Micro-Raman technology to interrogate two phase extraction on a

Subscriber access provided by University of Winnipeg Library

Article

Micro-Raman technology to interrogate two phase extraction on a microfluidic device Gilbert L. Nelson, Susan E. Asmussen, Amanda M. Lines, Amanda J. Casella, Danny Bottenus, Sue B. Clark, and Samuel A. Bryan Anal. Chem., Just Accepted Manuscript • Publication Date (Web): 07 May 2018 Downloaded from http://pubs.acs.org on May 7, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

Micro-Raman technology to interrogate two phase extraction on a microfluidic device Gilbert L. Nelson,†,ǂ Susan E. Asmussen,§,ǂ Amanda M. Lines,§, ǂ Amanda J. Casella,§* Danny R. Bottenus,§ Sue B. Clark, §,‡ and Samuel A. Bryan§* †

The College of Idaho, Department of Chemistry, Caldwell, Idaho, 83605, United States Pacific Northwest National Laboratory, Richland, Washington 99352, United States ‡ Washington State University, Department of Chemistry, Pullman, Washington, 99164, United States

§

ABSTRACT: Microfluidic devices provide ideal environments to study solvent extraction. When droplets form and generate plug flow down the microfluidic channel, the device acts as a microreactor in which the kinetics of chemical reactions and interfacial transfer can be examined. Here we present a methodology that combines chemometric analysis with on-line micro-Raman spectroscopy to monitor biphasic extractions within a microfluidic device. Among the many benefits of microreactors is the ability to maintain small sample volumes, which is especially important when studying solvent extraction in harsh environments, such as in separations related to the nuclear fuel cycle. In solvent extraction, the efficiency of the process depends on complex formation and rates of transfer in biphasic systems. Thus, it is important to understand the kinetic parameters in an extraction system to maintain a high efficiency and effectivity of the process. This monitoring provided concentration measurements in both organic and aqueous plugs as they were pumped through the microfluidic channel. The biphasic system studied was comprised of HNO3 as the aqueous phase and 30% (v/v) tributyl phosphate in n-dodecane comprised the organic phase, which simulated the Plutonium Uranium Reduction EXtraction (PUREX) process. Using pre-equilibrated solutions (post extraction) the validity of the technique and methodology is illustrated. Following this validation, solutions that were not equilibrated were examined and the kinetics of interfacial mass transfer within the biphasic system were established. Kinetic results of extraction were compared to kinetics already determined on a macro scale to prove the efficacy of the technique.

Separation techniques are broad and varied, and include techniques such as electrophoresis, chromatography, filtration, and distillation.1 Solvent extraction (SX) is a prevalent method of separating, concentrating, and modifying analytes in solution by utilizing the interface between two immiscible liquids to prompt separation.1-3 A variety of equipment can be used for a given extraction method, including, but not limited to, standard laboratory glassware, centrifugal contactors, pulsed columns, and mixer-settlers.1,4,5 However, these methods have disadvantages with respect to large sample volumes, long equilibration times, and ill-defined hydrodynamic regimes.1,3,5 Microfluidic devices (MFDs), sometimes called lab-on-a-chip technology, aim to overcome the difficulties presented in the larger, macro-scale system. Miniaturizing SX not only is advantageous in terms of small sample volumes,2,6,7 waste reduction,1,7,8 and controlled hydrodynamics,1,8 but also in sample portability,9,10 decreased experimental time due to increased transport phenomena in microsystems,2,11,12 and a higher throughput of experiments.5,6,13 Microfluidic devices are becoming increasingly more common experimentally, particularly in the realm of liquid-liquid extractions.1-3,6,8,14-16 An on-line analysis method is crucial to probe the reactions and transfer occurring within a MFD. While detection methods can be used off-chip, such as mass spectrometry and highperformance liquid chromatography,12 these methods do not allow for continuous on-line monitoring within the MFD. Spectroscopic methods, such as ultraviolet-visible (UV-vis) absorbance, infrared (IR), and Raman spectroscopy have

shown to be effective on-chip detection methods to monitor local interfaces and provide real-time data collection of solutions within the MFD.12,17,18 More specifically, Raman spectroscopy has proven to be an effective technique for monitoring and optimizing chemical reactions within MFDs.10,17,18 The variety of laser light sources, the ability to examine both organic and aqueous solutions, coupled with the fact that the Raman spectra of water provides a mostly unobstructed spectral window with no interference,10 makes Raman spectroscopy a promising on-line, in situ detection method. While the use of Raman spectroscopy to investigate nitric acid (HNO3) systems has been established,19,20 established methods did not involve solvent extraction on the droplet scale or kinetic measurements. To allow on-line analysis in a MFD, a micro-Raman probe with the capability to focus within the channel of the MFD was developed. With a focal point of 69 µm,20 the focal point of the Raman probe fits well within the confinements of the microchannel (300 µm × 250 µm). By integrating this probe with a MFD to measure spectra on a microfluidic scale, both aqueous and organic phase Raman spectra can be collected from a single experiment for further analysis, especially for the purposes of SX. To examine the interfacial transfer and kinetics associated with extraction, a quantitative assessment of the concentration of analytes of interest in each phase as a function of extraction time is required. Due to non-linearity of Raman signals and confounding variables in resulting spectra, the use of multivar-

