Article Cite This: Anal. Chem. 2018, 90, 2548−2554
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Multivariate Analysis To Quantify Species in the Presence of Direct Interferents: Micro-Raman Analysis of HNO3 in Microfluidic Devices Amanda M. Lines,*,† Gilbert L. Nelson,‡ Amanda J. Casella,† Job M. Bello,§ Sue B. Clark,†,⊥ and Samuel A. Bryan*,† †
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, United States Department of Chemistry, College of Idaho, 2112 Cleveland Boulevard, Caldwell, Idaho 83605, United States § Spectra Solutions Inc., 1502 Providence Highway, Norwood, Massachusetts 02062-4643, United States ⊥ Washington State University, Department of Chemistry, Pullman, WA 99164, United States ‡
S Supporting Information *
ABSTRACT: Microfluidic devices are a growing field with significant potential for applications to small scale processing of solutions. Much like large scale processing, fast, reliable, and cost-effective means of monitoring streams during processing are needed. Here we apply a novel micro-Raman probe to the online monitoring of streams within a microfluidic device. For either macro- or microscale process monitoring via spectroscopic response, interfering or confounded bands can obfuscate results. By utilizing chemometric analysis, a form of multivariate analysis, species can be accurately quantified in solution despite the presence of overlapping or confounding spectroscopic bands. This is demonstrated on solutions of HNO3 and NaNO3 within microflow and microfluidic devices.
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knowledge of HNO3 concentration is, in some cases, vital to system performance. An example of this can be seen in the reprocessing of used nuclear fuel where the plutonium uranium extraction (PUREX) and related separation processes are highly dependent on HNO3 concentration.12−15 Previously published work demonstrates that Raman spectroscopy can be successfully utilized to measure HNO3 concentration in solution.13,14,16−18 While multivariate analysis was used to quantify HNO3 in the listed references, solution conditions were relatively simple; overlapping bands, matrix effects, or systematic baseline shifts did not pose a significant difficulty to quantifying species. Chemometric analysis has been applied to spectroscopic monitoring systems exhibiting complex band structures of not fully confounded species.1,13,17,19,20 In this work, the successful quantification of HNO3 in the presence of directly interfering species is demonstrated. Demonstration of successful spectroscopic analysis of systems with overlapping bands can have a tremendous impact on industrial and even lab scale applications of spectroscopy. Applications are shifting toward online real-time data analysis systems capable of analyzing flowing or continuous process systems. This can be observed in several industries including food processing and pharmaceuticals.4,21,22 Other fields could benefit from the utilization of online real-time process
pectroscopy is a profoundly common technique that is applied across a range of microscale experiments to industrial scale online systems.1−4 Typically used for identification and quantification of species, a myriad of spectroscopic techniques are available to isolate the desired analyte signature, including absorbance, fluorescence, infrared, Raman, etc. In general, spectroscopy is a valuable tool because it provides fast results, employs simple experimental setups, and is nondestructive in nature. However, spectroscopic analysis can be difficult to apply to complex systems. Analysis of solutions containing multiple species can become difficult when the system exhibits overlapping bands, matrix effects, and baseline shifts.5 This is particularly notable when traditional methods of single variate analysis (e.g., Beer’s Law) are used to quantify a species on the basis of the spectroscopic response at a single point (e.g., wavelength). The work presented here describes an advanced approach to the analysis of spectroscopic data that allows for accurate and precise identification of species under complex solution conditions. Namely, this work explores the application of multivariate, or chemometric, analysis to the quantification of species in solution where species exhibit confounding bands. This builds on and expands the applicability of previously demonstrated forms of spectroscopic analysis and online monitoring.6−11 Of specific interest to this work is the quantification of nitric acid (HNO3) in solution. HNO3 is a key component in a variety of laboratory and industrial scale solution systems, and © 2018 American Chemical Society
Received: September 19, 2017 Accepted: December 21, 2017 Published: January 30, 2018 2548
DOI: 10.1021/acs.analchem.7b03833 Anal. Chem. 2018, 90, 2548−2554
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0.14, 0.14, 0.999 0.13, 0.13, 0.999 0.19, 0.19, 0.999 0.12, 0.12, 0.999 3
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(1) normalize to area of the water band; (2) (2nd order polynomial); (3) mean center (1) normalize to area of the water band; (2) (2nd order polynomial); (3) mean center (1) normalize to area of the water band; (2) (2nd order polynomial); (3) m center (1) normalize to area of the water band; (2) (2nd order polynomial); (3) mean center set 1, 4 cm static vials set 1, 4 cm static vials set 1, 4 cm static vials set 1, 4 cm static vials Figure 6
solution length solution length solution length solution length Figures 4 and 5 (top) Figures 4 and 5(bottom) Figure 6
PLS: modeling conc of HNO3 with NaNO3 present PLS: modeling conc of total NO3 with HNO3 and NaNO3 present PLS: modeling conc of HNO3 with NaNO3 present PLS: modeling conc of total NO3 with HNO3 and NaNO3 present
RESULTS AND DISCUSSION Micro-Raman System. The micro-Raman system was designed with the goal of interrogating solutions within lowvolume cells (
