Data Fusion of Acoustic and Optical Emission from Laser-Induced Plasma for In Situ Measurement of Rare Earth Elements in Molten LiCl-KCl.

Molten salts have a significant potential for use as next-generation nuclear reactor coolants and in pyroprocessing for the recycling of used nuclear fuel. However, the molten salt composition needs to be known at all times, and high temperatures and intense ionizing radiation pose challenges for the monitoring instrumentation. Although the technique of laser-induced breakdown spectroscopy (LIBS) has been studied for in situ measurements of molten salts, trials to improve its monitoring accuracy using chemometrics are lacking. In this study, a data fusion technique using the LIBS optical and laser-induced acoustic (LIA) signals was investigated to enhance the measurement accuracy for molten salt monitoring. Prediction models were constructed using the partial least-squares method, and the variable importance in projection scores was analyzed to evaluate the effect of incorporating the LIA signal into the analysis. This study investigates rare earth elements Eu, Er, and Pr found not only in nuclear but also in other settings such as laser and magnetic materials. The analysis of LIBS data without data fusion resulted in a root-mean-square error of prediction (RMSEP) of 0.0774-0.0913 wt %, whereas the prediction model using data fusion led to approximately 18-40% enhanced RMSEP (0.0461-0.0679 wt %). The results suggest that fusing the LIBS data with the simultaneously recorded LIA data can improve the monitoring accuracy of rare earth element composition in molten salts.

Impact of Glass Irradiation on Laser-Induced Breakdown Spectroscopy Data Analysis.

Increased absorption of optical materials arising from exposure to ionizing radiation must be accounted for to accurately analyze laser-induced breakdown spectroscopy (LIBS) data retrieved from high-radiation environments. We evaluate this effect on two examples that mimic the diagnostics placed within novel nuclear reactor designs. The analysis is performed on LIBS data measured with 1% Xe gas in an ambient He environment and 1% Eu in a molten LiCl-KCl matrix, along with the measured optical absorption from the gamma- and neutron-irradiated low-OH fused silica and sapphire glasses. Significant changes in the number of laser shots required to reach a 3σ detection level are observed for the Eu data, increasing by two orders of magnitude after exposure to a 1.7 × 1017 n/cm2 neutron fluence. For all cases examined, the spectral dependence of absorption results in the introduction of systematic errors. Moreover, if lines from different spectral regions are used to create Boltzmann plots, this attenuation leads to statistically significant changes in the temperatures calculated from the Xe II lines and Eu II lines, lowering them from 8000 ± 610 K to 6900 ± 810 K and from 15,800 ± 400 K to 7200 ± 800 K, respectively, for exposure to the 1.7 × 1017 n/cm2 fluence. The temperature range required for a 95% confidence interval for the calculated temperature is also broadened. In the case of measuring the Xe spectrum, these effects may be mitigated using only the longer-wavelength spectral region, where radiation attenuation is relatively small, or through analysis using the iterative Saha-Boltzmann method.

Machine learning-assisted laser-induced breakdown spectroscopy for monitoring molten salt compositions of small modular reactor fuel under varying laser focus positions.

Next-generation advanced nuclear reactors based on molten salts are interested to apply machine learning (ML) technology to minimize human error and realize effective autonomous operation. Owing to harsh environments with limited access to molten salts, laser-induced breakdown spectroscopy (LIBS) has been investigated as a possible option for remote online monitoring. However, the height of molten salts is easily fluctuated by vibration. In addition, the level of molten salts could change during normal operation through the insertion of a controlling structure. While these uncertainties should be considered, their effects have not been studied yet. In this study, LIBS has been actively coupled with ML to automate the online monitoring of difficult-to-access molten salt systems. To practically apply a prediction model with ML, we intentionally defocus the measurement by manipulating the sample position. This study investigates the focusing and defocusing spectra of Sr and Mo as fission products for constructing the two prediction models using partial least squares and artificial neural network methods. For each method, the prediction models trained with focusing spectra only or focusing and defocusing spectra simultaneously are constructed and compared to each other. While the prediction model using only focusing spectra resulted in a root mean square error of prediction (RMSEP) of 0.1943-0.2175 wt%, a prediction model using both spectra led to approximately 10 times enhanced RMSEP (0.0210-0.0316 wt%). This study implies that not only focusing data but also defocusing data are needed to construct the prediction model while considering its practical usage in a real system, especially in the complex processes of the nuclear industry.

