Online, Real-Time Analysis of Highly Complex Processing Streams: Quantification of Analytes in Hanford Tank Sample

Development of an Attenuated Total Reflectance-Ultraviolet-Visible Probe for the Online Monitoring of Dark Solutions

Optical spectroscopy is a valuable tool for online monitoring of a variety of processes. Ultraviolet-visible (UV-vis) spectroscopy can monitor the concentration of analytes as well as identify the speciation and oxidation state. However, it can be difficult or impossible to employ UV-vis-based sensors in chemical systems that are very dark (i.e., have a high optical density), requiring exceedingly short path lengths (for transmission approaches) or an effective means of backscattering (for reflectance approaches). Examples of processes that produce highly absorbing solutions and that would benefit significantly from the diagnostic potential of optical sensors include used nuclear fuel recycling and molten salt systems with high concentrations of dissolved uranium. Utilizing an attenuated total reflectance (ATR) UV-vis approach can overcome these challenges and allow for the measurement of solutions orders of magnitude more concentrated than transmission UV-vis. However, determining ideal sensor specifications for various processes can be time-consuming and expensive. Here, we evaluate the ability of a novel ATR-UV-vis probe to measure very concentrated solutions of Co(II) and Ni(II) nitrate as well as organic dyes (methylene blue, acid red 1, and crystal violet). This sensor design provides a modular method for exploring possible "path lengths" by altering the length of the ATR fiber that was submerged within solution during spectral measurements. Measurements within the ATR sensor cell were compared to measurements gathered by transmission UV-vis of samples within a commercially available 1 cm optical cuvette. The ATR-UV-vis probe was capable of measuring absorbance of solutions with a chromophore concentration 600 times greater than that in the 1 cm cuvette. Advanced data analysis in the form of multivariate curve resolution (MCR) was used to analyze the speciation of methylene blue over a large concentration range. The application of this novel ATR-UV-vis probe to the investigation of dark solutions is a promising avenue for use in online monitoring of nuclear processes.

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

Quantification of Hydrogen Isotopes Utilizing Raman Spectroscopy Paired with Chemometric Analysis for Application across Multiple Systems

Online and real-time analysis of a chemical process is a major analytical challenge that can drastically change the way the chemical industry or chemical research operates. With in situ analyses, a new and powerful understanding of chemistry can be gained; however, building robust tools for long-term monitoring faces many challenges, including compensating for instrument drift, instrument replacement, and sensor or probe replacement. Accounting for these changes by recollecting calibration data and rebuilding quantification models can be costly and time-consuming. Here, methods to overcome these challenges are demonstrated with an application of Raman spectroscopy to monitoring hydrogen isotopes with varied speciation within dynamic gas streams. Specifically, chemical data science tools such as chemometric modeling are leveraged along with several examples of calibration transfer approaches. Furthermore, the optimization of instrument and sensor cell parameters for targeted gas-phase analyses is discussed. While the particular focus on hydrogen is highly beneficial within the nuclear energy sector, mechanisms built and demonstrated here are widely applicable to optical spectroscopy monitoring in numerous other chemical systems that can be leveraged in other processes.

Monitoring of sugars adsorption breakthrough curves with online Raman spectroscopy

We introduce a new application for online Raman spectroscopy to monitor adsorption breakthrough curves of a glucose and xylose mixtures. Univariate and multivariate Partial Least Squares (PLS) calibration models are developed for each sugar when they are dissolved in water and in the case of the ethanol addition as a cosolvent. The models are validated by performing actual breakthrough experiments in a liquid phase using a column packed with a zeolite adsorbent. The first statistical moments of predicted curves are compared to the reference curves obtained with offline High-Performance Liquid Chromatography (HPLC). Glucose and xylose univariate predictions in the presence or absence of ethanol in the mixture are accurate and no improvements are found with the PLS models. Spectral subtraction coupled with the first derivative proved to be effective pretreatments to develop robust univariate models.

Quantification of Uranium in Complex Acid Media: Understanding Speciation and Mitigating for Band Shifts

In situ and real-time analysis of chemical systems, or online monitoring, has numerous benefits in all fields of chemistry. A common challenge can be found in matrix effects, where the addition of a new chemical species causes chemical interactions and changes the fingerprints of other chemical species in the system. This is demonstrated here by looking at the Raman and visible spectra of the uranyl ion within combined nitric acid and hydrofluoric acid media. This system is not only highly important to nuclear energy, a green and reliable option for energy portfolios, but also provides a clear chemistry example that can be applied to other chemical systems. The application of optical spectroscopy is discussed, along with the application and comparison of both multivariate curve resolution and HypSpec to deconvolute and understand speciation. Finally, the use of chemical data science in the form of chemometric modeling is used to demonstrate robust quantification of uranium within a complex chemical system where potential matrix effects are not known a priori.

