quantum network. This type of network could ultimately help secure the nation’s power grid and other infrastructure from cyberattacks.

ORNL postdoctoral research associate Alex Miloshevsky presents his novel research in quantum networks at the 2024 OFC conference.

ORNL was front and center recently at one of the world’s largest optical networking conferences, the 2024 Optic Fiber Communication Conference and Exhibition, or OFC. ORNL researchers had major roles at the OFC 2024, a three-day event held in San Diego, California from March 26-28 which featured thousands of the world’s leading optical communications and networking professionals. 

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.