Leveraging visible and near-infrared spectroelectrochemistry to calibrate a robust model for Vanadium(IV/V) in varying nitric acid and temperature levels

Andrews, Hunter; Sadergaski, Luke R.

doi:10.1016/j.talanta.2023.124554

Cited by 10 publications

(15 citation statements)

References 35 publications

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“…NIR absorption water bands with negative absorbance values were observed at 960 and 1200 nm. These regions are sensitive to various ionic species (e.g., H + and NO 3 – ) and temperature. , …”

Section: Resultsmentioning

confidence: 99%

“…Prediction performance is strong when RMSEP % < 5%, satisfactory when RMSEP % ≤ 5−10%, and indicative when RMSEP % ≤ 10−15%. 9 Fission Product Ingrowth Modeling in Nuclear Fuel. The models were applied to evaluate a persistent challenge of FP ingrowth in nuclear fuel simulated for different reactors and fuel enrichments.…”

Section: ■ Methodsmentioning

confidence: 99%

“…PLSR models were optimized by minimizing the RMSEP. Prediction performance is strong when RMSEP % < 5%, satisfactory when RMSEP % ≤ 5–10%, and indicative when RMSEP % ≤ 10–15% …”

Section: Methodsmentioning

confidence: 99%

“…5−7 Design of experiments can be used to reduce the training set size while maintaining or improving prediction performance, but examples are often limited to only two or three variables. 8,9 The designed approach must be extended to include numerous factors and test the limits of describing realworld systems.…”

Section: ■ Introductionmentioning

confidence: 99%

“…This is reasonable in many nonradiological environments, where such techniques were originally implemented . Developing efficient methods to train chemometric models with as few samples as possible is imperative for processing in harsh/restrictive environments where radioactive materials can be in short supply. − Design of experiments can be used to reduce the training set size while maintaining or improving prediction performance, but examples are often limited to only two or three variables. , The designed approach must be extended to include numerous factors and test the limits of describing real-world systems.…”

Section: Introductionmentioning

confidence: 99%

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Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Sadergaski,

Andrews,

Wilson

2024

Anal. Chem.

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Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL–1), europium (0–150 μg mL–1), samarium (0–250 μg mL–1), praseodymium (0–350 μg mL–1), neodymium (0–1000 μg mL–1), and HNO3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. The optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

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Section: Resultsmentioning

confidence: 99%

Section: ■ Methodsmentioning

confidence: 99%

“…PLSR models were optimized by minimizing the RMSEP. Prediction performance is strong when RMSEP % < 5%, satisfactory when RMSEP % ≤ 5–10%, and indicative when RMSEP % ≤ 10–15% …”

Section: Methodsmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%