Researchers have demonstrated a way to determine the type of reactor that a sample of spent fuel comes from. Based on isotopic and elemental measurements of a sample, the researchers used pattern recognition and machine learning techniques to consider all material parameters (including impurities and isotopes) simultaneously.
"Currently the field of nuclear forensics focuses on the analysis of key material properties to determine details about the materials processing history, for example, utilizing known half-lives of isotopes can determine when the material was last processed," say authors Andrew Jones, Phillip Turner, Colin Zimmerman and John Goulermas. They extend previous work on spent fuel to reliably ascertain the type of reactor the spent fuel originated from with classification algorithms. "A number of these classification techniques are novel applications in nuclear forensics and expand on the existing knowledge in this field by creating a reliable and robust classification model."
The article, "Classification of spent reactor fuel for nuclear forensics" was published in Analytical Chemistry 86 (11) pp. 5399-5405