Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics
Controlled-potential in situ thin-layer spectropotentiometry was leveraged to generate visible/near-infrared (VIS/NIR) absorption spectral data sets for the development of chemometric models to quantify Np(III/IV/V/VI) oxidation states in HNO3. This technology would be valuable in laboratory studies...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Nuclear Engineering |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnuen.2023.1323372/full |
| _version_ | 1827164641289043968 |
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| author | Luke R. Sadergaski Hunter B. Andrews Sara E. Gilson Adam J. Parkison |
| author_facet | Luke R. Sadergaski Hunter B. Andrews Sara E. Gilson Adam J. Parkison |
| author_sort | Luke R. Sadergaski |
| collection | DOAJ |
| description | Controlled-potential in situ thin-layer spectropotentiometry was leveraged to generate visible/near-infrared (VIS/NIR) absorption spectral data sets for the development of chemometric models to quantify Np(III/IV/V/VI) oxidation states in HNO3. This technology would be valuable in laboratory studies and when monitoring process solutions to guide feed adjustments for radiochemical separations—the performance of which depends on oxidation state. This approach successfully isolated and stabilized Np species in pure (∼99%) oxidation states without compromising solution optical properties. Multivariate curve resolution–alternating least squares models were evaluated to resolve spectral and component concentrations from a scan that sequentially produced Np(VI), Np(V), Np(IV), and Np(III) spectra with mixtures of two valences at a time. Although it provided a useful approximation, the method was not able to quantitively resolve each component likely because of rotational ambiguity. Additionally, partial least squares regression models were built from artificial and electrochemically generated VIS/NIR spectral training sets to study the effect of interionic interactions on spectral characteristics. Models built with true Bi-chemical mixtures of coexisting Np oxidation states and spectra generated from additive combinations of pure end points had similar prediction performance. This methodology can be used to directly quantify Np concentration and the ratio of Np oxidation states and other actinides in remote settings such as hot cells. |
| first_indexed | 2024-03-09T00:02:06Z |
| format | Article |
| id | doaj.art-7db1dbc2b48545bba08265a3a65abc85 |
| institution | Directory Open Access Journal |
| issn | 2813-3412 |
| language | English |
| last_indexed | 2025-03-21T01:19:50Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nuclear Engineering |
| spelling | doaj.art-7db1dbc2b48545bba08265a3a65abc852024-08-03T02:23:11ZengFrontiers Media S.A.Frontiers in Nuclear Engineering2813-34122023-12-01210.3389/fnuen.2023.13233721323372Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometricsLuke R. SadergaskiHunter B. AndrewsSara E. GilsonAdam J. ParkisonControlled-potential in situ thin-layer spectropotentiometry was leveraged to generate visible/near-infrared (VIS/NIR) absorption spectral data sets for the development of chemometric models to quantify Np(III/IV/V/VI) oxidation states in HNO3. This technology would be valuable in laboratory studies and when monitoring process solutions to guide feed adjustments for radiochemical separations—the performance of which depends on oxidation state. This approach successfully isolated and stabilized Np species in pure (∼99%) oxidation states without compromising solution optical properties. Multivariate curve resolution–alternating least squares models were evaluated to resolve spectral and component concentrations from a scan that sequentially produced Np(VI), Np(V), Np(IV), and Np(III) spectra with mixtures of two valences at a time. Although it provided a useful approximation, the method was not able to quantitively resolve each component likely because of rotational ambiguity. Additionally, partial least squares regression models were built from artificial and electrochemically generated VIS/NIR spectral training sets to study the effect of interionic interactions on spectral characteristics. Models built with true Bi-chemical mixtures of coexisting Np oxidation states and spectra generated from additive combinations of pure end points had similar prediction performance. This methodology can be used to directly quantify Np concentration and the ratio of Np oxidation states and other actinides in remote settings such as hot cells.https://www.frontiersin.org/articles/10.3389/fnuen.2023.1323372/fullactinideoptical spectroscopymachine learningonline monitoringmultivariate analysis |
| spellingShingle | Luke R. Sadergaski Hunter B. Andrews Sara E. Gilson Adam J. Parkison Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics Frontiers in Nuclear Engineering actinide optical spectroscopy machine learning online monitoring multivariate analysis |
| title | Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| title_full | Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| title_fullStr | Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| title_full_unstemmed | Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| title_short | Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| title_sort | quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics |
| topic | actinide optical spectroscopy machine learning online monitoring multivariate analysis |
| url | https://www.frontiersin.org/articles/10.3389/fnuen.2023.1323372/full |
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