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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Characterization of Tank 9H Annulus Sample in Support of Residual Material Inventory Determinations

The Savannah River National Laboratory (SRNL) was requested by Savannah River Mission Completion (SRMC) to provide sample preparation and characterization of the Tank 9H annulus sample in support of Residual Material Inventory Determinations. One Tank 9H sample in three vials [HTF-9-25-13, HTF-9-25-14 and HTF-9-25-15], with each vial containing approximately 200 mL of the Tank 9H annulus salt solution, were delivered to the SRNL Shielded Cells for sample preparation and characterizations in February 2025. The density of the “as-received” solution contained in each of the three Tank 9H annulus sample vials were determined followed by a solid-liquid separation on each one using 0.45-micron Nalgene® nylon filter membranes. The resulting filtrates were combined to form the Tank 9H annulus sample with a total volume of about 600 mL. The combined wet solid fractions, about a total of 4.8 grams of salt material, remaining on the filter membranes were air-dried in the Shielded Cells for 72 hours. The total weight of the air-dried solids was 2.1 grams. These air-dried solids were washed with deionized water (DI water) at a phase ratio of 60 mL DI water/gram of solids to recover insoluble solids, if any. No visible or measurable quantity of insoluble solids were recovered after DI water washing of the air-dried solids because the air-dried solids completely dissolved in the DI water. The solid fraction-wash water was not combined with the 600 mL of the filtrate solution, and the resulting solution was not screened or analyzed for radionuclides. Aliquot sample volumes of the undiluted Tank 9H annulus sample were sent to the SRNL analytical services groups for radionuclides, elementals, anions and total mercury analysis by various methods including radiochemical separations/counting methods, inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) and special preparations. All sample analyses were performed in triplicate. This report presents the analytical characterization results for the Tank 9H annulus sample. The results are also reported where analytical methods yielded additional analytes, other than those requested by SRMC. In the characterization of the Tank 9H annulus sample, the detection limits for all the analytes, as specified in the Technical Task Request (TTR) and Task Technical and Quality Assurance Plan (TTQAP), were met.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Improving Photometric Redshift Estimates with Training Sample Augmentation

Abstract Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek methods to improve the photo- z estimates that arise from nonrepresentative training samples. Spectroscopic training samples for photo- z 's are biased toward redder, brighter galaxies, which also tend to be at lower redshift than the typical galaxy observed by LSST, leading to poor photo- z estimates with outlier fractions nearly 4 times larger than for a representative training sample. In this Letter, we apply the concept of training sample augmentation, where we augment simulated nonrepresentative training samples with simulated galaxies possessing otherwise unrepresented features. When we select simulated galaxies with ( g - z ) color, i -band magnitude, and redshift outside the range of the original training sample, we are able to reduce the outlier fraction of the photo- z estimates for simulated LSST data by nearly 50% and the normalized median absolute deviation (NMAD) by 56%. When compared to a fully representative training sample, augmentation can recover nearly 70% of the degradation in the outlier fraction and 80% of the degradation in NMAD. Training sample augmentation is a simple and effective way to improve training samples for photo- z 's without requiring additional spectroscopic samples.

Moskowitz, Irene (ORCID:0000000222068589)↗

DOE OSTI2024

Production rate calibration for cosmogenic 10 Be in pyroxene by applying a rapid fusion method to 10 Be-saturated samples from the Transantarctic Mountains, Antarctica

Measurements of multiple cosmogenic nuclides in a single sample are valuable for various applications of cosmogenic nuclide exposure dating and allow for correcting exposure ages for surface weathering and erosion and establishing exposure–burial history. Here we provide advances in the measurement of cosmogenic 10 Be in pyroxene and constraints on the production rate that provide new opportunities for measurements of multi-nuclide systems, such as 10 Be/ 3 He, in pyroxene-bearing samples. We extracted and measured cosmogenic 10 Be in pyroxene from two sets of Ferrar Dolerite samples collected from the Transantarctic Mountains in Antarctica. One set of samples has 10 Be concentrations close to saturation, which allows for the production rate calibration of 10 Be in pyroxene by assuming production–decay equilibrium. The other set of samples, which has a more recent exposure history, is used to determine if a rapid fusion method can be successfully applied to samples with Holocene to Last Glacial Maximum exposure ages. From measured 10 Be concentrations in the near-saturation sample set we find the production rate of 10 Be in pyroxene to be 3.74 ± 0.10 atoms g -1 yr -1 , which is consistent with 10 Be/ 3 He paired nuclide ratios from samples assumed to have simple exposure. Given the high 10 Be concentration measured in this sample set, a sample mass of ~ 0.5 g of pyroxene is sufficient for the extraction of cosmogenic 10 Be from pyroxene using a rapid fusion method. However, for the set of samples that have low 10 Be concentrations, measured concentrations were higher than expected. We attribute spuriously high 10 Be concentrations to failure in removing all meteoric 10 Be and/or a highly variable and poorly quantified procedural blank background correction.

