Abstract
The Plutonium-238 Supply Program at Oak Ridge National Laboratory has developed the capability to inform process decisions during full-scale 238Pu anion exchange column runs using multivariate chemometrics and visible-near infrared (Vis-NIR) absorption spectroscopy. Multivariate analytical methods provided a suitable option for real-time analysis of complex neptunium (Np) and plutonium (Pu) absorption spectra. Thousands of spectra from multiple production campaigns were analyzed by principal component analysis and Kennard-Stone sample selection to select a training set composed of 60 spectra. Multivariate curve resolution–alternating least squares analysis (MCR-ALS) identified spectral components and component concentrations. A partial least squares regression (PLSR) model was built using the spectra and concentration values determined by these virtually unsupervised methods. Next, a supervised PLSR model was built by scaling the MCR-ALS–selected concentration matrix using molar epsilon values. Both PLSR models predicted the concentrations of Np(IV), Np(V), Pu(III), Pu(IV), and Pu(VI) in the column effluent and identified nearly identical product cut decisions. The time-dependent Np and Pu concentration profiles provided valuable insight into column dynamics and the predictions agreed with traditional methods including alpha spectrometry and inductively coupled plasma mass spectrometry. These results establish a resourceful avenue for modeling multicomponent systems with convoluted absorption bands without significant user input. It is particularly advantageous for production-oriented radiochemical applications in restrictive hot cell environments.
| Original language | English |
|---|---|
| Article number | 100120 |
| Journal | Talanta Open |
| Volume | 5 |
| DOIs | |
| State | Published - Aug 2022 |
Funding
Funding for this program was provided by NASA's Science Mission Directorate and administered by the DOE Office of Nuclear Energy, under contract DEAC05-00OR22725. This work used resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by ORNL. The authors wish to thank Hunter B. Andrews for assistance with the TOC graphic. The work performed was supported by the Plutonium-238 Supply Program at ORNL. The authors wish to thank Nonreactor Nuclear Facilities Division staff members Donald Caverly and Roger Weaver for making the hot cell operations involved in this work possible and Radioisotope Science and Technology Division staff members Dennis E. Benker and David W. DePaoli for designing the column conditions and support. The authors also thank the Chemical Sciences Division for making alpha spectroscopy and ICP-MS data on stream samples available for comparison. Notice: This manuscript has been authored by UT-Battelle LLC under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).
| Funders | Funder number |
|---|---|
| U.S. Department of Energy | |
| Office of Nuclear Energy | DEAC05-00OR22725 |
| Oak Ridge National Laboratory | |
| Science Mission Directorate | |
| UT-Battelle | DE-AC05-00OR22725 |
Keywords
- Anion exchange
- Hot cell
- Kennard-stone
- Machine learning
- Multivariate analysis
- Neptunium
- Partial least squares
- Plutonium
- Principal component analysis
- Spectrophotometry
- Supervised
- Unsupervised