1 ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

iate analysis, specifically partial least squares (PLS) analysis, is the preferred modelling method for complex systems. Using Raman spectra collected within a MFD channel, chemometric analysis can bridge the gap to gain understanding of concentration profiles as a function of time in SX. This work focused on feasibility of implementing a microRaman probe for use in a MFD to study the kinetics of the well-defined extraction of HNO3 by TBP. To our knowledge, this is the first demonstration of this extraction on the microfluidic scale. The novelty of the methodology and technique lies in the fact that this work can measure interfacial transfer in real time, without further chemical work up, is in situ and does not require aliquots for sample analysis, and is nondestructive. Building on a recently developed micro-Raman probe,20,21 and methodology for on-line measurement in a two phase Lewis Cell extraction system,22,23 methods were advanced to collect Raman spectra in aqueous and organic phases on-line as they were pumped down the microchannel of a single channel MFD in a segmented plug flow pattern. The flow rate may be adjusted to obtain steady 1:1 volumes for the alternating droplets.5 The result is a large surface contact area and a small bulk volume that permits a fast equilibrium to be established during the course of the droplet flow through the chip.2,5-7,11,12 Initial studies were focused on simple and well understood HNO3 extraction system to establish firm controls and understanding of the on-chip process and the on-line monitoring results. Collected spectra were analysed by chemometric analysis to determine concentration changes within the organic and aqueous phase. To validate the method for use in SX, the welldefined system of HNO3 and 30% (v/v) TBP in n-dodecane were used to simulate the Plutonium Uranium Reduction EXtraction (PUREX) process. Studies were initially performed with pre-equilibrated solutions, to eliminate the need to determine and identify transient species, prior to studies of extraction within the MFD for validation. The goal of this methodology is to detail and monitor the kinetics associated with the extractions that can occur within a MFD. While there are many methods available for concentration measurements of HNO3, these methodologies are either not in situ or the analysis occurs off chip, post biphasic separation. To be comparable to the in situ Raman technique presented here, the methodology must not have any sample pretreatment or post-treatment. Zhu et al.24 reviewed methods for analytical detection within droplet microfluidics with common analytical detection techniques. In addition to Raman spectroscopy, these methods include bright-field microscopy, fluorescence microscopy, laser induces fluorescence, electrochemistry, capillary electrophoresis, mass spectroscopy, nuclear magnetic resonance spectroscopy, and absorption detection.24 For purposes of comparison to our system, we focused on detection techniques relevant in droplet based reactions and solvent extraction. Imaging-based droplet analysis techniques have limited use in solvent extraction. Imaging based techniques, such as bright-field microscopy, can determine the shape, size, color, and other information regarding droplets of interest.25 While the imaging effectively shows the droplet formation and interactions during their progression down the microchannel, no quantitative information regarding solvent interaction or interfacial transfer can be gathered unless solutions are colored. In our case, solutions in the organic and aqueous phase are both

Page 2 of 10

clear and colorless, thus rendering imaging based technology only valuable for droplet size, formation, and progress with no analytical information gathered from this technique. Fluorescence imaging techniques and laser-induced fluorescence detection have proven beneficial in droplet techniques involving fluorescing compounds of interest. Fluorescence imaging is limited in that high throughput screening can often not be achieved due to fact that the frame rate of the CCD camera is normally lower than the frequency of droplet generation. However, laser-induced fluorescence is able to overcome this drawback and provide high sensitivity.24 Over time, kinetic data can be analyzed at different time points down the microchannel by taking measurements at varying positions down the channel length.26 Unfortunately, there lies a large limitation in that compounds of interest must be fluorescent. Those molecules that do not fluoresce (such as nitric acid) will give no analytical information using this technique or will require additive compounds in solution. Raman spectroscopy can be used in microfluidic solvent extraction as a label-free detection technique, provided the species of interest is Raman active. Surface-enhanced Raman scattering (SERS) is an extension of the technical capabilities of Raman. Using SERS, the ability to quickly measure droplets in MFDs can be greatly enhanced by using electromagnetic enhancement mechanisms as well as chemical enhancement mechanisms.27 However, while the SERS technique presents many benefits over conventional Raman techniques, it does require localized surface plasmon resonances (LSPRs). Such resonances are typically derived from metals, which must be added to solution, limiting the utility and broad application of this technique.27 With the correct MFD set up, electrochemical detection can be used as an analytical technique to determine physical characteristics and ion concentrations using impedance techniques.24 Capacitance techniques can also prove useful in electrochemical detection. To obtain chemical information within the droplets amperometric-based methods were utilized to measure rapid enzyme kinetics. However, there were drawbacks in this method in that two phase systems caused detection issues in the electrodes and further analysis required the separation of the two phases, a process which is not desirable when measuring solvent extraction. Capillary electrophoresis is a methodology that is growing to allow for detection,28 in addition to separation. This technology is mainly focused on biological applications and research. However, applications thus far are still primarily separations based, and secondary detection techniques are normally required for analysis following phase separation. With the exception of Raman spectroscopy, the detection techniques listed above are not suitable for purposes of measuring the kinetics of solvent extraction in the system we are interested in. For a directly comparative analysis, Pandey et al.29 studied the macro-scale extraction of nitric acid by tributyl phosphate in n-paraffin hydrocarbons using various organic and aqueous concentrations. While the extraction itself is similar in mechanism, the experimental set up and data treatment differ. Experiments were performed in a constantly stirred cell that maintains a known interfacial area. To determine the concentration of nitric acid in the organic and aqueous phases during the experiments aliquots of the organic phase and the aqueous


Page 3 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


phase were withdrawn at regular intervals. No on-line or in situ testing was performed. An additional advantage for using the micro-Raman probe technique for in situ MFD analysis, is the ability to measure other extraction species in addition to nitric acid. Raman spectroscopy has been shown to differentiate and quantify nitrate, nitric acid, and uranyl ion simultaneously30. The other techniques are limited in their ability to measure multicomponent mixtures. We use nitric acid for initial demonstration purposes, but we are actively pursuing the extraction of other species including uranyl nitrate and other metal and organic species common to nuclear fuel reprocessing. The novelty of the methodology and technique lies in the fact that this work can measure interfacial transfer and complexation in real time, is in situ, does not require aliquots (that often require further sample preparation or larger sample sizes) for sample analysis, and is non-destructive. Experiments can be monitored in real time as an extraction progresses, and, due to the small sample volumes, the extraction occurs on a shorter time scale than those samples with larger volumes. This work is a continuation of our group’s efforts to design, develop, and demonstrate spectroscopy based sensor applications on systems in harsh environments. These sensor applications can be used for a variety of chemical constituents in nuclear fuel reprocessing19,31-34 and related nuclear waste solutions;35-38 at macro23,29 and microfluidic39-41 scales.

packaged in a small handheld probe head with fiber optic connections to the laser and the spectrograph. An Ethernet cable connects the CCD video camera to the computer for live display of the magnified sample image.