In Situ Raman Methodology for Online Analysis of CO2 and H2O Loadings in a Water-Lean Solvent for CO2 Capture

Carbon capture represents a key pathway to meeting climate change mitigation goals. Powerful next-generation solvent-based capture processes are under development by many researchers, but optimization and testing would be significantly aided by integrating in situ monitoring capability. Further, real-time water analysis in water-lean solvents offers the potential to maintain their water balance in operation. To explore data acquisition techniques in depth for this purpose, Raman spectra of CO2, H2O, and a single-component water-lean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA) were collected at different CO2 and H2O concentrations using an in situ Raman cell. The quantification of CO2 and H2O loadings in 2-EEMPA was done by principal component regression and partial least squares methods with analysis of uncertainties. We conclude with discussions on how this simultaneous online analysis method to quantify CO2 and H2O loadings can be an important tool to enable the optimal efficiency of water-lean CO2 solvents while also maintaining the critical water balance under operating conditions relevant to post-combustion CO2 capture.

Quantifying Dense Multicomponent Slurries with In-Line ATR-FTIR and Raman Spectroscopies: A Hanford Case Study

The multiphase nature of slurries can make them difficult to process and monitor in real time. For example, the nuclear waste slurries present at the Hanford site in Washington State are multicomponent, multiphase, and inhomogeneous. Current analytical techniques for analyzing radioactive waste at Hanford rely on laboratory results from an on-site analytical laboratory, which can delay processing speed and create exposure risks for workers. However, in-line probes can provide an alternative route to collect the necessary composition information. In the present work, Raman spectroscopy and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy are tested on simulants of nuclear waste slurries containing up to 23.2 wt % solids. We observe ATR-FTIR spectroscopy to be effective in measuring the solution phase of the studied slurry systems (3.52% mean percent error), while Raman spectroscopy provides information about the suspended solids in the slurry system (18.21% mean percent error). In-line measurement of multicomponent solids typical of nuclear waste processing has been previously unreported. The composition of both the solution and solid phases is vital in ensuring stable glass formulation and effective disposal of nuclear waste at Hanford. Raman and ATR-FTIR spectroscopies can provide a safer and faster alternative for acquiring compositional information on nuclear waste slurries.

Development of Online pH Monitoring for Lactic, Malonic, Citric, and Oxalic Acids Based on Raman Spectroscopy Using Hierarchical Chemometric Modeling

Online spectroscopic measurements can be used to provide unique insight into complex chemical systems, enabling new understanding and optimization of chemical processes. A key example of this is discussed here with the monitoring of pH of various acid systems in real-time. In this work the acids used in multiple chemical separations processes, such as TALSPEAK (Trivalent Actinide-Lanthanide Separation by Phosphorus reagent Extraction from Aqueous Komplexes) and oxalate precipitation, were characterized. Raman spectroscopy, a robust optical approach that can be integrated in corrosive processes, was used to follow the unique fingerprints of the various protonated and deprotonated acid species. This data was analyzed using a hierarchical modeling approach to build a consolidated model scheme using optical fingerprints from all weak acids to measure pH associated with any of the weak acid systems studied here. Validation of system performance included utilizing Raman spectroscopy under dynamic flow conditions to monitor solution pH under changing process conditions in-line. Overall, the Raman based approach provided accurate analysis of weak acid solution pH.

Combined Raman and Turbidity Probe for Real-Time Analysis of Variable Turbidity Streams

Real-time and in situ process monitoring is a powerful tool that can empower operators of hazardous processes to better understand and control their chemical systems without increased risk to themselves. However, the application of monitoring techniques to complex chemical processes can face challenges. An example of this is the application of optical spectroscopy, otherwise capable of providing detailed chemical composition information, to processes exhibiting variable turbidity. Here, details on a novel combined Raman spectroscopy and turbidimetry probe are discussed, which advances current technology to enable flexible and robust in situ monitoring of a flowing process stream. Furthermore, the analytical approach to accurately account for both Raman signal and turbidity while quantifying chemical targets is detailed. This new approach allows for accurate analysis without requiring assumptions of stable process chemistry, which may be unlikely in applications such as waste cleanup. Through leveraging Raman and turbidity data simultaneously collected from the combined probe within chemometric models, accurate quantification of multiple chemical targets can be achieved under conditions of variable concentrations and turbidity.

Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet-Visible Spectra

Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV-Vis absorbance of neodymium (Nd³⁺) in the presence of interferents, erbium (Er³⁺) and copper (Cu²⁺) under conditions simulating the liquid-liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. The selected chemometric model, partial least squares regression, accurately quantifies Nd³⁺ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.

