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At least 829 records · Page 46

Proteomic Sample Preparation Techniques: Towards Forensic Proteomic Applications

Proteomic sample preparation techniques rely on dynamic multi-step processes that are sample type dependent. Forensic proteomic applications comprise diverse sample types and therefore require numerous sample preparation workflows. A sample may need pre-treatment steps to solubilize proteins from a solid surface, for example - from clothing, from a swab, or off of a filter. A sample may need to be disrupted or homogenized to liberate proteins trapped in cells. Or a sample may need additional processing steps, such as organic extraction, to isolate proteins from small molecule contaminants which interfere with mass spectrometry (MS) measurements. Following these pre-treatment steps, proteins are reduced, denatured, alkylated, and enzymatically digested. The resulting peptide mixture can be desalted by solid phase extraction or fractionated prior to liquid chromatography MS-based proteomic characterization. Here we detail each step of this multi-stage sample type dependent processing.

Nicora, Carrie D.↗

Sampling synchronization through GPS signals

A method uses a distributed data acquisition system with multiple, physically unconnected, data acquisition units, that can be in wireless communication with a remote host, to timestamp measurement data with sub-microsecond time base accuracy of sampling clock relative to an absolute timeframe. A current absolute time is derived from messages received from a satellite radio beacon positioning system (GPS). Measurement data is sampled by each unit at a specified sampling rate. Using hardware logic, batches of sampled data are associated with corresponding timestamps representing the absolute time at which the data was sampled. Data and timestamps may be transmitted to the host. A time offset bias is compensated by comparing timestamps against a nominal time based on start time and nominal sampling rate. The sampling clock rate may be disciplined using time pulses from the GPS receiver. An initial start of data sampling by all units can also be synchronized.

Zhuge, James Q.↗

Colonie FUSRAP Site - Radioactive Dust Sampling of Residential and Commercial Properties - 16384

The Colonie Formerly Utilized Sites Remedial Action Program (FUSRAP) Site is located in the Town of Colonie, Albany County, New York. The U.S. Army Corps of Engineers (USACE) is currently addressing environmental contamination associated with the Site. The area surrounding the Site consists of residential and commercial properties, known as vicinity properties (VPs). Cleanup activities have been completed on many of these VPs under the FUSRAP to address depleted uranium contamination. Soil remediation activities have been substantially completed at the Colonie FUSRAP Site and its VPs under the FUSRAP. Recent studies performed by an independent party and under FUSRAP identified uranium within indoor dust in residencies and businesses in the immediate vicinity of the Site. The studies were limited to non-living areas such as basement window sills, garages, and attics. This paper discusses the indoor dust sampling and analysis, in support of the Remedial Investigation (RI) for the VPs, and presents sampling results. The indoor dust sample media presented many technical challenges regarding sampling design, data reduction, and data interpretation. In addition, because the RI is focused on numerous resident-owned, rental, and commercial properties, challenges where presented regarding right-of-entry to sample. Isotopic uranium ratios observed in the majority of the samples are indicative of the depleted uranium contaminant, even at trace levels. While the sampling and analysis methods were effective at identifying depleted uranium in the majority of the samples, preliminary property-specific risk assessment results do not indicate the presence of depleted uranium in sufficient concentrations to pose unacceptable risk to VP inhabitants. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