Chemometric Modelling PLS multivariate analysis is a powerful linear algebra based method of quantifying some system property (here the concentration of HNO3) based on the covariance observed between that property and the other system variables in a well characterized reference set – the training set or calibration set. This technique algebraically decomposes the spectral variables and the corresponding concentration variables into matrices that describe the maximum covariance in succeeding orthogonal dimensions. These latent variables may be linearly combined to form models for predicting properties in newly recorded measurements. All chemometric models were generated using Eigenvector Research PLS toolbox for MATLAB (version R2015B utilized here). Details on model types, numbers of principal components, and model performance parameters are included in the discussion. Training sets used to construct prediction models for each phase were composed of ten duplicate Raman spectra, taken in the MFD channel, of pre-contact and post-contact aqueous and organic static solutions. Actual HNO3 concentrations of these solutions were obtained by automated titration.

RESULTS AND DISCUSSION

EXPERIMENTAL SECTION

System overview A simple schematic of the experimental system is presented in Figure 1 along with a picture of the Raman laser focused in the channel of the MFD. Note, the channel width of the MFD is 300 µm while the focal point diameter of the Raman excitation laser is 69 µm. This allows for accurate measurement of solutions within the MFD channel.20,21 Both Raman probe and MFD can be held stationary or the MFD can be moved relative to the probe. Moving the MFD to interrogate solutions down the length of the MFD allows for the exploration of kinetic parameters on the chip, giving multiple target measurement points down the channel.42

Materials and Solutions Concentrated nitric acid (HNO3, ACS reagent grade concentration, 70%), trace metal grade, was purchased from Fisher, and used as received. All aqueous solutions were prepared with ≥ 18.2 Ω•cm deionized water (Barnstead E-Pure Ultrapure Water Purification System). Concentrations of HNO3 were confirmed by automated titration with standard NaOH. Tributyl phosphate (TBP, purity 98%) and n-dodecane (purity 99+%) were both purchased from Alfa Aesar and comprised the organic phase. Water-washed n-dodecane was used in experiments, while TBP was used without further purification. Spectral equipment Spectral measurements were obtained using a micro-Raman probe (beam diameter 69 µm). The micro probe was used with a Spectra Solutions Inc Raman fiber optic spectrometer using a continuous wave 670 nm diode-pumped solid state (DPSS) laser, and a high-throughput volume phase holographic (VPH) grating Raman spectrograph. A custom transmission VPH grating spectrograph with a thermoelectrically (TE)cooled charge-coupled device (CCD) detector was used to record the Raman signal from the Raman probe over the spectral range of 200 cm-1 to 3800 cm-1 at a resolution of ~ 6 cm-1. The probe employs a miniature fiber optic Raman probe with a backscattering optical design and a board level CCD video camera for live video imaging of the sample. A dichroic long pass filter that transmits the 670 nm Raman region and reflects the visible region for imaging is placed in between the CCD camera and the Raman probe. The dichroic filter overlaps the optical axis of the Raman and the video image so that both are focused on the same spot at the sample and thus have a common field of view. A 10× objective lens which focuses the laser beam to 69 µm, collects the Raman signal and provides a magnified image of the sample. The Raman microscope was



Figure 1. A) Schematic of micro-Raman system. B) Photograph of micro-Raman probe positioned for measurement within microfluidic chip. The laser beam for Raman excitation (670 nm) is focused into the microfluidic channel.

Page 4 of 10

Initial analysis of the Raman spectra of stationary (no flow) aqueous solutions injected into the MFD before extraction (pre-contact) and after extraction (post-contact) showed a reduction in the nitrate band Raman intensity with decreasing concentration at 1047 cm-1.52,53 This reduction is related to extraction of HNO3 from the aqueous phase to the organic phase (Figure 3 B and C, Equation 1). Raman spectra of the 30% (v/v) TBP in n-dodecane organic phase shows the opposite trend in an initial analysis of stationary solutions injected into the MFD pre- and post-contact. Figure 3 B and C shows several Raman spectral regions associated with HNO3 migration that increase in intensity as the organic phase extracts increasingly more concentrated aqueous phases. The strongest peaks, appearing at 940 cm-1 (ν N(OH)), 1220 cm-1, and 1310 cm-1 (νs NO2), in Figure 3 C comprise the region of the spectrum that was used to produce the chemometric model for predicting organic HNO3 solution concentrations in the flow portion of this study.

The system is equipped with a camera that gives a real time image of the formed droplets flowing past (Figure 2). This feature permits flow rate adjustment to give the desired droplet formation size, and also allows confirmation of steady flow of the alternating phase droplets.

Figure 2. A real time image of the formed droplets flowing past the on-board system camera. The interface between the two phases is shown. The aqueous phase slug is seen on the left and the organic phase slug is seen on the right.

Stationary extraction studies In this work the extraction of HNO3 from an aqueous phase to an organic phase by TBP was studied. Under the conditions examined, the extraction occurs primarily through the formation of a 1:1 adduct, HNO3•TBP, Equation 1.43-46 HNO3 + TBP ⇌ HNO3•TBP

(1)

The adduct is formed via a hydrogen-bonded bridge between the phosphoryl group on TBP and the HNO3 proton. The adduct forms at or close to the interface before transferring to the organic phase.29 The extraction can be measured by determining the concentration of HNO3 in the organic and aqueous phase as a function of time. Concentrations of HNO3 and TBP in n-dodecane were chosen to reflect concentrations relevant to the PUREX process. The Raman spectra associated with nitric acid in aqueous solution have bands diagnostic for nitric acid and nitrate ion as shown in Figure 3 A. For solutions less than 2M, three bands were observed associated with nitrate ion in accordance with the unperturbed nitrate ion being trigonal planar geometry within the D3h point symmetry group21,47. The 1048 cm-1 band is the most intense band observed, and is assigned to the ν1 symmetric stretch, the band located at 1411 cm-1 is assigned to the ν3 asymmetric stretch, and the 719 cm-1 band assigned to the ν4 in-plane deformation; and are assigned to the A1, E’, and E’ modes respectively48. Also observed in Figure 3 A, is the Raman spectroscopic signature of bulk water, which is characterized by the asymmetric and symmetric stretching bands (ν1A1 and ν3-B1 respectively) ranging from approximately 2900 cm-1 to 3800 cm-1, and symmetric bending (ν2-A1) modes from approximately 1500 cm-1 to 1750 cm-1, under C2v symmetry49-

Figure 3. A) Full scale Raman spectra associated with nitric acid in aqueous solution. B) Raman nitrate peak of the aqueous phase before and after extraction. Sample normalized to water band. C) Organic phase after extraction.

