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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Measurement of Passive Uptake Rates for Volatile Organic Compounds on Commercial Thermal Desorption Tubes and the Effect of Ozone on Sampling

Diffusive or passive sampling methods using commercially filled axial-sampling thermal desorption tubes are widely used for measuring volatile organic compounds (VOCs) in air. The passive sampling method provides a robust, cost effective way to measure air quality with time-averaged concentrations spanning up to a week or more. Sampling rates for VOCs can be calculated using tube geometry and Fick’s Law for ideal diffusion behavior or measured experimentally. There is evidence that uptake rates deviate from ideal and may not be constant over time. Therefore, experimentally measured sampling rates are preferred. In this project, a calibration chamber with a continuous stirred tank reactor design and constant VOC source was combined with active sampling to generate a controlled dynamic calibration environment for passive samplers. The chamber air was augmented with a continuous source of 45 VOCs ranging from pentane to diethyl phthalate representing a variety of chemical classes and physiochemical properties. Both passive and active samples were collected on commercially filled Tenax TA thermal desorption tubes over an 11-day period and used to calculate passive sampling rates. A second experiment was designed to determine the impact of ozone on passive sampling by using the calibration chamber to passively load five terpenes on a set of Tenax tubes and then exposing the tubes to different ozone environments with and without ozone scrubbers attached to the tube inlet. During the sampling rate experiment, the measured diffusive uptake was constant for up to seven days for most of the VOCs tested but deviated from linearity for some of the more volatile compounds between seven and eleven days. In the ozone experiment, both exposed and unexposed tubes showed a similar decline in terpene mass over time indicating back diffusion when uncapped tubes were transferred to a clean environment but there was no indication of significant loss by ozone reaction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm . This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Improved mesh based photon sampling techniques for neutron activation analysis

The design of fusion power systems requires analysis of neutron activation of large, complex volumes, and the resulting particles emitted from these volumes. Structured mesh-based discretization of these problems allows for improved modeling in these activation analysis problems. Finer discretization of these problems results in large computational costs, which drives the investigation of more efficient methods. Within an ad hoc subroutine of the Monte Carlo transport code MCNP, we implement sampling of voxels and photon energies for volumetric sources using the alias method. The alias method enables efficient sampling of a discrete probability distribution, and operates in 0(1) time, whereas the simpler direct discrete method requires 0(log(n)) time. By using the alias method, voxel sampling becomes a viable alternative to sampling space with the 0(1) approach of uniformly sampling the problem volume. Additionally, with voxel sampling it is straightforward to introduce biasing of volumetric sources, and we implement this biasing of voxels as an additional variance reduction technique that can be applied. We verify our implementation and compare the alias method, with and without biasing, to direct discrete sampling of voxels, and to uniform sampling. We study the behavior of source biasing in a second set of tests and find trends between improvements and source shape, material, and material density. Overall, however, the magnitude of improvements from source biasing appears to be limited. Future work will benefit from the implementation of efficient voxel sampling - particularly with conformal unstructured meshes where the uniform sampling approach cannot be applied. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Correcting intensity loss errors in the absence of texture-free reference samples during pole figure measurement

Even with the use of X-ray polycapillary lenses, sample tilting during pole figure measurement results in a decrease in the recorded X-ray intensity. The magnitude of this error is affected by the sample size and/or the finite detector size. These errors can be typically corrected by measuring the intensity loss as a function of the tilt angle using a texture-free reference sample (ideally made of the same alloy as the investigated material). Since texture-free reference samples are not readily available for all alloys, the present study employs an empirical procedure to estimate the correction curve for a particular experimental configuration. It involves the use of real texture-free reference samples that pre-exist in any X-ray diffraction laboratory to first establish the empirical correlations between X-ray intensity, sample tilt and their Bragg angles and thereafter generate correction curves for any Bragg angle. It will be shown that the empirically corrected textures are in very good agreement with the experimentally corrected ones. - Highlights: •Sample tilting during X-ray pole figure measurement leads to intensity loss errors. •Texture-free reference samples are typically used to correct the pole figures. •An empirical correction procedure is proposed in the absence of reference samples. •The procedure relies on reference samples that pre-exist in any texture laboratory. •Experimentally and empirically corrected textures are in very good agreement.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Current and future federal and state sampling guidance for per- and polyfluoroalkyl substances in environmental matrices