In Situ Sample Environment for Studying Corrosion of Nuclear Materials

Currently there is lack of fundamental understanding of kinetics and reaction mechanisms that occur at nuclear cladding-steam interface under extreme environments in the nuclear reactors. Such understanding is vital to design and develop advanced cladding materials for more economical and safer nuclear power. We present advanced in situ sample environment for probing solid-fluid interfaces using high resolution synchrotron methods for studying early stages of corrosion including development of oxide layer as corrosion proceeds. Both X-ray diffraction and X-ray fluorescence methods will be discussed to probe structural and elemental composition changes under steam environment using corrosion resistant cell at high temperatures. High intensity and brightness of synchrotron coupled with advanced in situ sample environment developed, presents an opportunity to understand the fundamental interfacial processes involved in degradation of materials. The in situ sample environment is optimized for XRD and XRF data collection at NSLS-II and will be available to all users through the proposal process. The in situ sample environment is built to study the interfacial interactions at temperatures and pressures up to 400 deg. C and 1500 psi. It consists of three main parts; the distribution manifold, the pressure vessel, and the reaction cell as shown in Figure 1. Water is allowed to heat up to 350 deg. C inside the pressure vessel to produce steam which is delivered to reaction cell using insulated delivery system. The cell design is adapted from J. Diefenbacher, et. al. However, it is modified for corrosion applications in steam environments. The reaction cell and sample holder are made from hastelloy due to its high corrosion resistance. The reaction cell is surrounded by copper heating block to control its temperature independently from the rest of the system. Lab view based platform is developed for remote monitoring of pressure and temperature. The sample environment was commissioned at 6-IDD beamline in the Advanced Photon Source, for grazing incidence XRD corrosion studies. Metallic Zr sample (200 μm thickness) was used due to its faster oxidation kinetics as compared to Zircaloy. Sample was exposed to steam at 350 deg. C and 50 psi for a total time of 64 hours. Results showed the presence of α-Zr as the dominant phase. After 32 hours of exposure to steam, three oxide peaks in the low diffraction angle side started to develop with time. These peaks are attributed to the growth of substoichiometric zirconium oxide phases (Zr{sub 3}O and Zr{sub 3}O{sub 1-x}). (authors)

36 MATERIALS SCIENCE↗

Sample mount for electron backscatter diffraction

A sample mount having a bottom surface, a front surface, and a second portion is disclosed. The first portion is perpendicular to the bottom surface. The second portion has an external surface and an internal surface and extends from the first portion to form a 70-degree angle relative to the bottom surface. The sample mount may also have a top surface, an opening extending through the second portion of the front surface, and a receiving area configured to receive a sample, wherein the top surface presents an unimpeded path between the sample and an SEM pole piece. The sample mount may include a spring-loaded handle configured to push the sample against the internal surface of the second portion of the front surface, wherein pushing the sample against the internal surface places the sample at the 70-degree angle relative to the bottom surface.

Wieliczka, David M.↗

Simulation Study of High-Precision Characterization of MeV Electron Interactions for Advanced Nano-Imaging of Thick Biological Samples and Microchips

The resolution of a mega-electron-volt scanning transmission electron microscope (MeV-STEM) is primarily governed by the properties of the incident electron beam and angular broadening effects that occur within thick biological samples and microchips. A precise understanding and mitigation of these constraints require detailed knowledge of beam emittance, aberrations in the STEM column optics, and energy-dependent elastic and inelastic critical angles of the materials being examined. This simulation study proposes a standardized experimental framework for comprehensively assessing beam intensity, divergence, and size at the sample exit. This framework aims to characterize electron-sample interactions, reconcile discrepancies among analytical models, and validate Monte Carlo (MC) simulations for enhanced predictive accuracy. Our numerical findings demonstrate that precise measurements of these parameters, especially angular broadening, are not only feasible but also essential for optimizing imaging resolution in thick biological samples and microchips. By utilizing an electron source with minimal emittance and tailored beam characteristics, along with amorphous ice and silicon samples as biological proxies and microchip materials, this research seeks to optimize electron beam energy by focusing on parameters to improve the resolution in MeV-STEM/TEM. This optimization is particularly crucial for in situ imaging of thick biological samples and for examining microchip defects with nanometer resolutions. Our ultimate goal is to develop a comprehensive mapping of the minimum electron energy required to achieve a nanoscale resolution, taking into account variations in sample thickness, composition, and imaging mode.