58 GEOSCIENCES↗

DOE OSTI2012

Transmission electron microscope sample holder with optical features

A sample holder for holding a sample to be observed for research purposes, particularly in a transmission electron microscope (TEM), generally includes an external alignment part for directing a light beam in a predetermined beam direction, a sample holder body in optical communication with the external alignment part and a sample support member disposed at a distal end of the sample holder body opposite the external alignment part for holding a sample to be analyzed. The sample holder body defines an internal conduit for the light beam and the sample support member includes a light beam positioner for directing the light beam between the sample holder body and the sample held by the sample support member.

47 OTHER INSTRUMENTATION↗

DOE OSTI2013

Sample holder with optical features

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

A Portable Immunoassay Platform for Multiplexed Detection of Biotoxins in Clinical and Environmental Samples

Multiple cases of attempted bioterrorism events using biotoxins have highlighted the urgent need for tools capable of rapid screening of suspect samples in the field (e.g., mailroom and public events). We present a portable microfluidic device capable of analyzing environmental (e.g., white powder), food (e.g., milk) and clinical (e.g., blood) samples for multiplexed detection of biotoxins. The device is rapid (<15-30 min sample-to-answer), sensitive (< 0.08 pg/mL detection limit for botulinum toxin), multiplexed (up to 64 parallel assays) and capable of analyzing small volume samples (< 20 μL total sample input). The immunoassay approach (SpinDx) is based on binding of toxins in a sample to antibody-laden capture particles followed by sedimentation of particles through a density-media in a microfluidic disk and quantification using a laser-induced fluorescence detector. A direct, blinded comparison with a gold standard ELISA revealed a 5-fold more sensitive detection limit for botulinum toxin while requiring 250-fold less sample volume and a 30 minute assay time with a near unity correlation. A key advantage of the technique is its compatibility with a variety of sample matrices with no additional sample preparation required. Ultrasensitive quantification has been demonstrated from direct analysis of multiple clinical, environmental and food samples, including white powder, whole blood, saliva, salad dressing, whole milk, peanut butter, half and half, honey, and canned meat. We believe that this device can met an urgent need in screening both potentially exposed people as well as suspicious samples in mail-rooms, airports, public sporting venues and emergency rooms. The general-purpose immunodiagnostics device can also find applications in screening of infectious and systemic diseases or serve as a lab device for conducting rapid immunoassays.

Koh, Chung-Yan↗

DOE OSTI2021

Laser ablation sampling system and method

A method and system for sampling a solid sample material can include the step of mounting the sample material on a support. A sample surface is coated with a surface treatment composition in a dry deposition process. A solvent supply conduit for supplying solvent to the sample surface and a solvent exhaust conduit for withdrawing solvent from the sample surface can be provided. Solvent is flowed from the solvent supply conduit to the surface treatment composition and the sample surface such that the solvent contacts the surface treatment composition. A laser beam is directed from a laser source to the sample and the surface treatment composition. The laser beam will ablate the sample and the surface treatment composition in portions intersected by the laser beam. Ablated sample material enters the solvent liquid and will be transported with the solvent away from the sample surface through the solvent exhaust conduit.

Kertesz, Vilmos↗

DOE OSTI2023

Laser ablation sampling system and method

Kertesz, Vilmos↗

DOE OSTI2015

Improved Sampling Algorithms in the Risk-Informed Safety Margin Characterization Toolkit

The RISMC approach is developing advanced set of methodologies and algorithms in order to perform Probabilistic Risk Analyses (PRAs). In contrast to classical PRA methods, which are based on Event-Tree and Fault-Tree methods, the RISMC approach largely employs system simulator codes applied to stochastic analysis tools. The basic idea is to randomly perturb (by employing sampling algorithms) timing and sequencing of events and internal parameters of the system codes (i.e., uncertain parameters) in order to estimate stochastic parameters such as core damage probability. This approach applied to complex systems such as nuclear power plants requires to perform a series of computationally expensive simulation runs given a large set of uncertain parameters. These types of analysis are affected by two issues. Firstly, the space of the possible solutions (a.k.a., the issue space or the response surface) can be sampled only very sparsely, and this precludes the ability to fully analyze the impact of uncertainties on the system dynamics. Secondly, large amounts of data are generated and tools to generate knowledge from such data sets are not yet available. This report focuses on the first issue and in particular employs novel methods that optimize the information generated by the sampling process by sampling unexplored and risk-significant regions of the issue space: adaptive (smart) sampling algorithms. They infer system response from surrogate models constructed from existing samples and predict the most relevant location of the next sample. It is therefore possible to understand features of the issue space with a small number of carefully selected samples. In this report, we will present how it is possible to perform adaptive sampling using the RISMC toolkit and highlight the advantages compared to more classical sampling approaches such Monte-Carlo. We will employ RAVEN to perform such statistical analyses using both analytical cases but also another RISMC code: RELAP-7.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Say where you sample: Increasing site selection transparency in urban ecology

