Spectrophotometers for plutonium monitoring in HB-line

Lascola, Robert; O'Rourke, Patrick; Kyser, Edward A.; Immel, David; Plummer, Jean; Evans, E. V.

doi:10.2172/1238600

Cited by 3 publications

(6 citation statements)

References 14 publications

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“…The spectral complexity and the peak variation highlighted in Figures and and in Table indicate traditional single variate analysis (Beer’s Law) represents a difficult path for quantifying Pu(IV) in solution. This has been recognized and initial developments in multivariate approaches to quantifying Pu have been published including systematic treatment of select wavelengths , and PLS regression techniques that break down acid strength regions to apply multiple hierarchical models . However, advances in mathematical approaches to data analysis have opened up new routes for quantifying species under complex conditions.…”

Section: Resultsmentioning

confidence: 99%

“…The mathematical operations/approaches vary with the type of modeling utilized, where different models have different output goals (i.e., classification, speciation, quantification, etc. ). ,,− …”

Section: Resultsmentioning

confidence: 99%

“…These models can then be used to accurately identify and quantify Pu(IV) in new or unknown samples. Recent studies have opened the door for this type of mathematical approach, 10 and here, we explore new approaches while connecting solution chemistry to the explanation of model outputs.…”

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confidence: 99%

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Multivariate Analysis for Quantification of Plutonium(IV) in Nitric Acid Based on Absorption Spectra

et al. 2017

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Development of more effective, reliable, and fast methods for monitoring process streams is a growing opportunity for analytical applications. Many fields can benefit from online monitoring, including the nuclear fuel cycle where improved methods for monitoring radioactive materials will facilitate maintenance of proper safeguards and ensure safe and efficient processing of materials. Online process monitoring with a focus on optical spectroscopy can provide a fast, nondestructive method for monitoring chemical species. However, identification and quantification of species can be hindered by the complexity of the solutions if bands overlap or show condition-dependent spectral features. Plutonium(IV) is one example of a species which displays significant spectral variation with changing nitric acid concentration. Single variate analysis (i.e., Beer's Law) is difficult to apply to the quantification of Pu(IV) unless the nitric acid concentration is known and separate calibration curves have been made for all possible acid strengths. Multivariate or chemometric analysis is an approach that allows for the accurate quantification of Pu(IV) without a priori knowledge of nitric acid concentration.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Multivariate Analysis for Quantification of Plutonium(IV) in Nitric Acid Based on Absorption Spectra

et al. 2017

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Section: ■ Introductionmentioning

confidence: 99%

“…Vibrational spectroscopy, especially Raman, has commonly been used to monitor process conditions in real time as these spectroscopic approaches can quickly measure multiple analytes simultaneously. , Raman spectroscopy has been successfully coupled with chemometric model development to enable analysis of the Hanford tanks. , A significant gap in the literature has been a thorough discussion of how the choice of the modeling algorithm can impact the ability of real-time analysis systems to handle interfering spectral bands. Understanding these impacts is essential for the informed and effective design of monitoring tools for Hanford remediation because many of the 1800 chemical species present in the Hanford tanks are poly-oxo anions, presenting signal overlap with each other…”

Section: Introductionmentioning

confidence: 99%

Quantification of Raman-Interfering Polyoxoanions for Process Analysis: Comparison of Different Chemometric Models and a Demonstration on Real Hanford Waste

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Shafer

Bryan

et al. 2021

Environ. Sci. Technol.

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The Hanford site represents a complicated environmental remediation challenge, remaining from the production of nuclear weapons. Over 100 million gallons of liquid radioactive waste of unknown composition will be chemically processed and vitrified, but the varying chemical composition and highly radioactive nature of the waste preclude the implementation of more developed, offline technologies to determine the composition. The only practical approach to waste treatment will require the significant utilization of real-time, chemometric modeling approaches. Although chemometric approaches have been applied to the analysis of Hanford waste, the models developed were highly tank-specialized, and limited discussion was provided on how models fared with interfering signals. As the tank waste is largely composed of oxoanions, which tend to have interfering Raman spectra, the general question was posed as to what chemometric approach is best suited to accurately quantify analytes in the presence of interfering signals. This was carried out by examining the ability of classical least square (CLS), principal component regression (PCR), partial least square (PLS), and locally weighted regression (LWR) to quantify NO 3 − and CO 3 2− using their bands around 1050 cm −1 . For all samples, the PLS-based model was found to be the most efficient approach from a model building and application perspective.

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