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Argonne research aims to improve nuclear fuel recycling and metal recovery
Servis
Scientists at Argonne National Laboratory are investigating a used nuclear fuel recycling technology that could lead to a scaled-down and more efficient approach to metal recovery, according to a recent news article from the lab. The research, led by Argonne radiochemist Anna Servis with funding from the Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E), could have an impact beyond the nuclear fuel cycle and improve other high-value metal processing, such as rare earth recovery, according to Argonne.
The research: Servis’s work is being carried out under ARPA-E’s CURIE (Converting UNF Radioisotopes Into Energy) program. The specific project—Radioisotope Capture Intensification Using Rotating Packed Bed Contactors—started in 2023 and is scheduled to end in January 2026.
Victoria Hypes-Mayfield, William Kubic, David Dogruel, Kirk Hollis, Scott Willms, Joseph H. Dumont
Fusion Science and Technology | Volume 77 | Number 7 | November 2021 | Pages 836-841
Technical Paper | doi.org/10.1080/15361055.2021.1883978
Articles are hosted by Taylor and Francis Online.
Uranium hydride is commonly used to store hydrogen or its isotopes in a solid state. The Self-Assaying Tritium Accountancy and Containment Unit for ITER (STACI) is a 5.2-kg bed of depleted uranium (dU) capable of holding up to 33 mol of hydrogen or its isotopes. This paper is a summary of data analysis of past experimental campaigns with STACI, with the aim of describing the kinetics and thermodynamics of the hydriding process. Computed tomography imaging was performed on STACI both before and after its experimental campaign, and a high degree of swelling was observed in the dU. Literature on studies in regard to the swelling of large (multikilogram) quantities of uranium hydride for storage applications was not identified during this study. Data from the experimental campaign, as well as data on the formation reaction, are presented. The authors hope to create an analytical model of STACI based on these data.