36 MATERIALS SCIENCE↗

A portable molecular-sieve-based CO{sub 2} sampling system for radiocarbon measurements

We have developed a field-capable sampling system for the collection of CO{sub 2} samples for radiocarbon-concentration measurements. Most target systems in environmental research are limited in volume and CO{sub 2} concentration, making conventional flask sampling hard or impossible for radiocarbon studies. The present system captures the CO{sub 2} selectively to cartridges containing 13X molecular sieve material. The sampling does not introduce significant under-pressures or significant losses of moisture to the target system, making it suitable for most environmental targets. The system also incorporates a significantly larger sieve container for the removal of CO{sub 2} from chambers prior to the CO{sub 2} build-up phase and sampling. In addition, both the CO{sub 2} and H{sub 2}O content of the sample gas are measured continuously. This enables in situ estimation of the amount of collected CO{sub 2} and the determination of CO{sub 2} flux to a chamber. The portable sampling system is described in detail and tests for the reliability of the method are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Compression–tension cell with sample manipulator for in situ X‐ray nanotomography experiments

In situ X-ray nanotomography experiments where tensile or compressive force is applied on the sample require specialized equipment. A compression-tension device with fluid flow-through capability has been designed for X-ray nanotomography beamlines. The compression-tension cell is equipped with a triaxial stage for sample alignment and a high sensitivity loadcell for measurement of applied force. To handle the <100 µm samples used for X-ray nanotomography imaging and for loading samples on the compression-tension cell a sample manipulator has been built. The sample manipulator is capable of selecting a single <100 µm particle for nanotomography scanning while viewing multiple samples under an optical microscope. To test the functionality of these two devices an initial compression experiment involving two glass beads was performed. To demonstrate instrument stability two spherical glass beads were compressed from a no load condition until one of the beads fractured. Nanotomography data were collected at each step of increasing compressive force. The experimentally observed contact area of the spherical glass beads was compared with the theoretical estimate using the Hertz analysis. To demonstrate the fluid flow capability, two calcite grains were compressed against each other under a calcite saturated solution. Surface topological changes were observed for the stressed grain contact area.

X-ray tomography↗

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.

61 RADIATION PROTECTION AND DOSIMETRY↗

TH-EF-BRA-08: A Novel Technique for Estimating Volumetric Cine MRI (VC-MRI) From Multi-Slice Sparsely Sampled Cine Images Using Motion Modeling and Free Form Deformation

Purpose: To develop a technique to estimate on-board VC-MRI using multi-slice sparsely-sampled cine images, patient prior 4D-MRI, motion-modeling and free-form deformation for real-time 3D target verification of lung radiotherapy. Methods: A previous method has been developed to generate on-board VC-MRI by deforming prior MRI images based on a motion model(MM) extracted from prior 4D-MRI and a single-slice on-board 2D-cine image. In this study, free-form deformation(FD) was introduced to correct for errors in the MM when large anatomical changes exist. Multiple-slice sparsely-sampled on-board 2D-cine images located within the target are used to improve both the estimation accuracy and temporal resolution of VC-MRI. The on-board 2D-cine MRIs are acquired at 20–30frames/s by sampling only 10% of the k-space on Cartesian grid, with 85% of that taken at the central k-space. The method was evaluated using XCAT(computerized patient model) simulation of lung cancer patients with various anatomical and respirational changes from prior 4D-MRI to onboard volume. The accuracy was evaluated using Volume-Percent-Difference(VPD) and Center-of-Mass-Shift(COMS) of the estimated tumor volume. Effects of region-of-interest(ROI) selection, 2D-cine slice orientation, slice number and slice location on the estimation accuracy were evaluated. Results: VCMRI estimated using 10 sparsely-sampled sagittal 2D-cine MRIs achieved VPD/COMS of 9.07±3.54%/0.45±0.53mm among all scenarios based on estimation with ROI-MM-ROI-FD. The FD optimization improved estimation significantly for scenarios with anatomical changes. Using ROI-FD achieved better estimation than global-FD. Changing the multi-slice orientation to axial, coronal, and axial/sagittal orthogonal reduced the accuracy of VCMRI to VPD/COMS of 19.47±15.74%/1.57±2.54mm, 20.70±9.97%/2.34±0.92mm, and 16.02±13.79%/0.60±0.82mm, respectively. Reducing the number of cines to 8 enhanced temporal resolution of VC-MRI by 25% while maintaining the estimation accuracy. Estimation using slices sampled uniformly through the tumor achieved better accuracy than slices sampled non-uniformly. Conclusions: Preliminary studies showed that it is feasible to generate VC-MRI from multi-slice sparsely-sampled 2D-cine images for real-time 3D-target verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Surface Water FTICR-MS, NPOC, TN, Anions, Stable Isotopes, Bacterial Abundance, and Dissolved Inorganic Carbon (v8)