Alternating phase flow study The sequence of spectra generated by continuously monitoring a flow series of alternating aqueous and organic droplets displays distinctive alternating regions. Figure 4 A shows the sequence of raw spectra recorded as alternating phases of a post-contact 5 M aqueous HNO3 solution and post-contact 30% (v/v) TBP in n-dodecane solution, already brought to equilibrium, are monitored by the micro-Raman system. The aqueous phase displays the single dominant peak (dominant red topped peak in Figure 4) associated with the NO3- from

51


Page 5 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


HNO3 in solution.21,52-54 The organic phase features a very large C-H stretch related peak,55 just below 3000 cm-1 (yellow topped peak in Figure 4 A), and a complex series of weaker peaks related to C-H (C-H bend, 720 cm-1), and P-O (ν1 PO43symmetric stretching at 959 cm-1, ν3 PO43-antisymmetric stretching at 1032 cm-1 and 1062 cm-1) interactions between 700 cm-1 and 1400 cm-1.55-60

subsets of spectra are left out when building the model from the test set spectra, and then predicted and known concentration values are compared for the spectra left out. See the figure legend for these values. As a demonstration of the accuracy of the method to determine the concentrations within a flow system of alternatively switching between aqueous and organic phases, the chemometric models were applied to a flow system described above. The flow system contained alternating aqueous and organic droplets that were post-contact, with concentrations of nitric acid at 2.70 M and 0.32 M respectively. The model results (Figure 5, C) agreed with known values within the standard deviation of measurement.

Figure 4. A) Raman response over time as different phase droplets flow past the micro-Raman probe; B) overhead view of data presented in top plot, repeated droplet signature visible.

Building chemometric models Data collected from the static extraction studies was used to construct training sets that captured the spectral variance associated with different concentrations of HNO3 in both the organic and aqueous phases. These training sets (and the associated concentration matrices) were used to build chemometric models that correlate spectral variance to concentration of HNO3. Spectra from each phase required different pre-processing steps in order to optimize the model created for each one. The organic phase, which was modelled based on the region between 900 cm-1 and 1400 cm-1, required the application of a least squares baseline and normalization of all variables in that range. The aqueous phase was modelled over a much wider range to include both the NO3- peak at 1047 cm-1 (ν1s NO3, 1047 cm-1)19,52,53 and the water peak between 3700 cm-1 and 4000 cm-1 (ν3 and ν2 frequencies of water).33,55 A scaling step was included in the prepossessing to deal with any baseline variations or laser power fluctuations. Specifically, the aqueous model used a first derivative step to baseline the spectra, and then a Variable Standard Scaling was applied. Such pre-processing gives rise to good predictive ability as is indicated by the parity plots shown in Figure 5. Crossvalidation calculations on the models built for each phase show good agreement between the modelling error, RMSEC, and the error associated cross-validation (RMSECV), where

Figure 5. Parity plots comparing the chemometrically measured concentration of nitric acid to the known nitric acid concentration in the aqueous (A) and organic (B) phases. Demonstration of model performance on alternating droplets of aqueous and organic solutions (C).

Application of chemometric models To validate this technique and method of measurement, the kinetics of extraction of HNO3 from the aqueous phase by TBP in the organic phase were measured. Pre-contact, nonequilibrated organic and aqueous solutions were brought together in a T-channel MFD (Translume) that contained two



inlets (an organic inlet and an aqueous inlet) and one outlet (Figure 6 A). The phases came into contact with one another at the T-juction of the microchannel and generated alternating organic and aqueous phase droplets as they entered the channel. The centre channel was 38 mm long which allowed for droplet interaction and extraction of HNO3 along the length of the channel. By adjusting the flow rate of each solution a 1:1 alternating aqueous:organic phase volume ratio was established. The MFD could be moved relative to the Raman probe to allow for the collection of spectra at difference positions along the microchannel (Figure 6 B). By focusing the microRaman at various points along the channel, the extraction could be monitored in on-line from the collected Raman spectra. Raman spectra were then analysed using chemometric modelling to determine the concentrations of HNO3 in the organic and aqueous phases at the specified distances down the channel. A profile of HNO3 concentration versus time was generated for kinetic analysis (Figure 6 C).

Page 6 of 10

lected per droplet, 60 droplets of alternating organic and aqueous phases flowed past the micro-Raman at a given collection point). The five data points noted in Figure 6 B correspond to measured points along the microfluidic channel: each point has a measured value in mm from the T-channel junction. Because the speed of the fluids, and ultimately the droplets, within the microfluidic channel is known, the amount of time it takes for a droplet to reach a given specified point along the microfluidic channel can be determined. Each point along the channel, labelled 1 through 5, was calculated as a measurement of time in s, to allow for the determination of the kinetics of interfacial mass transfer. The data presented in Figure 6 C which shows the results of measurements made at five locations along the MFD channel can be used to explore fundamental characterization of the extraction. The rectangular box represents the interquartile range (from the 25th percentile to the 75th percentile), with the filled circles (●) representing the mean, the line through the center of the box ( ─ ) representing the median, and the whiskers coming off the box representing the 5th and 95th percentile. The solid black line connecting the boxes represents the kinetics fit calculated. To determine the kinetics of extraction, the equilibrium observed can be defined as Equation 2: HNO3(aq) ⇌ HNO3(org) (2) where the forward and reverse rate of interfacial mass transfer coefficients defined as kf and kr, respectively. Presuming no initial additional chemical reactions, and with the initial and final aqueous and organic concentrations and distribution ratios at equilibrium (D, Equation 3) known from experimental conditions, the rate equation can be defined as Equation 4:61

(3)

! "# $ % ! &'

(4)

where A is the interfacial area (mm2), V is the volume of a droplet (mm3), t is the time measured in seconds, square brackets represent concentration, and the subscripts aq and org note the phase of interest. Images of the organic and aqueous droplets flowing in the MFD were collected using a digital microscope (Olympus DSX510) to determine the interfacial area and droplet volume. The OM software allowed for droplet dimensions to be generated to determine the interfacial area between droplets and the calculations of the total droplet volume. The term A/V is presumed constant for each experiment because the MFD components remain unchanged for each experiment, allowing the assumption that the volume and resulting interfacial area remains constant. Integrating Equation 4 with the initial condition of HNO3(org)(0)=0, and rearranging to solve for the interfacial mass transfer coefficient yields Equation 5.61

Figure 6. A) The T-junction MFD used for biphasic kinetic measurements, showing the separate aqueous and organic inlets, with the mixed dual phase outlet. B) A schematic of the MFD indicating the evenly spaced points along the microfluidic channel where Raman spectra were collected; where point 1 is at time 4.9 s, which is 4.9 s from the T-junction, and point 5 is at time 70.2 s. C) A box whisker plot showing the HNO3 concentration over time in the organic phase.