Per- and polyfluoroalkyl substances (PFAS) are a class of emerging contaminants composed of an estimated 5000 to 10,000 human-made, fluorinated, organic chemicals. Due to the complexity of PFAS, the need for multiple environmental matrix considerations and the absence of a promulgated federal standard for environmental sampling and analysis, U.S. states have begun developing health-based regulatory and/or guidance values for a limited number of PFAS in environmental matrices. As there is a growing body of science to inform PFAS sampling guidance standard development, it is important to understand which U.S. states are implementing sampling guidelines and how they plan to handle emerging PFAS. This critical review discusses the current and impending federal and state sampling guidelines for PFAS in environmental matrices, the data gaps surrounding PFAS sampling guidance in U.S. states, and the future impacts of impending guidance documents and regulations. Ten federal guidance documents are available for PFAS sampling guidance and analysis. The maximum number of PFAS covered in these guidance documents is 25 analytes spanning across 8 unique media. While the EPA has developed several different sampling and analytical guidelines for PFAS, there is no formal regulation of PFAS or requirements of states to enforce these guidelines. Consequently, only 31 states have informally adopted sampling guidelines, while the other 19 states have no guidance documentation in place for PFAS. The introduction of new PFAS sampling guidelines by the EPA, as well as updated analytical guidelines that target more PFAS or total organofluoride, is expected to continuously shift the landscape of federal and state guidance for PFAS sampling moving forward.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH

Isobaric labeling via tandem mass tag (TMT) reagents enables sample multiplexing prior to LC–MS/MS, facilitating high-throughput large-scale quantitative proteomics. Consistent and efficient labeling reactions are essential to achieve robust quantification; therefore, embedded in our clinical proteomic protocol is a quality control (QC) sample that contains a small aliquot from each sample within a TMT set, referred to as “Mixing QC.” This Mixing QC enables the detection of TMT labeling issues by LC–MS/MS before combining the full samples to allow for salvaging of poor TMT labeling reactions. While TMT labeling is a valuable tool, factors leading to poor reactions are not fully studied. We observed that relabeling does not necessarily rescue TMT reactions and that peptide samples sometimes remained acidic after resuspending in 50 mM HEPES buffer (pH 8.5), which coincided with low labeling efficiency (LE) and relatively low median reporter ion intensities (MRIIs). To obtain a more resilient TMT labeling procedure, we investigated LE, reporter ion missingness, the ratio of mean TMT set MRII to individual channel MRII, and the distribution of log 2 reporter ion ratios of Mixing QC samples. We discovered that sample pH is a critical factor in LE, and increasing the buffer concentration in poorly labeled samples before relabeling resulted in the successful rescue of TMT labeling reactions. Moreover, resuspending peptides in 500 mM HEPES buffer for TMT labeling resulted in consistently higher LE and lower missing data. By better controlling the sample pH for labeling and implementing multiple methods for assessing labeling quality before combining samples, we demonstrate that robust TMT labeling for large-scale quantitative studies is achievable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Effects of sampling techniques on short-term survival and genotyping success of salmonid fry

