Spectroscopic Quantification of Target Species in a Complex Mixture Using Blind Source Separation and Partial Least-Squares Regression: A Case Study on Hanford Waste
Author:
Affiliation:
1. School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
Funder
Center for Risk Evaluation and Stakeholder Participation
Publisher
American Chemical Society (ACS)
Subject
Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.1c01387
Reference34 articles.
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4. Poirier, M. R.; Howe, A. M.; Miera, F. R.; Stone, M. E.; DiPrete, C. C.; Farrar, M. E. WTP Real-Time In-Line Monitoring Program Tasks 4 and 6. Data Quality and Management and Preliminary Analysis Plan; Savannah River Site, 2017.
5. Toward Understanding the Effect of Low-Activity Waste Glass Composition on Sulfur Solubility
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