The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the surface water samples and does not include any results from the sediment. Sediment data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1729719. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in March 2020. It was updated in October 2020 (v2, new and modified files), July 2021 (v3, new and modified files), January 2023 (v4, new and modified files), February 2023 (v5, new and modified files), August 2023 (v6, new and modified files), July 2025 (v7,new and modified files), and August 2026 (v8, new and modified files). Version 8 includes major restructuring of the files and their formats. See the change history section in readme for more details. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset contains (1) readme, (2) data dictionary, (3) file level metadata, (4) sampling protocol, (5) a data checks report, (6) field metadata, (7) international generic sample number (IGSN) mapping file, (8) joint genome institute (JGI) mapping file, and (9) a folder of sample data. The sample data folder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and FTICR methods, (2) dissolved inorganic carbon (DIC), (3) stable water isotopes (O and H), (4) specific conductivity, (5) total dissolved nitrogen (TN), (6) anions, (7) flow cytometry bacterial abundance data, (8) laboratory methods, and (9) a folder containing unaligned, peak-picked high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL, https://www.pnnl.gov/environmental-molecular-sciences-laboratory), and (12) a folder containing processed FTICR-MS data. All files are .msa, .txt, .spx, .xml, .csv, .pdf, .txt, .html, .jpg, or .jpeg.

18-O↗

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Sediment FTICR-MS, Dissolved Organic Carbon, Aerobic Respiration, Elemental Composition, Grain Size, Total Nitrogen and Organic Carbon Content, Bacterial Abundance, and Stable Isotopes (v10)

The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the sediment samples and does not include any results from the surface water. Surface water data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1603775. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in December 2020. It was updated in April 2021 (v2; modified files), May 2022 (v3; new and modified files), November 2022 (v4; new and modified files), January 2023 (v5 and v6; new and modified files), February 2023 (v7; new and modified files), August 2023 (v8; new and modified files), July 2025 (v9; new and modified files), and June 2026 (v10; new and modified files). Version 10 includes major restructuring of the files and their formats. See the change history in the readme for details. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset contains (1) readme, (2) data dictionary, (3) file level metadata, (4) sampling protocol, (5) a data checks report, (6) field metadata, (7) international generic sample number (IGSN) mapping file, (8) joint genome institute (JGI) mapping file, (9) a folder of site photos, and (10) a folder of sample data. The sample data folder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and FTICR methods; (2) respiration rates and normalized respiration rates calculated from laboratory sediment incubations, (3) X-ray fluorescence (XRF) elemental composition, (4) grain size distribution from the < 2 millimeter fraction of sediment, (5) total organic carbon and total nitrogen content, (6) bacterial abundance flow cytometry data, (7) sediment stable isotopes (C and N), (8) laboratory methods, (9) water and sediment mass and volume used in incubations, (10) a folder with code, inputs, and plots for the respiration rates, (11) a folder containing XRF data, (12) a folder containing unaligned, peak-picked high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (12) and a folder containing processed FTICR-MS data. All files are .msa, .txt, .spx, .xml, .csv, .pdf, .txt, .jpg, or .jpeg.