On-Line Raman Measurement of the Radiation-Enhanced Reaction of Cellobiose with Hydrogen Peroxide

Production of a chemical feedstock as a secondary product from a commercial nuclear reactor can increase the economic viability of the reactor and enable the deployment of nuclear energy as part of the low-carbon energy grid. Currently, commercial nuclear reactors produce underutilized energy in the form of neutrons and gamma photons. This excess energy can be exploited to drive chemical reactions, increasing the fraction of utilized energy in reactors and providing a valuable secondary product from the reactor. Gamma degradation of cellulosic biomass has been studied previously. However, real-time, on-line monitoring of the breakdown of biomass materials under gamma radiation has not been demonstrated. Here, we demonstrate on-line monitoring of the reaction of cellobiose with hydrogen peroxide under gamma radiation using Raman spectroscopy, providing in situ quantification of organic and inorganic system components.

Quantification of Raman-Interfering Polyoxoanions for Process Analysis: Comparison of Different Chemometric Models and a Demonstration on Real Hanford Waste

The Hanford site represents a complicated environmental remediation challenge, remaining from the production of nuclear weapons. Over 100 million gallons of liquid radioactive waste of unknown composition will be chemically processed and vitrified, but the varying chemical composition and highly radioactive nature of the waste preclude the implementation of more developed, offline technologies to determine the composition. The only practical approach to waste treatment will require the significant utilization of real-time, chemometric modeling approaches. Although chemometric approaches have been applied to the analysis of Hanford waste, the models developed were highly tank-specialized, and limited discussion was provided on how models fared with interfering signals. As the tank waste is largely composed of oxoanions, which tend to have interfering Raman spectra, the general question was posed as to what chemometric approach is best suited to accurately quantify analytes in the presence of interfering signals. This was carried out by examining the ability of classical least square (CLS), principal component regression (PCR), partial least square (PLS), and locally weighted regression (LWR) to quantify NO₃^- and CO₃^2- using their bands around 1050 cm^-1. For all samples, the PLS-based model was found to be the most efficient approach from a model building and application perspective.

Raman Spectroscopy Coupled with Chemometric Analysis for Speciation and Quantitative Analysis of Aqueous Phosphoric Acid Systems

Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize online and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer's law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as the pH is varied. Locally weighted regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with multivariate curve resolution modeling, provide a direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations, to compensate for activity coefficients and nonidealities associated with high ionic strength systems.

On-Line Monitoring of Gas-Phase Molecular Iodine Using Raman and Fluorescence Spectroscopy Paired with Chemometric Analysis

Molten salt reactors (MSRs) have the potential to safely support green energy goals while meeting baseload energy needs with diverse energy portfolios. While reactor designers have made tremendous strides with these systems, licensing and deployment of these reactors will be aided through the development of new technology such as on-line and remote monitoring tools. Of particular interest is quantifying reactor off-gas species, such as iodine, within off-gas streams to support the design and operational control of off-gas treatment systems. Here, the development of advanced Raman spectroscopy systems for the on-line analysis of gas composition is discussed, focusing on the key control species I_2(g). Signal response was explored with two Raman instruments, utilizing 532 and 671 nm excitation sources, as a function of I_2(g) pressure and temperature. Also explored is the integration of advanced data analysis methods to enable real-time and highly accurate analysis of complex optical data. Specifically, the application of chemometric modeling is discussed. Raman spectroscopy paired with chemometric analysis is demonstrated to provide a powerful route to analyzing I_2(g) composition within the gas phase, which lays the foundation for applications within molten salt reactor off-gas analysis and other significant chemical processes producing iodine species.

Enabling Microscale Processing: Combined Raman and Absorbance Spectroscopy for Microfluidic On-Line Monitoring

Microfluidics have many potential applications including characterization of chemical processes on a reduced scale, spanning the study of reaction kinetics using on-chip liquid-liquid extractions, sample pretreatment to simplify off-chip analysis, and for portable spectroscopic analyses. The use of in situ characterization of process streams from laboratory-scale and microscale experiments on the same chemical system can provide comprehensive understanding and in-depth analysis of any similarities or differences between process conditions at different scales. A well-characterized extraction of Nd(NO₃)₃ from an aqueous phase of varying NO_{3^- (aq)} concentration with tributyl phosphate (TBP) in dodecane was the focus of this microscale study and was compared to an earlier laboratory-scale study utilizing counter current extraction equipment. Here, we verify that this same extraction process can be followed on the microscale using spectroscopic methods adapted for microfluidic measurement. Concentration of Nd (based on UV-vis) and nitrate (based on Raman) was chemometrically measured during the flow experiment, and resulting data were used to determine the distribution ratio for Nd. Extraction distributions measured on the microscale were compared favorably with those determined on the laboratory scale in the earlier study. Both micro-Raman and micro-UV-vis spectroscopy can be used to determine fundamental parameters with significantly reduced sample size as compared to traditional laboratory-scale approaches. This leads naturally to time, cost, and waste reductions.

