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Combining fundamental chemistry with high-performance computing resources at ORNL, researchers demonstrate a more efficient method for recovering uranium from seawater, unveiling a prototype material that outperforms best-in-class uranium adsorbents. Credit: Alexander Ivanov/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Scientists have demonstrated a new bio-inspired material for an eco-friendly and cost-effective approach to recovering uranium from seawater.

ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.

ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL

Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.

ORNL cybersecurity researchers Jared Smith (left) and Elliot Greenlee (right) participate in a demonstration day event to showcase how Akatosh, a new security analysis tool, quickly sorts through data to identify potential threats.

As technology continues to evolve, cybersecurity threats do as well. To better safeguard digital information, a team of researchers at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) has developed Akatosh, a security analysis tool that works in conjunctio...

Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL.

As leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory, Kerekes heads an accelerated lab-directed research program to build virtual models of critical infrastructure systems like the power grid that can be used to develop ways to detect and repel cyber-intrusion and to make the network resilient when disruption occurs.

The electromagnetic isotope separator system operates by vaporizing an element such as ruthenium into the gas phase, converting the molecules into an ion beam, and then channeling the beam through magnets to separate out the different isotopes.

A tiny vial of gray powder produced at the Department of Energy’s Oak Ridge National Laboratory is the backbone of a new experiment to study the intense magnetic fields created in nuclear collisions.

ORNL Director Thomas Zacharia (center, seated) visited Robertsville Middle School to present a check in support of the school’s CubeSat efforts.

Last November a team of students and educators from Robertsville Middle School in Oak Ridge and scientists from Oak Ridge National Laboratory submitted a proposal to NASA for their Cube Satellite Launch Initiative in hopes of sending a student-designed nanosatellite named RamSat into...

Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.
Oak Ridge National Laboratory provided significant contributions and coordination in the development of the Nuclear Energy Agency’s (NEA’s) recently released Spent Fuel Isotopic Composition (SFCOMPO) 2.0—the world’s largest open database for spent
Arjun Shankar

The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...

Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy.

A team of researchers from Oak Ridge National Laboratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scient...