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.

Application of Spectroscopy Techniques for Monitoring (Bio)Catalytic Processes in Continuously Operated Microreactor Systems

In the last twenty years, the application of microreactors in chemical and biochemical industrial processes has increased significantly. The use of microreactor systems ensures efficient process intensification due to the excellent heat and mass transfer within the microchannels. Monitoring the concentrations in the microchannels is critical for a better understanding of the physical and chemical processes occurring in micromixers and microreactors. Therefore, there is a growing interest in performing in-line and on-line analyses of chemical and/or biochemical processes. This creates tremendous opportunities for the incorporation of spectroscopic detection techniques into production and processing lines in various industries. In this work, an overview of current applications of ultraviolet–visible, infrared, Raman spectroscopy, NMR, MALDI-TOF-MS, and ESI-MS for monitoring (bio)catalytic processes in continuously operated microreactor systems is presented. The manuscript includes a description of the advantages and disadvantages of the analytical methods listed, with particular emphasis on the chemometric methods used for spectroscopic data analysis.

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.

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.

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.

A colorimetric chemosensor for pyrophosphate based on mono-pyrenylurea in aqueous media

Research on pyrophosphate ions detection remains important because it plays crucial roles in various fields. A simple and new colorimetric sensor for pyrophosphate (PPi) based on mono-pyrenylurea ligand (L) has been designed and synthesized by a simple reaction of 1-pyrenemethylamine hydrochloride with p-nitrophenylisocyanate. In DMSO-15% H₂O solution and DMSO-15% HEPES (10 mM, pH = 7.2) buffer solution, L displayed a selective colorimetric response for pyrophosphate (PPi) against other anions by changing color from colorless to yellow. This recognition process was confirmed by UV-vis spectroscopy. Also, the colorimetric properties of L are attributed to the anion-induced deprotonation of the urea subunit as demonstrated by ¹H NMR titration method. Moreover, convenient test strips coated with L could be utilized to detect PPi in aqueous solution by naked-eye.

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.

Nanoplastic Analysis by Online Coupling of Raman Microscopy and Field-Flow Fractionation Enabled by Optical Tweezers

Nanoplastic pollution is an emerging environmental concern, but current analytical approaches are facing limitations in this size range. However, the coupling of nanoparticle separation with chemical characterization bears potential to close this gap. Here, we realize the hyphenation of particle separation/characterization (field-flow fractionation (FFF), UV, and multiangle light scattering) with subsequent chemical identification by online Raman microspectroscopy (RM). The problem of low Raman scattering was overcome by trapping particles with 2D optical tweezers. This setup enabled RM to identify particles of different materials (polymers and inorganic) in the size range from 200 nm to 5 μm, with concentrations in the order of 1 mg/L (10⁹ particles L^-1). The hyphenation was realized for asymmetric flow FFF and centrifugal FFF, which separate particles on the basis of different properties. This technique shows potential for application in nanoplastic analysis, as well as many other fields of nanomaterial characterization.

Online Monitoring of Solutions Within Microfluidic Chips: Simultaneous Raman and UV-Vis Absorption Spectroscopies

Microfluidics is an appealing analytical tool in the global effort to close the nuclear fuel cycle. Using a microfluidic chip permits the analysis of greatly reduced sample volumes compared to what is necessary for traditional analytical methods. There is a commensurate reduction in disposal volume and cost. The development of novel sensors is necessary to take full advantage of the microchip configuration, where optical-spectroscopy-based approaches offer a powerful route to characterize chemical composition. This study uses simultaneously applied UV-vis and micro-Raman spectroscopies adapted to function on the microscale to analyze in situ both the Nd³⁺ (UV-vis-active) and HNO₃ (Raman-active) concentrations in the same sample. An adjustable translation platform was designed to hold the micro-Raman probe above and perpendicular to the chip face and the UV-vis probe in the plane of the chip. These complimentary spectral techniques when processed through multivariate partial least-squares (PLS) models gave an accurate picture of the widely varying solution concentrations as a function of time for each solution component. Solution matrix effects can drastically alter analyte signatures as measured by both UV-vis absorbance and Raman spectroscopy. PLS methods successfully modeled these spectral changes and accurately measured concentrations of components of interest within the microfluidic chip.

Visual detection of cyanide ion in aqueous medium by a new chromogenic azo-azomethine chemosensor

A simple and new chromogenic azo-azomethine chemosensor N'-(5-((2,4-dichloro- phenyl) diazenyl)-2-hydroxylbenzylidene) picolinohydrazide (L) has been synthesized as an effective colorimetric sensor for cyanide ion. The sensing behavior of the probe L towards CN^- over other anions was examined by naked-eye, UV-vis spectroscopy and NMR studies. L exhibited a selective sensing ability to CN^- in DMSO/H₂O(6:4, v:v) binary solution and DMSO/Tris(10 mM, pH = 7.1, 6:4, v:v) buffer solution by changing color from colorless to yellow. The detection limit was calculated to be 6.4 μM. The recognition mechanism was attributed to deprotonation process according to ¹H NMR titration method. Moreover, test strips coated with L were easily fabricated with low cost and could be used to detect CN^- in aqueous solution conveniently.