The aqueous flow solution was a single solution of 2.97 M HNO3, while the organic flow solution was comprised of 30% (v/v) TBP in n-dodecane. For this flow experiment spectra were collected at 5 equally spaced points down the MFD channel, Figure 6, with 300 spectra collected at each set distance for a total of 1500 spectra. Of the 300 spectra collected at each defined distance point, three to five consecutive spectra of alternating organic and aqueous phase spectra were collected for each droplet (i.e. presuming five spectra were col-

$

( ) 1 $

1 -

,,

./

(5)

The subscript eq denotes conditions at equilibrium. By fitting the concentration versus time data, and using the known constants present in Equation 5, kr can be solved. The kr value


Page 7 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


was optimized using the Microsoft Solver Add-In function, and the standard deviation for the kr term was determined. The forward interfacial mass transfer coefficient kf can in turn be calculated from Equation 3, as well as the corresponding standard deviation.5 The kf and kr values can be determined using either the organic or the aqueous phase data. There is a lower signal-to-noise ratio in the aqueous phase, resulting in a larger standard deviation in the k values when calculated using the aqueous phase. It was confirmed that values calculated using the organic and aqueous phase agreed (with the aqueous giving a higher standard deviation). Thus, for this work the organic phase was used to determine the kr before calculating the kf using Equation 3. As observed in Figure 6 C, the system did not reach an equilibrium organic HNO3 concentration during the course of the experiment. Literature values and experimental results measuring batch extractions show that 20% of the HNO3 in the aqueous phase is expected to form the adduct and transfer to the organic phase.23,62 In contrast, 15.6% of the HNO3 in the aqueous phase transferred to the organic phase in the adduct formation in the separation illustrated. This lesser transfer can be attributed to the flow rate affecting the mixing within the slugs, and the longer slug lengths.5 Because the purpose of this work was to validate the experimental technique, the flow rate was not manipulated to determine optimal flow and mixing conditions within the system. The separation performed, however, does validate this methodology, and future experimental work will include different mixing speeds within the microfluidic channel. Results indicated that the kf is 1.0 (± 0.1) × 10-3 mm s-1, while the kr is 6.4 (± 0.5) × 10-3 mm s-1 for the extraction of HNO3 from the aqueous phase to the organic phase by the formation of an adduct with TBP. The fit of kr relative to the collected data points is illustrated in Figure 6 C. While the fit does accurately follow the data trend, and the standard deviation is < 10%, it can be seen that there is a discrepancy between the kinetic fit and the data points. Because validation sets include both aqueous and organic spectra, archetypal binning was used to separate data and apply the appropriate aqueous or organic phase model. This involves applying models and removing non-applicable phase data via setting a limit on Q residuals. In its current form, this approach suffers some limitations, stemming from overlap of important bands in the aqueous and organic phases. Additional difficulties in analysing data can be traced back to droplet length, where only 4-5 spectra can be reasonably collected per droplet. Data points collected at either end of the droplet can experience spectral interferences from neighboring droplets of different phases. Alternatively, if the previous droplet left any residue in the channel, a “smear”, it could interfere with spectral signatures. Evidence of both of these behaviors can be seen in the Q residuals observed for measurements across droplets. A saddle shape with high Q residuals at either end of the droplet can indicate interferences from surrounding droplets while a downward slope of Q residuals can indicate the presence of a smear being washed away. Examples of these can be seen in Figure 7. Overall, this results in undesirable spread in HNO3 concentration measurements, as indicated in the standard deviation of data points in Figure 6. Future work will focus on improving precision of measurements by generating improved hierarchical modelling approaches that can utilize a better Q residual cut off to remove data points where

neighboring phases have compromised spectra. Additionally, modifying data collection parameters to allow for increased sampling in the center of droplets will reduce measurement spread. To test whether the interfacial mass transfer kinetics calculated using the MFD methodology were accurate, kinetics values were compared to results obtained using a conventional Lewis cell methodology with the same initial conditions and concentrations. In the Lewis cell, the kf value was determined to be 4.75 (± 0.14) × 10-3 mm s-1, while the kr was calculated as 2.56 (± 0.03) × 10-2 mm s-1.23 .Comparatively, the values calculated from the Lewis cell extraction system agreed well with the values calculated from the MFD extraction. The rate of interfacial mass transfer in the Lewis Cell occurs at a marginally faster rate in the MFD. The stir speed used in the Lewis Cell was maximized to minimize diffusion effects in the system, while the extraction performed in the MFD was likely limited by diffusion due to the flow rate of the organic and aqueous phase. If an exact match of rate of interfacial mass transfer between the MFD and macro Lewis cell was desired, parameters such as flow rate in the MFD can be altered.

Figure 7. Q residual patterns across the length of droplets indicating interferences from neighboring droplets. Red and black lines indicate two of the most common patterns observed.

The agreement between the kr and kf values validates the novel methodology developed to interrogate solvent extraction using a MFD. The studies performed prove that a macroscale Lewis cell could be scaled down to a MFD and open new avenues for detection and measurements in SX using a microRaman probe and chemometric analysis. This work was performed to validate the experimental technique. Aqueous and organic concentrations in this work were chosen in accordance with concentrations currently used in industry. Results presented indicate that the methodology and technique used were effective in monitoring the interfacial transfer of HNO3 to the organic phase. Because the purpose of this work presented was for proof-of-concept, flow rate, concentration, and droplet size were not thoroughly investigated. Future work will build on the results described here to apply this technique to more complex extraction streams as well as optimize microscale extraction parameters to better match those of macroscale systems.