ABSTRACT Objective Genetics tools have become an integral part of managing and understanding fish populations. Generally, a small tissue sample, such as a fin clip, is taken and then genotyped, with little effect on survival of the fish. However, tissue sampling may have a larger effect on juvenile fish survival compared to their adult counterparts. We evaluated survival and genotyping success of various genetic sampling techniques for Chinook Salmon Oncorhynchus tshawytscha and Rainbow Trout Oncorhynchus mykiss fry. Methods Three sampling treatments were evaluated including control (anesthetized and handled), fin clipping (partial caudal fin clip), and swabbing (OmniSwab was used to collect external mucus). Survival was monitored for 12 d posttreatment, and genotyping success was evaluated. Results Survival was high in all treatment groups (i.e., 0.93–1.00) but, on average, was lower in the swab treatment group. Genotyping was successful in 100% of the fin clip samples and 11–50% of the swab samples. Conclusions Results of this study suggest that sampling caudal-fin tissue does not negatively affect fry short-term survival and the small tissue samples yield highly successful genotyping results. Swabbing did not produce successful genotyping results, and fish sampled with swabs experienced higher mortality than those that received fin clips. Results indicate that fin clips should be used for collection of genetic samples from fry.

McCarrick, Darcy K.↗
DOE OSTI2023

Comparison of quantum advantage experiments using random circuit sampling

Random circuit sampling, the task of sampling bit strings from a random unitary operator, has been implemented to demonstrate quantum advantage on the Sycamore quantum processor with 53 qubits and on the Zuchongzhi quantum processor with 56 and 61 qubits. Recently, it was claimed that classical computers using tensor network simulation could catch on to current noisy quantum processors for random circuit sampling. While the linear cross-entropy benchmark fidelity was used to certify all these claims, it may not capture statistical properties of outputs in detail. Here, we compare the bit strings sampled from classical computers using tensor network simulation by Pan et al. [F. Pan, K. Chen, and P. Zhang, Phys. Rev. Lett. 129, 090502 (2022)] and by Kalachev et al. [G. Kalachev, P. Panteleev, P. Zhou, and M.-H. Yung, arXiv:2112.15083] with the bit strings from the Sycamore quantum processor. It is shown that all of Kalachev et al.'s samples passed the NIST random number tests. The heat maps of bit strings show that Pan et al.'s and Kalachev et al.'s samples are quite different from the Sycamore or Zuchongzhi samples. The analysis with the Marchenko-Pastur distribution and the Wasssertein distances demonstrates that Kalachev et al.'s samples are statistically closer to the Sycamore samples than Pan et al.'s while the three datasets have similar values for the linear cross-entropy fidelity. In conclusion, our finding implies that further study is needed to certify or beat the claims of quantum advantage using random circuit sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

General-Surrogate Adaptive Sampling Using Interquartile Range for Design Space Exploration

Abstract A surrogate model is a common tool to approximate system response at untested points for design space exploration. Adaptive sampling has been studied for improving the accuracy of surrogates iteratively by introducing additional samples (simulations and experiments). New samples are often selected based on the estimated uncertainty in the design space. While some surrogates such as kriging have readily available uncertainty models for their predictions, other surrogates do not. Consequently, there have been studies of using the process of leaving-samples-out (LSO) used in cross-validation tools to estimate prediction uncertainty, such as the universal prediction distribution (UPD). In this paper, an adaptive sampling scheme for general surrogates is proposed based on LSO, similar to cross-validation and interquartile range (IQR). Multiple submodels are first developed from LSO. The uncertainty is then estimated from the IQR of these surrogates at a given point. New samples are added iteratively at the point with maximum IQR for design space exploration. The proposed scheme is illustrated using kriging, radial basis function, and neural network surrogates. The proposed scheme is evaluated using four algebraic test functions. Multiple sets of initial samples were produced to account for randomness. For these test functions, the proposed scheme was found to be more accurate and robust than kriging with its own uncertainty model. The proposed scheme was more accurate than the UPD for three out of the four test functions. For a fixed number of samples, the IQR-based adaptive sampling also proved to be more accurate than all-at-once sampling in most cases even when the estimated uncertainty was only mildly correlated with prediction errors.