13C↗

Spatial Study 2022: Surface Water Samples, Cotton Strip Degradation, and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides data and photos generated from sample collection during the same one-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. The contents include surface water geochemistry data; river substrate grain size photos; stream depth data; manual chamber open channel respiration data; and field metadata (including qualitative information on instream and river corridor characteristics). Grain size photos can be used to improve estimates of channel substrate D50 data. The dataset also includes tensile strength and photos from cotton strip field degradation experiments; five-week sensor time series temperature, dissolved oxygen, pressure, pH, specific conductance, chlorophyll A, and turbidity data; plots of the sensor data; and R scripts used to generate the plots. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. SSS data published in the CM data package were not included in this data package. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Additionally, sensor data from a similar 2021 spatial study can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052 and 2021 sample data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1898914. The 2021 spatial study had some sites in common with this 2022 spatial study. This dataset is comprised of three photo folders and one main data folder with six subfolders. The photo folders contain photographs and videos of cotton strip retrieval and sediment quadrats. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) total suspended solids (TSS) data and cotton strip tensile strength data and averages; (5) field protocol; (6) readme; (7) methods codes; (8) international generic sample number (IGSN) mapping file; (9) sensor installation methods summary; (10) stream depth and averages; and (11) Ultrameter data and averages. The Sonar subfolder consists of Sonar time-series depth data and a processing script. The BarotrollAtm, DepthHOBO, MantaRiver, miniDOT, and miniDOTManualChamber subfolders contain time-series data, plots, and summary files. All files are .csv, .pdf, .txt, .R, .Rmd, .jpg, .jpeg, .AVI, .mp4, or .mov. The data package was originally published in April 2023. It was updated in August 2023 (v2; modified files) and September 2024 (v3; modified files). See the change history section in the readme for details. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Post-fire time series of sensor and geochemistry sample data from surface water, groundwater, precipitation, soil, and vegetation across Oak Creek watershed, Washington

This dataset supports a broader study examining wildfire impacts on hydrologic connectivity across 5 sites within the Oak Creek watershed and the resulting biogeochemical impacts. Stream sites were selected using the Advanced Terrestrial Simulator (ATS) hydrologic model to identify locations with varying groundwater contributions and hydrologic responses across different burn severity scenarios. The Retreat Fire burned from July 23 to August 2 in 2024, affecting the five study sites at varying burn severities. Each site is equipped with YSI EXO2 sondes logging sub-hourly throughout the year, and grab samples are collected approximately every six weeks. YSI sondes are used to measure temporally resolved proxies for groundwater inputs (specific conductivity) and organic matter (fluorescent dissolved organic matter; fDOM) along with basic water quality and depth. Grab samples of surface water, groundwater, and precipitation are analyzed for water stable isotopes and conductivity to understand endmembers for hydrologic mixing Grab samples of surface water, groundwater, soil water, and litter/vegetation/soil leachates are analyzed for organic matter composition measured by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) to understand organic matter dynamics. Game camera photos are provided in a separate data package available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018598. Future versions of this dataset will include time series data from YSI EXO2 sondes (fDOM, dissolved oxygen, temperature, depth, specific conductance, turbidity, pH), BaroTROLL sensors (air temperature and barometric pressure), rain gauges (precipitation), and data from the soil and vegetation samples. Because this study is ongoing, this data package will be updated regularly to include newly collected data and the additional data types. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data; (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) a data checks report; (5) file-level metadata; (6) data dictionary; (7) field metadata; (8) readme; (9) international generic sample number (IGSN) mapping file; and (10) field protocols. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) stable water isotopes and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Biogeochemistry↗

Analysis of Tank 39H (HTF-39-15-61, 62) Surface and Subsurface Supernatant Samples in Support of Corrosion Control Program