CONCLUSIONS A technique to monitor and measure the concentration of HNO3 within a microfluidic channel using on-line methodology was tested and presented. Using chemometric modelling the concentration of HNO3 was monitored under three condi-



Page 8 of 10

(6) Huebner, A.; Sharma, S.; Srisa-Art, M.; Hollfelder, F.; Edel, J. B.; deMello, A. J. Microdroplets: A sea of applications? Lab Chip 2008, 8, 1244-1254 (7) Kuswandi, B.; Nuriman; Huskens, J.; Verboom, W. Optical sensing systems for microfluidic devices: A review. Anal. Chim. Acta 2007, 601, 141-155 (8) Pinho, B.; Hartman, R. L. Microfluidics with in situ Raman spectroscopy for the characterization of non-polar/aqueous interfaces. React. Chem. Eng, 2017, 2, 189-200 (9) Ashok, P. C.; Dholakia, K. In Optical Nano- and Microsystems for Bioanalytics, Fritzsche, W.; Popp, J., Eds.; Springer Berlin Heidelberg: Berlin, Heidelberg, 2012, pp 247-268. (10) Viskari, P. J.; Landers, J. P. Unconventional detection methods for microfluidic devices. Electrophoresis 2006, 27, 17971810 (11) Tabeling, P. Introduction to Microfluidics; Oxford Univeristy Press: New York, NY, 2011. (12) Lee, M.; Lee, J.-P.; Rhee, H.; Choo, J.; Gyu Chai, Y.; Kyu Lee, E. Applicability of laser-induced Raman microscopy for in situ monitoring of imine formation in a glass microfluidic chip. J. Raman Spectrosc. 2003, 34, 737-742 (13) Xu, C.; Xie, T. Review of Microfluidic Liquid–Liquid Extractors. Ind. Eng. Chem. Res. 2017, 56, 7593-7622 (14) Lestari, G.; Abolhasani, M.; Bennett, D.; Chase, P.; Günther, A.; Kumacheva, E. Switchable Water: Microfluidic Investigation of Liquid–Liquid Phase Separation Mediated by Carbon Dioxide. J. Am. Chem. Soc. 2014, 136, 11972-11979 (15) Hotokezaka, H.; Tokeshi, M.; Harada, M.; Kitamori, T.; Ikeda, Y. System for high-level radioactive waste using microchannel chip — extraction behavior of metal ions from aqueous phase to organic phase in microchannel. Prog Nucl Energ 2005, 47, 439-447 (16) Wang, N.; Mao, S.; Liu, W.; Wu, J.; Li, H.; Lin, J.-M. Online monodisperse droplets based liquid-liquid extraction on a continuously flowing system by using microfluidic devices. RSC Adv. 2014, 4, 11919-11926 (17) Yue, J.; Schouten, J. C.; Nijhuis, T. A. Integration of Microreactors with Spectroscopic Detection for Online Reaction Monitoring and Catalyst Characterization. Ind. Eng. Chem. Res. 2012, 51, 14583-14609 (18) Cristobal, G.; Arbouet, L.; Sarrazin, F.; Talaga, D.; Bruneel, J.-L.; Joanicot, M.; Servant, L. On-line laser Raman spectroscopic probing of droplets engineered in microfluidic devices. Lab Chip 2006, 6, 1140-1146 (19) Bryan, S. A.; Levitskaia Tatiana, G.; Johnsen, A. M.; Orton, C. R.; Peterson, J. M. Spectroscopic monitoring of spent nuclear fuel reprocessing streams: an evaluation of spent fuel solutions via Raman, visible, and near-infrared spectroscopy. Radiochim. Acta 2011, 99, 563-571 (20) Casella, A.; Lines, A.; Nelson, G.; Bello, J.; Bryan, S. MicroRaman Measurements for Nuclear Fuel Reprocessing Applications. Procedia Chem. 2016, 21, 466-472 (21) Nelson, G. L.; Lines, A. M.; Casella, A. J.; Bello, J. M.; Bryan, S. A. Development and testing of a novel micro-Raman probe and application of calibration method for the quantitative analysis of microfluidic nitric acid streams. Analyst 2018, 143, 1188-1196 (22) Heller, F. D.; Casella, A. J.; Lumetta, G. J.; Nash, K. L.; Sinkov, S. I.; Bryan, S. A. Incorporating spectroscopic on-line monitoring as a method of detection for a Lewis cell setup. Analyst 2017, 142, 2426-2433 (23) Asmussen, S. E.; Lines, A.; Bottenus, D.; Heller, F. D.; Bryan, S.; Delegard, C.; Louie, C.; Ivory, C. F.; Lumetta, G. J.; Pellegrini, K.; Pitts, W. K.; Clark, S.; Casella, A. J. In situ monitoring and kinetic analysis of the extraction of nitric acid by tributyl phosphate in n-dodecane using Raman spectroscopy. Unpublished Work, Pacific Northwest National Laboratory 2018 (24) Zhu, Y.; Fang, Q. Analytical detection techniques for droplet microfluidics—A review. Anal. Chim. Acta 2013, 787, 24-35 (25) Yobas, L.; Martens, S.; Ong, W.-L.; Ranganathan, N. Highperformance flow-focusing geometry for spontaneous generation of monodispersed droplets. Lab Chip 2006, 6, 1073-1079

tions: 1) as static solution within the channel to build a chemometric model, 2) as flowing droplets of pre-equilibrated solutions that had already undergone extraction, and 3) as solutions without prior contact to enable the monitoring of extraction kinetics to validate the model. The agreement with pre- and post-contact extraction concentrations between the experimental and chemometric results indicates a robust model appropriate for modelling extraction within a microfluidic device using a micro-Raman probe. It was shown that on-line data collection on a microfluidic device was rapid, allowing for many experimental iterations and conditions with low levels of waste production. The monitoring allows for on-line collection of data, without the need for sample extraction or alteration of organic:aqueous ratios within an experiment. The rates of interfacial mass transfer measured are in agreement with values calculated for the same chemical system on the macro scale. Moving forward, the unique methodology can be fine-tuned and altered to monitor various species in solution, especially in the case of a more complicated solvent extraction system. The extraction in various other solvent systems can be studied, allowing for a deeper understanding of the various facets of liquid-liquid extraction.

