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

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.

Quantification of Lanthanides on a PMMA Microfluidic Device with Three Optical Pathlengths Using PCR of UV-Visible, NIR, and Raman Spectroscopy

Microfluidic devices (MFDs) offer customizable, low-cost, and low-waste platforms for performing chemical analyses. Optical spectroscopy techniques provide nondestructive monitoring of small sample volumes within microfluidic channels. Optical spectroscopy can probe speciation, oxidation state, and concentration of analytes as well as detect counterions and provide information about matrix composition. Here, ultraviolet-visible (UV-vis) absorbance, near-infrared (NIR) absorbance, and Raman spectroscopy are utilized on a custom poly(methyl methacrylate) (PMMA) MFD for the detection of three lanthanide nitrates in solution. Absorbance spectroscopies are conducted across three pathlengths using three portions of a contiguous channel within the MFD. Univariate and chemometric multivariate modeling, specifically Beer's law regression and principal component regression (PCR), respectively, are utilized to quantify the three lanthanides and the nitrate counterion. Models are composed of spectra from one or multiple pathlengths. Models are also constructed from multiblock spectra composed of UV-vis, NIR, and Raman spectra at one or multiple pathlengths. Root-mean-square errors (RMSE), limit of detection (LOD), and residual predictive deviation (RPD) values are compared for univariate, multivariate, multi-pathlength, and multiblock models. Univariate modeling produces acceptable results for analytes with a simple signal, such as samarium cations, producing an LOD of 5.49 mM. Multivariate and multiblock models produce enhanced quantification for analytes that experience spectral overlap and interfering nonanalyte signals, such as holmium, which had an LOD reduction from 7.21 mM for the univariate model down to 3.96 mM for the multiblock model. Multi-pathlength models are developed that maintain model errors in line with single-pathlength models. Multi-pathlength models have RPDs from 9.18 to 46.4, while incorporating absorbance spectra collected at optical paths of up to 10-fold difference in length.

Aerogel-Lined Capillaries as Liquid-Core Waveguides for Raman Signal Gain of Aqueous Samples: Advanced Manufacturing and Performance Characterization

An advanced process for the manufacturing of aerogel-lined capillaries is presented; these are applicable as liquid-core waveguides for gaining the Raman signal of aqueous samples. With respect to the spin-coating process we have used so far for the manufacturing of aerogel-lined capillaries, the here-presented manufacturing process is advanced as it enables (i) the lining of longer capillaries, (ii) the adjustment of the lining-thickness via the lining velocity, and (iii) the reproducible generation of crack-free linings. The key parameters of the advanced process and their effect on the fabrication of aerogel-lined capillaries with optimal Raman signal gain are reported and related to the thickness and topography of the aerogel linings by the support of scanning electron microscopy.

Raman spectroscopy - a visit to the literature on plant, food, and agricultural studies

Raman spectroscopy, a fast, non-invasive, and label-free optical technique, has significantly advanced plant and food studies and precision agriculture by providing detailed molecular insights into biological tissues. Utilizing the Raman scattering effect generates unique spectral fingerprints that comprehensively analyze tissue composition, concentration, and molecular structure. These fingerprints are obtained without chemical additives or extensive sample preparation, making Raman spectroscopy particularly suitable for in-field applications. Technological enhancements such as surface-enhanced Raman scattering, Fourier-transform-Raman spectroscopy, and chemometrics have increased Raman spectroscopy sensitivity and precision. These and other advancements enable real-time monitoring of compound translocation within plants and improve the detection of chemical and biological contaminants, essential for food safety and crop optimization. Integrating Raman spectroscopy into agronomic practices is transformative and marks a shift toward more sustainable farming activities. It assesses crop quality - as well as the quality of the food that originated from crop production - early plant stress detection and supports targeted breeding programs. Advanced data processing techniques and machine learning integration efficiently handle complex spectral data, providing a dynamic and detailed view of food conditions and plant health under varying environmental and biological stresses. As global agriculture faces the dual challenges of increasing productivity and sustainability, Raman spectroscopy stands out as an indispensable tool, enhancing farming practices' precision, food safety, and environmental compatibility. This review is intended to select and briefly comment on outstanding literature to give researchers, students, and consultants a reference for works of literature in Raman spectroscopy mainly focused on plant, food, and agronomic sciences. © 2024 Society of Chemical Industry.

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.

A review of SERS coupled microfluidic platforms: From configurations to applications

Microfluidic systems have attracted considerable attention due to their low reagent consumption, short analysis time, and ease of integration in comparison to conventional methods, but still suffer from shortcomings in sensitivity and selectivity. Surface enhanced Raman scattering (SERS) offers several advantages in the detection of compounds, including label-free detection at the single-molecule level, and the narrow Raman peak width for multiplexing. Combining microfluidics with SERS is a viable way to improve their detection sensitivity. Researchers have recently developed several SERS coupled microfluidic platforms with substantial potential for biomolecular detection, cellular and bacterial analysis, and hazardous substance detection. We review the current development of SERS coupled microfluidic platforms, illustrate their detection principles and construction, and summarize the latest applications in biology, environmental protection and food safety. In addition, we innovatively summarize the current status of SERS coupled multi-mode microfluidic platforms with other detection technologies. Finally, we discuss the challenges and countermeasures during the development of SERS coupled microfluidic platforms, as well as predict the future development trend of SERS coupled microfluidic platforms.