This report provides the results of analyses on Tanks 39H surface and subsurface supernatant liquid samples in support of the Corrosion Control Program. Analyses included warm acid strike preparation followed by analysis for silicon, aluminum, and sodium and water dilution preparation followed by analysis for anions. Other reported analytical results include analyses results for uranium, Pu-241 and Pu-239. The measured sodium concentration averaged, respectively, 4.28E+00 ± 9.30E-02 M and 4.32E+00 ± 1.076E-01 M in the Tank 39H surface sample and Tank 39H subsurface sample. In general, the nitrate, nitrite, free-OH and specific gravity of the Tank 39H surface and subsurface samples were all about the same in magnitude, respectively, averaging 1.98 M, 0.314 M, 1.26 M and 1.24. The measured silicon concentration for the Tank 39H surface and subsurface samples were, respectively, 3.84E+01± 5.51E+00 and 4.14E+01± 1.17E + 00 mg/L. Based on the uranium, Pu-241 and Pu-239 concentrations, the calculated U-235 equivalent is 21.41 wt% for the surface sample and 21.32 wt% for the subsurface sample.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Results For The Third Quarter Calendar Year 2016 Tank 50H Salt Solution Sample

In this memorandum, the chemical and radionuclide contaminant results from the Third Quarter Calendar Year 2016 (CY16) sample of Tank 50H salt solution are presented in tabulated form. The Third Quarter CY16 Tank 50H samples (a 200 mL sample obtained 6” below the surface (HTF-5-16-63) and a 1 L sample obtained 66” from the tank bottom (HTF-50-16-64)) were obtained on July 14, 2016 and received at Savannah River National Laboratory (SRNL) on the same day. Prior to obtaining the samples from Tank 50H, a single pump was run at least 4.4 hours, and the samples were pulled immediately after pump shut down. The information from this characterization will be used by Defense Waste Processing Facility (DWPF) & Saltstone Facility Engineering for the transfer of aqueous waste from Tank 50H to the Saltstone Production Facility, where the waste will be treated and disposed of in the Saltstone Disposal Facility. This memorandum compares results, where applicable, to Saltstone Waste Acceptance Criteria (WAC) limits and targets. Data pertaining to the regulatory limits for Resource Conservation and Recovery Act (RCRA) metals will be documented at a later time per the Task Technical and Quality Assurance Plan (TTQAP) for the Tank 50H saltstone task. The chemical and radionuclide contaminant results from the characterization of the Third Quarter CY16 sampling of Tank 50H were requested by Savannah River Remediation (SRR) personnel and details of the testing are presented in the SRNL TTQAP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques

Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.

36 MATERIALS SCIENCE↗

Cluster Sampling Filters for Non-Gaussian Data Assimilation

This paper presents a fully non-Gaussian filter for sequential data assimilation. The filter is named the &ldquo;cluster sampling filter&rdquo;, and works by directly sampling the posterior distribution following a Markov Chain Monte-Carlo (MCMC) approach, while the prior distribution is approximated using a Gaussian Mixture Model (GMM). Specifically, a clustering step is introduced after the forecast phase of the filter, and the prior density function is estimated by fitting a GMM to the prior ensemble. Using the data likelihood function, the posterior density is then formulated as a mixture density, and is sampled following an MCMC approach. Four versions of the proposed filter, namely C ℓ MCMC , C ℓ HMC , MC- C ℓ HMC , and MC- C ℓ HMC are presented. C ℓ MCMC uses a Gaussian proposal density to sample the posterior, and C ℓ HMC is an extension to the Hamiltonian Monte-Carlo (HMC) sampling filter. MC- C ℓ MCMC and MC- C ℓ HMC are multi-chain versions of the cluster sampling filters C ℓ MCMC and C ℓ HMC respectively. The multi-chain versions are proposed to guarantee that samples are taken from the vicinities of all probability modes of the formulated posterior. The new methodologies are tested using a simple one-dimensional example, and a quasi-geostrophic (QG) model with double-gyre wind forcing and bi-harmonic friction. Here, numerical results demonstrate the usefulness of using GMMs to relax the Gaussian prior assumption especially in the HMC filtering paradigm.

97 MATHEMATICS AND COMPUTING↗