Engineering↗
DOE OSTI2013

Random Sampling Process Leads to Overestimation of β-Diversity of Microbial Communities

The site-to-site variability in species composition, known as β-diversity, is crucial to understanding spatiotemporal patterns of species diversity and the mechanisms controlling community composition and structure. However, quantifying β-diversity in microbial ecology using sequencing-based technologies is a great challenge because of a high number of sequencing errors, bias, and poor reproducibility and quantification. Herein, based on general sampling theory, a mathematical framework is first developed for simulating the effects of random sampling processes on quantifying β-diversity when the community size is known or unknown. Also, using an analogous ball example under Poisson sampling with limited sampling efforts, the developed mathematical framework can exactly predict the low reproducibility among technically replicate samples from the same community of a certain species abundance distribution, which provides explicit evidences of random sampling processes as the main factor causing high percentages of technical variations. In addition, the predicted values under Poisson random sampling were highly consistent with the observed low percentages of operational taxonomic unit (OTU) overlap (<30% and <20% for two and three tags, respectively, based on both Jaccard and Bray-Curtis dissimilarity indexes), further supporting the hypothesis that the poor reproducibility among technical replicates is due to the artifacts associated with random sampling processes. Finally, a mathematical framework was developed for predicting sampling efforts to achieve a desired overlap among replicate samples. Our modeling simulations predict that several orders of magnitude more sequencing efforts are needed to achieve desired high technical reproducibility. These results suggest that great caution needs to be taken in quantifying and interpreting β-diversity for microbial community analysis using next-generation sequencing technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using low volume eDNA methods to sample pelagic marine animal assemblages

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380–1800 mL) collected at depths of 0–2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Midmorning Point Sampling May Not Accurately Represent Nitrous Oxide Emissions Following Fertilizer Applications

A common approach for measuring N 2 O emissions is to collect midmorning or early evening gas samples from experiments utilizing the chamber-based flux methodology. However, due to high spatial and temporal variability, N 2 O estimates based on midmorning or early evening sampling may not provide accurate estimates of total emissions. This study determined the impact of sampling collection timing on the precision and accuracy of N 2 O emissions estimates. Nitrous oxide emissions, air and soil temperatures, and soil moisture were measured for 21 d following the application of 224 kg urea-N ha –1 on 20 Sept. 2017, 11 Oct. 2017, and 1 May 2018, at six time intervals (0130–0230, 0530–0630, 0930–1030, 1330–1430, 1730–1830, and 2130–2230 h) over a 24-h period. Based on multiple daily measurements, point samples collected between 0930 and 1030 h (midmorning) were inconsistent in their ability to predict N 2 O emissions. However, samples collected between 2130 and 2230 h (early evening) were similar to average emissions. The number of randomly collected point samples to be within 20% of the mean 80% of the time over a 21-d period ranged from 13 samples for fertilizer applied on 20 Sept. 2017 to 48 samples for fertilizer applied on 11 Oct. 2017. This research indicates that management and climatic variability affect N 2 O emissions, and that accurate sampling protocols vary across management and climates. To reduce uncertainty, N 2 O sampling protocol should be tested under conditions likely to occur and where possible, near-continuous measurement systems should be adopted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Results of Hg speciation testing on tanks 30, 32, and 37 depth samples

The Savannah River National Laboratory (SRNL) was tasked with preparing and shipping samples for Hg speciation by Eurofins Frontier Global Sciences, Inc. in Seattle, WA on behalf of the Savannah River Remediation (SRR) Mercury Task Team. The twelfth shipment of samples was designated to include 3H evaporator system Tank 30, 32, and 37 depth samples. The Tank 30 depth sample (HTF-30-15-70) was taken at 190 inches from the tank bottom and the Tank 32 depth sample (HTF-32-15-68) was taken at 89 inches from the tank bottom and both were shipped to SRNL on June 29, 2015 in an 80 mL stainless steel dip bottles. The Tank 37 surface sample (HTF-37-15-94) was taken around 253.4 inches from the tank bottom and shipped to SRNL on July 21, 2015 in an 80 mL stainless steel dip bottle. All samples were placed in the SRNL Shielded Cells and left unopened until intermediate dilutions were made on July 24, 2015 using 1.00 mL of sample diluted to 100.00 mL with deionized H 2 O. A 30 mL Teflon® bottle was rinsed twice with the diluted tank sample and then filled leaving as little headspace as possible. It was immediately removed from the Shielded Cells and transferred to refrigerated storage where it remained at 4 °C until final dilutions were made on October 20. A second portion of the cells diluted tank sample was poured into a shielded polyethylene bottle and transferred to Analytical Development for radiochemical analysis data needed for Hazardous Material Transportation calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Results of Hg speciation testing on DWPF SMECT-8, OGCT-1, AND OGCT-2 samples