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0-100 μg mL-1), europium (0-150 μg mL-1), samarium (0-250 μg mL-1), praseodymium (0-350 μg mL-1), neodymium (0-1000 μg mL-1), and HNO3 (2-4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet-visible-near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9-5.7% for the seven factors. The optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

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.

Online Quantitative Analysis of Chlorine Contents in Chlorinated Paraffins by Facile Raman Spectroscopy

Online analysis of industrial chemicals is extremely important for managing product quality and performance. The chlorine (Cl) content is one of the most important technical metrics for chlorinated paraffins (CPs), and the conventional approaches to estimate Cl contents require transforming the Cl element to chloride followed by quantitative analysis with either titration or instrumentation, which are normally tedious and time-consuming and cannot simultaneously guide the industrial production. Here, we developed a rapid, real-time, and online approach to determine the Cl content of CPs with facile Raman spectroscopy. The chlorination of paraffins generated two new Raman peaks at 610-618 and 668-690 cm^-1, which are associated with the vibrational modes of the S_HH and S_HC conformations of the C-Cl bond in CPs, respectively. More importantly, the corresponding peak of the S_HH conformation decreased and that of the S_HC conformation increased with the enhancement of the chlorination degree of CPs. The ratiometric calculation of the two respective Raman peak areas leads to a quantitative analysis of the Cl content of CPs. The developed approach can online provide the Cl contents of CPs within seconds accurately but without the tedious sample treatment required by conventional approaches. The strategy of integrating Raman analysis with the industrial pipeline will help in managing the production and quality control of industrial chemicals.

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.

Iodine and Carbonate Species Monitoring in Molten NaOH-KOH Eutectic Scrubber via Dual-Phase In Situ Raman Spectroscopy

Molten hydroxide scrubbing of off-gas vapors is a potential process to improve safety during the operation of generation IV molten salt nuclear reactors (MSRs). MSRs produce off-gases that can be vented by the reactor core and treated via off-gas scrubbers. Molten hydroxide scrubbers focus on capturing volatile iodine radionuclides, and they can also be used to capture aerosols and particulates and to neutralize acidic species. The performance of these scrubbers depends on the chemical interactions of the scrubbing medium with the off-gas species. Knowledge of the concentration and speciation of scrubbed or target species, as well as process and environmental interferents, can enable advanced operation of MSR off-gas treatment systems. Optical online monitoring is an excellent technology to provide this information in real time, while limiting the need for operators to interact with radioactive samples through hands-on interrogation. Raman spectroscopy can provide crucial chemical information on the state of the molten eutectic during treatment in the molten phase, as well as the gas phase. In this work, Raman spectroscopy is used to detect iodine species, specifically iodate, in the molten phase of a NaOH-KOH eutectic and to construct a calibration curve of the Raman signal of those species. Additionally, a carbonate interferent is followed from the gas phase to the liquid phase as a basis for reaching a Raman-aided mass balance of the molten hydroxide eutectic scrubber system.

Microfluidic In-Situ Spectrophotometric Approaches to Tackle Actinides Analysis in Multiple Oxidation States

The study and development of present and future processes for the treatment/recycling of spent nuclear fuels require many steps, from design in the laboratory to setting up on an industrial scale. In all of these steps, analysis and instrumentation are key points. For scientific reasons (small-scale studies, control of phenomena, etc.) but also with regard to minimizing costs, risks, and waste, such developments are increasingly carried out on milli- or microfluidic devices. The logic is the same for the chemical analyses associated with their follow-up and interpretation. Due to this, over the last few years, opto-microfluidic analysis devices adapted to the monitoring of different processes (dissolution, liquid-liquid extraction, precipitation, etc.) have been increasingly designed and developed. In this work, we prove that photonic lab-on-a-chip (PhLoC) technology is fully suitable for all actinides concentration monitoring along the plutonium uranium refining extraction (plutonium, uranium, reduction, extraction, or Purex) process. Several PhLoC microfluidic platforms were specifically designed and used in different nuclear research and development (R&D) laboratories, to tackle actinides analysis in multiple oxidation states even in mixtures. The detection limits reached (tens of µmol·L^-1) are fully compliant with on-line process monitoring, whereas a range of analyzable concentrations of three orders of magnitude can be covered with less than 150 µL of analyte. Finally, this work confirms the possibility and the potential of coupling Raman and ultraviolet-visible (UV-Vis) spectroscopies at the microfluidic scale, opening the perspective of measuring very complex mixtures.

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.

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.