AUTHOR INFORMATION Corresponding Author *Email: [email protected] Phone 1 509 375 5648 *Email: [email protected] Phone: 1 509 375 5622 Author Contributions ǂ These authors contributed equally.

ACKNOWLEDGEMENT This research was supported in part by the U.S. Department of Energy (DOE) Fuel Cycle Research and Development (FCR&D) Separations Campaign within the Office of Nuclear Energy (NE), the U.S. DOE; Nuclear Process Science Initiative at Pacific Northwest National Laboratory, a Laboratory Directed Research and Development Program at PNNL; Visiting Faculty Program (VFP), Office of Science (SC), and Small Business Innovative Research (SBIR) Grant, Office of Science (SC). PNNL is a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy. Pacific Northwest National Laboratory is operated by Battelle Memorial Institute for the U.S. Department of Energy under contract DE-AC05-76RL01830.

REFERENCES (1) Ciceri, D.; Perera, J. M.; Stevens, G. W. The use of microfluidic devices in solvent extraction. J. Chem. Technol. Biotechnol. 2014, 89, 771-786 (2) Mary, P.; Studer, V.; Tabeling, P. Microfluidic Droplet-Based Liquid−Liquid Extraction. Anal. Chem. 2008, 80, 2680-2687 (3) Lestari, G.; Salari, A.; Abolhasani, M.; Kumacheva, E. A microfluidic study of liquid-liquid extraction mediated by carbon dioxide. Lab Chip 2016, 16, 2710-2718 (4) Hanson, C. In Recent Advances in Liquid–Liquid Extraction, Hanson, C., Ed.; Pergamon Press: Elmsford, New York, 1971, pp 113. (5) Nichols, K. P.; Pompano, R. R.; Li, L.; Gelis, A. V.; Ismagilov, R. F. Toward Mechanistic Understanding of Nuclear Reprocessing Chemistries by Quantifying Lanthanide Solvent Extraction Kinetics via Microfluidics with Constant Interfacial Area and Rapid Mixing. J. Am. Chem. Soc. 2011, 133, 15721-15729


Page 9 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry (43) Moore, R. L., The Mechanism of Extraction of Uranium by Tributyl Phosphate; Atomic Energy Commission Report AECD-3196 Hanford Works: Washington, D.C., 1951. (44) Tuck, D. G. 567. Solvent extraction studies. Part II. The system nitric acid-water-tri-n-butyl phosphate. J. Chem. Soc. 1958, 2783-2789 (45) Olander, D. R.; Benedict, M. The Mechanism of Extraction by Tributyl Phosphate - n-Hexane Solvents – Part II. Nitric Acid Extraction. Nucl. Sci. Eng. 1963, 15, 354-365 (46) Davis Jr, W.; Navratil, J. D.; Lasztity, A.; Horvath, Z. In Science and Technology of Tributyl Phosphate, Schulz, W. W.; Navratil, J. D., Eds.; CRC Press: Boca Raton, 1984, pp 267-327. (47) Carter, R. L. Molecular Symmetry and Group theory; John Wiley and Sons, Inc.: Hoboken, NJ, 1997, p 299. (48) Nakamoto, K. Infrared and Raman Spectra of Inorganic and Coordination Compounds: Theory and applications in inorganic chemistry; John Wiley, 1997. (49) Walrafen, G. E. ARGON-ION-LASER-RAMAN STUDIES OF EFFECTS OF PRESSURE ON WATER STRUCTURE. Applied Spectroscopy 1968, 22, 237-253 (50) Walrafen, G. E.; Pugh, E. Raman combinations and stretching overtones from water, heavy water, and NaCl in water at shifts to ca. 7000 cm(-1). J Solution Chem 2004, 33, 81-97 (51) Carey, D. M.; Korenowski, G. M. Measurement of the Raman spectrum of liquid water. Journal of Chemical Physics 1998, 108, 2669-2675 (52) Ruas, A.; Pochon, P.; Simonin, J.-P.; Moisy, P. Nitric acid: modeling osmotic coefficients and acid-base dissociation using the BIMSA theory. Dalton T. 2010, 39, 10148-10153 (53) Minogue, N.; Riordan, E.; Sodeau, J. R. Raman Spectroscopy as a Probe of Low-Temperature Ionic Speciation in Nitric and Sulfuric Acid Stratospheric Mimic Systems. J. Phys. Chem. A 2003, 107, 4436-4444 (54) Lines, A. M.; Nelson, G. L.; Casella, A. J.; Bello, J. M.; Clark, S. B.; Bryan, S. A. Multivariate Analysis To Quantify Species in the Presence of Direct Interferents: Micro-Raman Analysis of HNO3 in Microfluidic Devices. Anal Chem 2018, 90, 2548-2554 (55) Burger, L. L. In Science and Technology of Tributyl Phosphate, Schulz, W. W.; Navratil, J. D.; Talbot, A. E., Eds.; CRC Press: Boca Raton, Florida, 1984, pp 25-67. (56) Ferraro, J. R.; Borkowski, M.; Chiarizia, R.; McAlister, D. R. FT-IR Spectroscopy of Nitric Acid in TBP/Octane Solution. Solvent Extr. Ion Exch. 2001, 19, 981-992 (57) Levitskaia, T. G.; Peterson, J. M.; Campbell, E. L.; Casella, A. J.; Peterman, D. R.; Bryan, S. A. Fourier Transform Infrared Spectroscopy and Multivariate Analysis for Online Monitoring of Dibutyl Phosphate Degradation Product in Tributyl Phosphate/nDodecane/Nitric Acid Solvent. Ind. Eng. Chem. Res. 2013, 52, 1760717617 (58) Crane, N. J.; Popescu, V.; Morris, M. D.; Steenhuis, P.; Ignelzi, M. A. Raman spectroscopic evidence for octacalcium phosphate and other transient mineral species deposited during intramembranous mineralization. Bone 2006, 39, 434-442 (59) Frost, R. L.; Čejka, J.; Ayoko, G. A.; Weier, M. A Raman spectroscopic study of the uranyl phosphate mineral bergenite. Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy 2007, 66, 979-984 (60) Rufus, A. L.; Dhanesh, M. K.; Velmurugan, S. Dissolution of synthetic uranium dibutyl phosphate (U-DBP) in sodium EDTA and sodium carbonate based formulations. Prog Nucl Energ 2017, 100, 373-379 (61) Orth, D. A.; Wallace, R. M.; Karraker, D. G. In Science and Technology of Tributyl Phosphate, Schulz, W. W.; Navratil, J. D., Eds.; CRC Press, Inc.: Boca Raton, Florida, 1984, pp 161-219. (62) Davis Jr, W. Thermodynamics of Extraction of Nitric Acid by Tri-n-Butyl Phosphate – Hydrocarbon - Diluent Solutions: I. Distribution Studies with TBP in Amsco 125-82 at Intermediate and Low Acidities. Nucl. Sci. Eng. 1962, 14, 159-168