The Savannah River National Laboratory (SRNL) was tasked with preparing and shipping samples for Hg speciation by Eurofins Frontier Global Sciences, Inc. in Seattle, WA on behalf of the Savannah River Remediation (SRR) Mercury Task Team. The sixteenth shipment of samples was designated to include a Defense Waste Processing Facility (DWPF) Slurry Mix Evaporator Condensate Tank (SMECT) sample from Sludge Receipt and Adjustment Tank (SRAT) Batch 738 processing and two Off-Gas Condensate Tank (OGCT) samples, one following Batch 736 and one following Batch 738. The DWPF sample designations for the three samples analyzed are provided. The Batch 738 ‘End of SME Cycle’ SMECT sample was taken at the conclusion of Slurry Mix Evaporator (SME) operations for this batch and represents the fourth SMECT sample examined from Batch 738. Batch 738 experienced a sludge slurry carryover event, which introduced sludge solids to the SMECT that were particularly evident in the SMECT-5 sample, but less evident in the ‘End of SME Cycle’ SMECT-8 sample.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Data Validation Package April 2016 Groundwater and Surface Water Sampling at the Monticello, Utah, Disposal and Processing Sites August 2016

This semiannual event includes sampling groundwater and surface water at the Monticello Disposal and Processing Sites. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated) and Program Directive MNT-2016-01. Complete sample sets were collected from 42 of 48 planned locations (9 of 9 former mill site wells, 13 of 13 downgradient wells, 7 of 9 downgradient permeable reactive barrier wells, 4 of 7 seeps and wetlands, and 9 of 10 surface water locations). Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. Locations R6-M3, SW00-01, Seep 1, Seep 2, and Seep 5 were not sampled due to insufficient water availability. A partial sample was collected at location R4-M3 due to insufficient water. All samples from the permeable reactive barrier wells were filtered as specified in the program directive. Duplicate samples were collected from surface water location Sorenson and from monitoring wells 92-07 and RlO-Ml. Water levels were measured at all sampled wells and an additional set of wells. See Attachment2, Trip Report for additional details. The contaminants of concern (COCs) for the Monticello sites are arsenic, manganese, molybdenum, nitrate+ nitrite as nitrogen (nitrate+ nitrite as N), selenium, uranium, and vanadium. Locations with COCs that exceeded remediation goals are listed in Table 1 and Table 2. Time-concentration graphs of the COCs for all groundwater and surface water locations are included in Attachment 3, Data Presentation. An assessment of anomalous data is included in Attachment 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

M3FT-17OR0301070211 - Preparation of Hot Isostatically Pressed AgZ Waste Form Samples