Spectroscopic Study into Lanthanide Speciation in Deep Eutectic Solvents.

Deep eutectic solvents are a new class of green solvents that are being explored as an alternative for used nuclear fuel and critical material recycling. However, there is a paucity of knowledge regarding metal behavior in them. This paper explores the underlying chemistry of rare-earth elements in choline chloride-based deep eutectic solvents by using a multi-technique spectroscopic methodology. Results show that speciation is highly dependent on the choice of the hydrogen-bond donor. Collected EXAFS data showed Ln3+ coordination with ethylene glycol and urea in their respective solvents and coordination with chloride in the lactic acid system. Generalized coordination environments were determined to be [LnL4-5], [LnL7-10], and [LnL5-6] in the ethylene glycol, urea, and lactic acid systems, respectively. Collected UV/vis spectra for Nd3+ and Er3+ showed variations with changing solvents, showing that Ln-Cl interactions do not dominate in these systems. Luminescence studies were consistent, showing varying emission spectra with varying solvent systems. The shortest luminescent lifetimes were observed in the choline chloride-ethylene glycol deep eutectic solvent, suggesting coordination through O-H groups. Combining all collected data allowed Eu3+ coordination geometries to be assigned.

Surface decontamination of protective duplex oxide layers on stainless steel waste using deep eutectic solvents.

The decontamination capabilities of deep eutectic solvents (DESs) formed from choline chloride (ChCl) and p-toluenesulfonic acid monohydrate (PtsA), ChCl:PtsA, under different conditions (hydrated, heated, and agitated) were tested with simulant oxidized stainless steel 304 specimens. Although the leaching rates were satisfactory under all conditions, hydrated and stirred ChCl:PtsA at 60 °C showed the fastest leaching rate of 0.1647 mg/min. Oxidized specimens with an average mass gain of 1.2 ± 1 mg were leached, and their masses were reduced by 558 ± 22 mg after 26 h. These results were understood by improved physical properties of ChCl:PtsA upon hydration. Metal oxide solubility of CoO and NiO increased with water, and those of Cr2O3 and Fe3O4 decreased with hydration. Importantly, the use of choline chloride-based DESs in decontamination applications may significantly reduce the cost of decontamination because these DESs can be mass-produced and their components are both easily obtainable and economical. Also, DESs are biodegradable and eco-friendly. The different speciation of Co and Ni, which bond with Cl-, compared with Fe and Cr, which bond with H2O, illustrated the potential for a metal recovery for secondary liquid waste reduction.

Aerodynamic diameter and radioactivity distributions of radioactive aerosols from activated metals cutting for nuclear power plant decommissioning.

Radioactive aerosols from nuclear power plant decommissioning have not been actively studied compared to those from severe accidents. However, it will be more critical issues in the future. The radioactive aerosols will deposit on the surfaces of matter and disperse in the working space. Hence, the workers in nuclear power plant decommissioning may inhale some of the aerosols during the normal operation or accident. The health effects of aerosols depend not only on the particle size but also on the aerodynamic and thermodynamic characteristics. Therefore, it is crucial to understand the distribution of radioactive aerosols regarding their aerodynamic diameters, radioactive isotopes, and chemical forms to ascertain the respirable fraction. We analyze the effect of the cutting method, cutting material, and cutting conditions on the mass and radioactivity distributions of radioactive aerosols and identify the dominant factor for the safety of workers in the nuclear power plant decommissioning process. We confirm that the chemical composition and radioactive contamination in cutting material affect the aerodynamic diameter distribution and the amount of aerosol. Finally, we suggest the underwater plasma arc cutting process that could minimize the internal dose of workers at the nuclear power plant decommissioning sites.