Nuclear energy is a promising low-carbon energy candidate to meet the increased demand for green energy, where the integration of fuel recycling can have significant benefits for material usage and waste reduction. Utilizing in situ monitoring tools can provide ample opportunities to better control and safeguard nuclear material recycle processes while also offering knowledge and insight into real-time solution properties. The simultaneous measurement of analytical targets in multiple process locations can enable real-time mass balance and material accountancy calculations. This is demonstrated here with a mass balance study of Nd3+ on countercurrent aqueous/organic metal extraction within a single centrifugal contactor. The Nd3+ concentration was simultaneously monitored at the inlets and outlets of both aqueous and organic phases using a visible absorbance detector that allowed for the simultaneous measurement of up to six locations. The Nd3+ concentration was calculated by using chemical data science algorithms, where model training sets were collected on a single track of the detector. The discussion includes addressing the challenges of using a model collected on a single track and applying it as a model across the other tracks on the detector. Each track of the detector corresponds to one measurement location on the contactor. The difference in the integrated moles of Nd3+ between the inlet and outlet at the end of the experiment was near zero, indicating that the mass balance of this experiment was maintained. Overall, the online spectroscopic monitoring was able to follow changing solution conditions and accurately measure the concentration of Nd3+ in different locations within the contactor system.

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.

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.

During process monitoring applications, referenced optical spectroscopy, such as absorbance spectroscopy, can suffer from environmental and instrumental fluctuations that alter the intensity of irradiance reaching the spectrometer's detector at each detected frequency. Temperature, vibration, light source aging, instrument damage, detector aging, detector registry shifts, sampling cell degradation, and similar perturbations create situations in which a previously collected reference spectrum may no longer be valid for the current state of the system. This can lead to the calculation of poor-quality absorbance spectra that are unsuitable for qualitative or quantitative analysis based on prior calibration models. The use of single-beam spectra in the creation of multivariate calibration models circumvents the need for collecting and maintaining a stable reference spectrum throughout an ongoing chemical process. However, unlike absorbance spectra, which typically have a zero baseline, single-beam spectra contain a high background signal relative to an analyte signal, and they may also contain intense peaks from the light source. Here, multivariate principal component analysis (PCA) and partial least squares (PLS) regression models are built using single-beam and absorbance spectra to compare the efficacy of both types of spectra for qualitative and quantitative analyses of lanthanide solutions. A multileg fiber optic UV-visible spectrometer is utilized to collect samples under three distinct wavelength registries in three unique sampling cells and under lighting conditions spanning 0.2 to 2.0 relative transmittance. Under these conditions, single-beam spectral PCA models produced enhanced discrimination between sampling conditions, allowing spectra to be grouped by the instrumental conditions under which they were collected. Absorbance and single-beam PLS models produced equivalent quantitations of the lanthanide concentrations.

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least-squares (CLS), principal component regression (PCR), and partial least-squares (PLS), as well as the univariate Beer's law method have been described and compared, building students' understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data are described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understand how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprising 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene, and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown data set. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supporting Information and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The data sets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own data sets into MATLAB and performing CLS, PCR, and PLS on their data.

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.

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, which can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this; here, this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671, 532, and 405 nm excitation wavelengths. Generally, limits of detection decrease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

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.

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.

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 NO3-((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.

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.

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.

Microfluidics offer novel and state-of-the-art pathways to process materials. Microfluidic systems drastically reduce timeframes and costs associated with traditional lab-scale efforts in the area of analytical sample preparations. The challenge arises in effectively connecting microfluidics to off-chip analysis tools to accurately characterize samples after treatment on-chip. Fabrication of a chip-to-world connection includes one end of a fused silica capillary interfaced to the outlet of a microfluidic device (MFD). The other end of the capillary is connected to a commercially available CEI-100 interface that passes samples into an inductively coupled plasma mass spectrometer (ICP-MS). This coupling creates an inexpensive and simple chip-to-world connection that enables on-chip and off-chip methods of analyzing the separation of rare earth elements. Specifically, this is demonstrated by utilizing isotachophoresis (ITP) on a microfluidic chip to separate up to 14 lanthanides from a homogenous sample into elementally pure bands. The separated analyte zones are successfully transferred across a 7 nL void volume at the microchip-capillary junction, such that separation resolution is maintained and even increased through the interface and into the ICP-MS, where the elemental composition of the sample is analyzed. Lanthanide samples of varying composition are detected using ICP-MS, demonstrating this versatile and cost-effective approach, which maintains the separation quality achieved on the MFD. This simple connection enables fast, low-cost sample preparation immediately prior to injection into an ICP-MS or other analytical instrument.

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.

limited by the approximate Radiation Boundary Conditions (RBC's) used to model the radiation into an infinite space. Improved RBC's were researched, developed, and incorporated into the existing EMSolve finite-element code to provide a 10-100x improvement in the accuracy of the boundary conditions. Section I provides an introduction to the project and the project goals. Section II provides a summary of the project's research and accomplishments as presented in the attached papers.

Elemental analysis of rare earth elements is essential in a variety of fields including environmental monitoring and nuclear safeguards; however, current techniques are often labor intensive, time consuming, and/or costly to perform. The difficulty arises in preparing samples, which requires separating the chemically and physically similar lanthanides. However, by transitioning these separations to the microscale, the speed, cost, and simplicity of sample preparation can be drastically improved. Here, all fourteen non‐radioactive lanthanides (lanthanum through lutetium minus promethium) are separated by ITP for the first time in a serpentine fused‐silica microchannel (70 µm wide × 70 µm tall × 33 cm long) in <10 min at voltages ≤8 kV with limits of detection on the order of picomoles. This time includes the 2 min electrokinetic injection time at 2 kV to load sample into the microchannel. The final leading electrolyte consisted of 10 mM ammonium acetate, 7 mM α‐hydroxyisobutyric acid, 1% polyvinylpyrrolidone, and the final terminating electrolyte consisted of 10 mM acetic acid, 7 mM α‐hydroxyisobutyric acid, and 1% polyvinylpyrrolidone. Electrophoretic electrodes are embedded in the microchip reservoirs so that voltages can be quickly applied and switched during operation. The limits of detection are quantified using a commercial capacitively coupled contactless conductivity detector (C4D) to calculate ITP zone lengths in combination with ITP theory. Optimization of experimental procedures and reproducibility based on statistical analysis of subsequent experimental results are addressed. Percent error values in band length and conductivity are ≤8.1 and 0.37%, respectively.