Urban ecological studies have the potential to extend our understanding of socio-ecological systems beyond that of an individual city or region. Cross-comparative empirical work and synthesis are imperative to develop a general urban ecological theory. This can be achieved only if studies are replicable and generalizable. Transparency in methods reporting facilitates generalizability and replicability by documenting the decisions scientists make during the various steps of research design; this is particularly true for sampling design and selection because of their impact on both internal and external validity and the potential to unintentionally introduce bias. Three interdependent aspects of sample design are study sample selection (e.g., specific organisms, soils, or water), sample specification (measurement of specific variable of interest), and site selection (locations sampled). Of these, documentation of site selection—the where component of sample design—is underrepresented in the urban ecology literature. Using a stratified random sample of 158 papers from 12 major urban ecology journals, we investigated how researchers selected study sites in urban ecosystems and evaluated whether their site selection methods were transparent. We extracted data from these papers using a 50-question, theory-based questionnaire and a multiple-reviewer approach. Our sample represented almost 45 years of urban ecology research across 40 different countries. We found that more than 80% of the papers read were not transparent in their site selection methodology. We do not believe site selection methods are replicable for 70% of the papers read. Key weaknesses include incomplete descriptions of populations and sampling frames, urban gradients, sample selection methods, and property access. Low transparency in reporting the where methodology limits urban ecologists’ ability to assess the internal and external validity of studies’ findings and to replicate published studies; it also limits the generalizability of existing studies. The challenges of low transparency are particularly relevant in urban ecology, a field where standard protocols for site selection and delineation are still being developed. These limitations interfere with the fields’ ability to build theory and inform policy. We conclude by offering a set of recommendations to increase transparency, replicability, and generalizability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Using Xe Plasma FIB for High-Quality TEM Sample Preparation

Here, a direct comparison between electron transparent transmission electron microscope (TEM) samples prepared with gallium (Ga) and xenon (Xe) focused ion beams (FIBs) is performed to determine if equivalent quality samples can be prepared with both ion species. We prepared samples using Ga FIB and Xe plasma focused ion beam (PFIB) while altering a variety of different deposition and milling parameters. The samples’ final thicknesses were evaluated using STEM-EELS $\textit{t/λ}$ data. Using the Ga FIB sample as a standard, we compared the Xe PFIB samples to the standard and to each other. We show that although the Xe PFIB sample preparation technique is quite different from the Ga FIB technique, it is possible to produce high-quality, large area TEM samples with Xe PFIB. We also describe best practices for a Xe PFIB TEM sample preparation workflow to enable consistent success for any thoughtful FIB operator. For Xe PFIB, we show that a decision must be made between the ultimate sample thickness and the size of the electron transparent region.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Compact, portable, automatic sample changer stick for cryostats and closed-cycle refrigerators

Beamlines are facilities that produce and deliver highly focused and intense beams of radiation, typically x rays, synchrotron radiation, or neutrons, for scientific research purposes. Millions of dollars are spent annually to maintain and operate these scientific beamlines, oftentimes running continuously between cycles. To reduce human intervention and improve productivity, mechanical sample changers are often commissioned for use. Designing sample changers is difficult because mechanical parts can be bulky, expensive, and challenging to design for instruments with low volume access, high radiation, and cryogenic environments. We present a portable and inexpensive sample changer stick that can hold and manipulate up to four samples, specifically designed for use with cryogenic closed-cycle refrigerators. The sample changer stick enables rapid and efficient exchange of samples without manual intervention, and is compatible with standard sample mounts such as vanadium cans. The sample changer stick includes a motorized rotation and lancing mechanism, which enables the precise positioning of each sample in the neutron beam, while ensuring compatibility with the operating temperatures and vacuum conditions required for closed-cycle refrigerators. The design has been successfully tested at the VISION beamline at the Spallation Neutron Source. The mechanical action and software controls are detailed. Furthermore, the sample changer stick is a valuable tool for scientists working with cryogenic closed-cycle refrigerators.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction

Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. With remote sensing data, acquiring a sufficiently representative training set is a challenge due to both the inherent multi-modal variability of satellite or aerial imagery and the general high cost of labeling data. To address this challenge, we have developed ISOSCELES, an Iterative Self-Organizing SCEne LEvel Sampling method for hierarchical sampling of large image sets. Using affinity propagation, ISOSCELES automates the selection of highly representative training images. Compared to random sampling or using available reference data, the distribution of the training is principally data driven, reducing the chance of oversampling uninformative areas or undersampling informative ones. In comparison to manual sample selection by an analyst, ISOSCELES exploits descriptive features, spectral and/or textural, and eliminates human bias in sample selection. Using a hierarchical sampling approach, ISOSCELES can obtain a training set that reflects both between-scene variability, such as in viewing angle and time of day, and within-scene variability at the level of individual training samples. We verify the method by demonstrating its superiority to stratified random sampling in the challenging task of adapting a pre-trained model to a new image and spatial domain for country-scale building extraction. Using a pair of hand-labeled training sets comprising 1,987 sample image chips, a total of 496,000,000 individually labeled pixels, we show, across three distinct model architectures, an increase in accuracy, as measured by F1-score, of 2.2–4.2%.

42 ENGINEERING↗

DOE OSTI2012

Respiratory motion sampling in 4DCT reconstruction for radiotherapy

Purpose: Phase-based and amplitude-based sorting techniques are commonly used in four-dimensional CT (4DCT) reconstruction. However, effect of these sorting techniques on 4D dose calculation has not been explored. In this study, the authors investigated a candidate 4DCT sorting technique by comparing its 4D dose calculation accuracy with that for phase-based and amplitude-based sorting techniques.Method: An optimization model was formed using organ motion probability density function (PDF) in the 4D dose convolution. The objective function for optimization was defined as the maximum difference between the expected 4D dose in organ of interest and the 4D dose calculated using a 4DCT sorted by a candidate sampling method. Sorting samples, as optimization variables, were selected on the respiratory motion PDF assessed during the CT scanning. Breathing curves obtained from patients' 4DCT scanning, as well as 3D dose distribution from treatment planning, were used in the study. Given the objective function, a residual error analysis was performed, and k-means clustering was found to be an effective sampling scheme to improve the 4D dose calculation accuracy and independent with the patient-specific dose distribution. Results: Patient data analysis demonstrated that the k-means sampling was superior to the conventional phase-based and amplitude-based sorting and comparable to the optimal sampling results. For phase-based sorting, the residual error in 4D dose calculations may not be further reduced to an acceptable accuracy after a certain number of phases, while for amplitude-based sorting, k-means sampling, and the optimal sampling, the residual error in 4D dose calculations decreased rapidly as the number of 4DCT phases increased to 6.Conclusion: An innovative phase sorting method (k-means method) is presented in this study. The method is dependent only on tumor motion PDF. It could provide a way to refine the phase sorting in 4DCT reconstruction and is effective for 4D dose accumulation. Optimized sorting techniques could achieve acceptable residuals (less than 0.5% of the prescription dose) using 6 sorting samples, which is much better than amplitude-based or phase-based sorting. Further increase in sorting phase number exceeding 6 or more may not be necessary when using the k-means sampling or optimal sampling points.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Characterization Data Package for Containerized Sludge Samples Collected from Engineered Container SCS-CON-210

This data package contains the K Basin sludge characterization results obtained by Pacific Northwest National Laboratory during processing and analysis of four sludge core samples collected from Engineered Container SCS-CON-210 in 2010 as requested by CH2M Hill Plateau Remediation Company. Sample processing requirements, analytes of interest, detection limits, and quality control sample requirements are defined in the KBC-33786, Rev. 2. The core processing scope included reconstitution of a sludge core sample distributed among four to six 4-L polypropylene bottles into a single container. The reconstituted core sample was then mixed and subsampled to support a variety of characterization activities. Additional core sludge subsamples were combined to prepare a container composite. The container composite was fractionated by wet sieving through a 2,000 micron mesh and a 500-micron mesh sieve. Each sieve fraction was sampled to support a suite of analyses. The core composite analysis scope included density determination, radioisotope analysis, and metals analysis, including the Waste Isolation Pilot Plant Hazardous Waste Facility Permit metals (with the exception of mercury). The container composite analysis included most of the core composite analysis scope plus particle size distribution, particle density, rheology, and crystalline phase identification. A summary of the received samples, core sample reconstitution and subsampling activities, container composite preparation and subsampling activities, physical properties, and analytical results are presented. Supporting data and documentation are provided in the appendices. There were no cases of sample or data loss and all of the available samples and data are reported as required by the Quality Assurance Project Plan/Sampling and Analysis Plan.

core sampling↗

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↗