DOE OSTI · 1496738
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
Vesselinov, Velimir Valentinov. 2019-02-22. Unsupervised Machine Learning Methods for Feature Extraction. https://www.osti.gov/biblio/1496738
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
We present Gd isotope compositions on 25 well-characterized uranium ore concentrates (UOCs). About half the UOCs have isotope depletions in 157 Gd coupled with anticorrelated excesses in 158 Gd due to neutron capture effects. UOCs from older ore bodies and with higher U contents show larger neutron capture effects than UOCs from younger ore bodies with lower U contents. These Gd data are correlated with their previously measured Sm isotope compositions, and we use the Sm data to estimate the neutron fluence of these samples. In conclusion, this work demonstrates how Gd isotope signatures can be employed as a new tool for nuclear forensics.
Explore the source record for details and available documents.
Explore the source record for details and available documents.