Absolute Band Intensity of the Iodine Monochloride Fundamental Mode for Infrared Sensing and Quantitative Analysis

Iodine monochloride (ICl) is a potential off-gas product of molten salt reactors; monitoring this heteronuclear diatomic molecule is of great interest for both environmental and safety purposes. In this paper, we investigate the possibility of infrared monitoring of ICl by measuring the far-infrared absorption cross section of its fundamental band near 381 cm^-1. We have performed quantitative studies of the neat gas in a 20 cm cell at 25, 35, 50, and 70 °C at multiple pressures up to ∼9 Torr and investigated the temperature and pressure dependencies of the band's infrared cross section. Quantitative measurements were problematic due to sample adhesion to the cell walls and windows as well as reactions/possible hydrolysis of ICl to form HCl gas. Effects were mitigated by measuring only the neat gas, using short measurement times, and subtracting out the partial pressure of the HCl(g). The integrated band strength is shown to be temperature independent and was found to be equal to 9.1 × 10^-19 (cm²/molecule) cm^-1. As expected, the temperature dependence of the band profile showed only a small effect over this limited temperature range. We have also investigated using the absorption data along with inverse least squares multivariate methods for the quantitative monitoring of ICl effluent concentrations under different scenarios using infrared (standoff) sensing and compare these results with traditional Beer's law (univariate) techniques.

Sensor Fusion: Comprehensive Real-Time, On-Line Monitoring for Process Control via Visible, Near-Infrared, and Raman Spectroscopy

On-line monitoring based on optical spectroscopy provides unprecedented insight into the chemical composition of process streams or batches. Amplifying this approach through utilizing multiple forms of optical spectroscopy in sensor fusion can greatly expand the number and type of chemical species that can be identified and quantified. This is demonstrated herein, on the analysis of used nuclear fuel recycling streams: highly complex processes with multiple target and interfering analytes. The optical techniques of visible absorbance, near-infrared absorbance, and Raman spectroscopy were combined to quantify plutonium(III, IV, VI), uranium(IV, VI), neptunium(IV, V, VI), and nitric acid. Chemometric modeling was used to quantify analytes in process streams in real time, and results were successfully used to enable immediate process control and generation of a product stream at a set composition ratio. This represents a significant step forward in the ability to monitor and control complex chemical processes occurring in harsh chemical environments.

Review of on-line and near real-time spectroscopic monitoring of processes relevant to nuclear material management

Spectroscopic chemometric based on-line monitoring of used nuclear fuel (UNF) reprocessing solutions and characterization of legacy nuclear waste (LNW) stored at Hanford is discussed in this manuscript. Utilizing on-line and near real-time monitoring, as opposed to traditional off-line monitoring, can significantly reduce the cost, risk and improve the efficiency of characterizing UNF and LNW processing streams. Specifically, this manuscript will highlight the benefits of spectroscopy-based monitoring approaches, which generally include the ability to collect data non-destructively. Furthermore, significant literature precedence supports the use of various real-time analysis methods, including chemometric analysis, that enable near-instantaneous conversion of spectroscopic data into information useable by process operators. This approach can accurately quantify and qualify nuclear material in near-real time enabling immediate condition characterization and potential diversion detection within UNF reprocessing streams and LNW. The ability to be applied in a real reprocessing plant and in an actual Hanford waste tank/transfer pipe has been demonstrated by applying this technique to accurately quantify analytes in real UNF streams and LNW samples. The future development of spectroscopy-based on-line monitoring is also discussed in this manuscript.

Reimagining pH Measurement: Utilizing Raman Spectroscopy for Enhanced Accuracy in Phosphoric Acid Systems

Measurement of pH is an integral component of chemical studies and process control; however, traditional pH probes are difficult to utilize in harsh or complex chemical systems. Optical spectroscopy-based online monitoring offers a powerful and novel route for characterizing system parameters, such as pH, and is well adapted to deployment in harsh environments or chemically complex systems. Specifically, Raman spectroscopy combined with chemometric analysis can provide an improved method of online p[H⁺] measurement. Multivariate curve resolution (MCR) analysis of Raman spectra can be utilized to determine speciation as a function of p[H⁺], and the MCR scores assigned to each species can be used to calculate p[H⁺]. Subsequent chemometric modeling can be used to correlate spectral response to p[H⁺]. This was demonstrated with phosphoric acid, a chemical system known to challenge traditional pH probes. Raman spectra exhibit clear changes with pH due to changing speciation, and chemometric modeling can be successfully utilized to correlate those fingerprints to p[H⁺]. With the use of this approach, p[H⁺] of the phosphoric acid system can be accurately measured without foreknowledge of system conditions such as ionic strength.