(26) Song, H.; Ismagilov, R. F. Millisecond Kinetics on a Microfluidic Chip Using Nanoliters of Reagents. J. Am. Chem. Soc. 2003, 125, 14613-14619 (27) Sharma, B.; Frontiera, R. R.; Henry, A.-I.; Ringe, E.; Van Duyne, R. P. SERS: Materials, applications, and the future. Mater. Today 2012, 15, 16-25 (28) Mora, M. F.; Stockton, A. M.; Willis, P. A. Microchip capillary electrophoresis instrumentation for in situ analysis in the search for extraterrestrial life. Electrophoresis 2012, 33, 2624-2638 (29) Pandey, N. K.; Augustine, E.; Murali, R.; Desigan, N.; Kamachi Mudali, U.; Joshi, J. B. Kinetics of extraction of nitric acid into binary mixture of tri-n-butyl phosphate and normal paraffin hydrocarbon. Chem. Eng. Res. Des. 2016, 111, 492-503 (30) Bryan, S. A.; Levitskaia, T. G.; Casella, A. J.; Peterson, J. M.; Johnsen, A. M.; Lines, A. M.; Thomas, E. M.; Orton, C. In Advanced separation techniques for nuclear fuel reprocessing and radioactive waste treatment, Nash, K. L.; Lumetta, G. J., Eds.; Woodhead Publishing Ltd; CRC Press LLC.: Cornwall, UK, 2011. (31) Chatterjee, S.; Bryan, S. A.; Casella, A. J.; Peterson, J. M.; Levitskaia, T. G. Mechanisms of neptunium redox reactions in nitric acid solutions. Inorg Chem Front 2017, 4, 581-594 (32) Schroll, C. A.; Lines, A. M.; Heineman, W. R.; Bryan, S. A. Absorption spectroscopy for the quantitative prediction of lanthanide concentrations in the 3LiCl-2CsCl eutectic at 723 K. Anal Methods 2016, 8, 7731-7738 (33) Casella, A. J.; Levitskaia, T. G.; Peterson, J. M.; Bryan, S. A. Water O–H Stretching Raman Signature for Strong Acid Monitoring via Multivariate Analysis. Anal. Chem. 2013, 85, 4120-4128 (34) Lines, A. M.; Adami, S. R.; Sinkov, S. I.; Lumetta, G. J.; Bryan, S. A. Multivariate Analysis for Quantification of Plutonium(IV) in Nitric Acid Based on Absorption Spectra. Anal. Chem. 2017, 89, 9354-9359 (35) Stegemiller, M. L.; Heineman, W. R.; Seliskar, C. J.; Ridgway, T. H.; Bryan, S. A.; Hubler, T.; Sell, R. L. Spectroelectrochemical Sensing Based on Multimode Selectivity Simultaneously Achievable in a Single Device. 11. Design and Evaluation of a Small Portable Sensor for the Determination of Ferrocyanide in Hanford Waste Samples. Environ. Sci. Technol. 2003, 37, 123-130 (36) Maizels, M.; Stegemiller, M.; Ross, S.; Slaterbeck, A.; Shi, Y.; Ridgway, T. H.; Heineman, W. R.; Seliskar, C. J.; Bryan, S. A. In Nuclear Site Remediation; American Chemical Society, 2000, pp 364378. (37) Maizels, M.; Seliskar, C. J.; Heineman, W. R.; Bryan, S. A. Spectroelectrochemical sensing based on multimode selectivity simultaneously achievable in a single device. 10. Sensing of ferrocyanide in Hanford tank waste simulant solution. Electroanal 2002, 14, 1345-1352 (38) Casella, A. J.; Ahlers, L. R. H.; Campbell, E. L.; Levitskaia, T. G.; Peterson, J. M.; Smith, F. N.; Bryan, S. A. Development of Online Spectroscopic pH Monitoring for Nuclear Fuel Reprocessing Plants: Weak Acid Schemes. Anal. Chem. 2015, 87, 5139-5147 (39) Schroll, C. A.; Chatterjee, S.; Heineman, W. R.; Bryan, S. A. Thin‐Layer Spectroelectrochemistry on an Aqueous Microdrop. Electroanal 2012, 24, 1065-1070 (40) Schroll, C. A.; Chatterjee, S.; Heineman, W. R.; Bryan, S. A. Semi-Infinite Linear Diffusion Spectroelectrochemistry on an Aqueous Micro-Drop. Anal. Chem. 2011, 83, 4214-4219 (41) Branch, S. D.; Lines, A. M.; Lynch, J.; Bello, J. M.; Heineman, W. R.; Bryan, S. A. Optically Transparent Thin-Film Electrode Chip for Spectroelectrochemical Sensing. Anal. Chem. 2017, 89, 7324-7332 (42) Chrimes, A. F.; Khoshmanesh, K.; Stoddart, P. R.; Mitchell, A.; Kalantar-zadeh, K. Microfluidics and Raman microscopy: current applications and future challenges. Chem. Soc. Rev. 2013, 42, 58805906



10 Environment ACS Paragon Plus

Page 10 of 10

Micro-Raman technology to interrogate two phase extraction on a

Recommend Documents