Simultaneous quantification of uranium(vi), samarium, nitric acid, and temperature with combined ensemble learning, laser fluorescence, and Raman scattering for real-time monitoring. Issue 18 (12th August 2022) - Sadergaski, Luke R.; Andrews, Hunter B.
Abstract : Laser-induced fluorescence spectroscopy, Raman spectroscopy, and a stacked regression was developed for rapid quantification of uranium(vi ) (1–100 μg mL −1 ), samarium (0–200 μg mL −1 ) and nitric acid (0.1–4 M) with varying temperature (20 °C–45 °C). Abstract : Laser-induced fluorescence spectroscopy (LIFS), Raman spectroscopy, and a stacked regression ensemble was developed for near real-time quantification of uranium(vi ) (1–100 μg mL −1 ), samarium (0–200 μg mL −1 ) and nitric acid (0.1–4 M) with varying temperature (20 °C–45 °C). LIFS applications range from fundamental lab-scale studies to real-time process monitoring at industrial levels, such as nuclear reprocessing applications, provided the phenomena affecting the fluorescence spectrum are accounted for ( e.g., absorption, quenching, complexation). Multiple chemometric models were examined and compared to a more traditional multivariate regression approach called partial least squares (PLS). Results obtained on synthetic samples selected using D-optimal experimental design indicated that a stacked regression method, which included ridge regression, random forest, PLS, and an eXtreme gradient boost algorithm, successfully measured uranium(vi ) concentrations directly in nitric acid without measuring luminescence lifetimes or standard addition. The top model resulted in percent root-mean-square error of prediction values of 5.2, 1.9, 3.0, and 2.3% for U(vi ), Sm 3+, HNO3, and temperature, respectively. The approach may be useful for quantifying fluorescent fission products ( e.g., Sm 3+ ) to provide information on burnup of irradiated nuclear fuel. This novel framework reinforces the applicability of LIFS for real-time applications in nuclear fuel cycle applications.