Multivariate Analysis To Quantify Species in the Presence of Direct Interferents: Micro-Raman Analysis of HNO₃ in Microfluidic Devices

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 HNO and NaNO within microflow and microfluidic devices.

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

“…18 Partial least squares regression (PLSR) is a statistical, multivariate approach relating spectral features to concentration in multicomponent systems. 19,20 PLSR relates the independent (X matrix) and dependent (Y matrix) variables with linear combinations of latent variables. X represents an n  m matrix of n samples across m wavelengths (i.e., spectra), and Y represents the response matrix (i.e., concentration) for n samples.…”

Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy

“…However, the quantification of multiple and/or confounding species in solution has been made possible by advancements in mathematical approaches such as multivariate regression analysis. 5–12…”

“…One useful example of PLSR is that the effects of covarying analytes can be modeled simultaneously. 11,12…”

“…However, the quantification of multiple and/or confounding species in solution has been made possible by advancements in mathematical approaches such as multivariate regression analysis. [5][6][7][8][9][10][11][12] Partial least squares regression (PLSR) is one of the most commonly used techniques used across multiple disciplines to generate predictive models. 13,14 Partial least squares (PLS) methods are ideal for spectral analyses since the data is inherently over-determined, noisy, and correlated.…”

“…One useful example of PLSR is that the effects of covarying analytes can be modeled simultaneously. 11,12 Raman spectroscopy was chosen given its sensitivity to the analytes of interest [15][16][17] and ability to be performed remotely in a hot cell via optical fibers. In alkaline solution, the primary Al-bearing species is the four-coordinate AlðOHÞ À 4 ion with tetrahedral symmetry.…”