The production of radioactive iodine-bearing waste forms that exhibit long-term stability and are suitable for permanent geologic disposal has been the subject of substantial research interest. One potential method of iodine waste form production is hot isostatic pressing (HIP). Recent studies at Oak Ridge National Laboratory (ORNL) have investigated the conversion of iodine-loaded silver mordenite (I-AgZ) directly to a waste form by HIP. ORNL has performed HIP with a variety of sample compositions and pressing conditions. The base mineral has varied among AgZ (in pure and engineered forms), silver-exchanged faujasite, and silverexchanged zeolite A. Two iodine loading methods, occlusion and chemisorption, have been explored. Additionally, the effects of variations in temperature and pressure of the process have been examined, with temperature ranges of 525°C–1,100°C and pressure ranges of 100–300 MPa. All of these samples remain available to collaborators upon request. The sample preparation detailed in this document is an extension of that work. In addition to previously prepared samples, this report documents the preparation of additional samples to support stability testing. These samples include chemisorbed I-AgZ and pure AgI. Following sample preparation, each sample was processed by HIP by American Isostatic Presses Inc. and returned to ORNL for storage. ORNL will store the samples until they are requested by collaborators for durability testing. The sample set reported here will support waste form durability testing across the national laboratories and will provide insight into the effects of varied iodine content on iodine retention by the produced waste form and on potential improvements in waste form durability provided by the zeolite matrix.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Solvent Hold Tank Sample Results for MCU-18-425- 427 (October 2018), MCU-18-459-460-461 (November 2018), and MCU-18-487-488-489 (December 2018) (Quarterly Report)

A trend summary of three Solvent Hold Tank (SHT) monthly samples MCU-18-425-426-427, MCU-18- 459-460-461 and MCU-18-487-488-489 are reported. Most of the conclusions are based on the December SHT sample (MCU-18-487-488-489). Analyses of the December SHT sample (MCU-18-487-488-489 indicated that the Modifier (Cs-7SB) and the extractant (MaxCalix) concentrations were below their nominal recommended concentrations (169,000 mg/L and 46,400 mg/L respectively) by 2% and 9% respectively. The suppressor (N,N’,N”–tris(3,7-dimethyloctyl)guanidine or TiDG) concentration has decreased since the October 2018 measurement (Modular Caustic-Side Solvent Extraction Unit or MCU resumed processing (from May through November 2018) to 528 mg/L, but it is above the minimum recommended concentration (479 mg/L). These new levels are consistent with the concentrations observed when MCU was fully operational in 2016. The Semi-Volatile Organic Analysis (SVOA) did not detect any impurities. However, the Fourier Transform Hydrogen Nuclear Magnetic Resonance (FT-HNMR) analysis detected presence of phthalates at a few ppm. The impurity concentration was highest in the October sample and consistently detected in the November and December samples (but always a few ppm or less). Another impurity observed in the samples was mercury. Based on the December SHT sample, up to 24 ± 5 micrograms of mercury per mL of solvent was detected (as the average of the Direct Mercury Analysis (DMA) and X-Ray Fluorescence (XRF) methods). The higher mercury concentration in the solvent (as determined in the last three-monthly samples) is possibly due to the higher mercury concentration in Salt Batches 9 and 10. The gamma concentration (~3.6E5 dpm/mL) measured in the December SHT samples was consistent with previous values observed when MCU was fully operational (for example, between December 2016 and January 2017) but it was lower than the April SHT measurement. The “dip” in the gamma measurement for the May 2018 SHT sample was due to an Isopar™ L addition to MCU during April and May 2018. The laboratory will continue to monitor the quality of the solvent for any new impurities or degradation of the solvent components.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Calendar Year 2020 Underground Test Area Annual Sampling Report Nevada National Security Site, Nevada (Rev. 1)

This CY 2020 annual sampling report presents the background of the FFACO and Sampling Plan implementation, sampling and analysis methods, sampling results, quality assurance and quality control, regulatory requirements, and analytical data for the CY 2020. Appendix A presents data from samples collected in CY 2020 from the YF/CM CAU and the RM/SM CAU. This sampling was conducted in support of the Sampling Plan at these CAUs prior to approval of the final CRs. Appendix B presents the well completion diagrams for the wells sampled in CY 2020. Appendix C presents data from samples collected in CY 2019. These results were not reported in the previous sampling report because they were not available from the specialized laboratories at the time of the report’s publication.

54 ENVIRONMENTAL SCIENCES↗