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NASA NTRSDate not supplied

Identification of Presolar Grains in Quick Look Samples of Asteroid Bennu Returned By the OSIRIS-REx Mission

The OSIRIS-REx spacecraft returned regolith sample from the B-type asteroid Bennu on September 24, 2023. The first samples to be analyzed, termed the Quick Look samples, are comprised of material collected from the avionics deck of the OSIRIS-REx sample canister. Initial mineralogical analysis of the Quick Look sample revealed a diversity of components, including hydrated and anhydrous silicates, sulfides, magnetite, phosphates, and abundant organic matter. Each constituent has their own origin and history, and their study can inform us of the history of Bennu and its parent asteroid. The analysis plan for asteroid Bennu samples is guided by hypotheses that address specific periods of Bennu’s history, from the pre-accretionary epoch to the OSIRIS-REx epoch. The pre-accretionary epoch studies aim to characterize materials that predate the formation of the solar system. One hypothesis that falls under this epoch is that Bennu contains presolar materials derived from diverse sources. These presolar materials include stardust grains that condensed from the outflows of evolved stars or the ejecta of novae and supernovae (SN), as well as organic matter that formed in the interstellar medium. Here we report the identification of C-rich presolar stardust grains in the Bennu Quick Look sample. Isotopically anomalous organic matter in this sample is reported in.

A N Nguyen↗

NASA NTRSDate not supplied

Summary of Apollo Next Generation Sample Analysis (ANGSA) and Insights for Artemis Preliminary Examination Activities

Analyses of Apollo samples have provided fundamental insights into the origin and history of the Earth-Moon system and the solar system broadly. With great foresight, a subset of samples from Apollo were left unprocessed so that they could be studied by future generations with their modern technology. To prepare for the return of samples from the Moon by the Artemis Program, NASA initiated the Apollo Next Generation Sample Analysis Program (ANGSA) to analyze a subset of the previously unprocessed Apollo samples. The ANGSA consortium consisted of 9 original teams funded by NASA that combined into a single science team referred to as the ANGSA Science Team. ANGSA was designed to function like the sample analysis phase of a sample return mission with a goal to investigate the lower portion of a double drive tube previously sealed on the lunar surface (73001), the upper portion of that drive tube that had remained unopened (73002), and a variety of Apollo 17 samples that had remained stored at -20 ºC for approximately 50 years.

Francis M. McCubbin↗

NASA NTRSDate not supplied

Trace Oxygen Measurements of Asteroid Sample Storage Desiccators

The Astromaterials Curation facility at the NASA Johnson Space Center is currently curating more than 120 g of carbonaceous asteroid Bennu material as well as over 500 mg of asteroid Ryugu [1 and 2]. These astromaterials are stored in isolating desiccators and gloveboxes under a continuous purge of pure (<1 ppm O 2 ) gaseous nitrogen. The oxygen and moisture concentrations in our OSIRIS-REx sample processing gloveboxes are continuously monitored via integrated sensors; however, our sample storage desiccators lack integrated oxygen and humidity sensors. In previous studies, we used PreSens Fibox 4 trace oxygen meters and optochemical PSt9 spot sensors to measure the oxygen concentrations in candidate asteroid sample containers that had been sealed in nitrogen; we determined that Eagle stainless steel containers inhibit the ingress of external oxygen for several weeks [3]. This optochemical sensor technology allowed us to take precise, contactless measurements within a trace range of 0 to 200 ppmv O 2 . The effectiveness of the trace oxygen sensors in our container experiments inspired us to utilize them to assess the performance of our desiccators that previously lacked trace oxygen monitoring. In this study, our goal was to determine the quality of the nitrogen purge in the isolating desiccator under normal operating conditions by measuring the trace oxygen content. Utilizing optochemical sensor technology, we determined how long the oxygen concentration takes to reach an equilibrium in the desiccator; that is, determine the rate at which the oxygen diffusion into the desiccator equals the rate at which oxygen diffuses out of the desiccator via N2 purge. Additionally, we wanted to determine the oxygen concentration at this equilibrium, the state in which our desiccators are in during normal operating conditions. We tested a custom three chamber desiccator manufactured by Germfree using a PSt9 trace oxygen sensor spot that was mounted into a ¼” National Pipe Tapered (NPT) metal flow-through cell and attached it to the desiccator exhaust. The desiccator consists of top, middle, and bottom isolating chambers. The top chamber door was opened for several minutes to simulate a sample exchange, it was sealed, and then purged ~15 Standard Cubic Feet per Hour (SCFH). Oxygen measurements were automatically recorded via the Fibox 4 trace oxygen meter in 5-minute intervals over the course of a 24-hour period. Our results indicate the desiccator reached an equilibrium value of 10-15 ppm O 2 after ~5 hours (Fig. 1). This data allows us to explore standards for purging and exchange protocols that can be applied to similar types of desiccators in Hayabusa2, OSIRIS-REx, and for sample return collections. The assessment of the internal gaseous compositions of desiccators also allows us to share with the community the N 2 environment in which many of our asteroid samples and hardware are securely curated. Future measurements will include other nitrogen flow rates and measuring the trace oxygen concentration as a function of time for the levels of the previous commercial desiccator in which the Hayabusa2 sample collection was stored. We will also analyze how long the desiccators hold N2 after being disconnected from their N2 source, an extended measurement for sample security reassurance.

Curation↗

DOE OSTI2023

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.↗

DOE OSTI2024

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.↗

DOE OSTI2024

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↗

DOE OSTI2025

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↗

DOE OSTI2023

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↗

DOE OSTI2026

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↗

DOE OSTI2025

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↗

DOE OSTI2022

Meta-Study of Particulate Detection Losses on Radioactive Air Sample Filters

Several mathematical relationships between air sample filter mass loading and the correlated analytical self-absorption factor were developed using data from other published research in this meta-study. Gross-alpha and -beta applications are addressed for this research. As filter media becomes loaded with particulate matter, there is potential for measurement losses due to self-absorption by mass loading. Components contributing to absorption include particulate dust, radioactive particulates, and filter material. Standards indicate a correction factor should be used when the penetration of radioactive material into the collection media or self-absorption of radiation by the material collected would reduce the detection rate by more than 5%. Previously, losses due to self-absorption have been reported up to 100% over a range up to ~10 mg∙cm -2 mass loading. These absorption losses then can be used to determine a correction factor for sample results. For low mass loadings (e.g., ≤0.1 mg∙cm -2 ) corrections factors in the 0.85 - 1 range have been recommended and used, while at higher mass loadings nearer to 10 mg∙cm -2 correction factors closer to 0 (representing near 100% losses) are used. Based on data from published studies, the different methods for relating percent loss due to self-absorption to mass loading include linear, exponential, quadratic, and trinomial derived functions. Where applicable, both forced zero and non-forced zero results were evaluated. From the derived functions evaluated, the trinomial function provided the best fit. Once the sample filter mass loading is known, the trinomial function can be applied to estimate losses and the corresponding self-absorption factor. When applied to routine operating conditions for radiological facility stacks monitored at the Pacific Northwest National Laboratory for an average sample filter mass loading of 0.09 ± 0.12 (2σ) mg∙cm -2 (excluding negative values and outliers) and a range from 0 - 0.24 mg∙cm -2 , the estimated trinomial function nominal self-absorption losses are less than 5% at 0.09 mg∙cm -2 and less than 10% at 0.24 mg∙cm -2 . The trinomial function is one method that may be used to adjust the activity results of an air sample when the sample-specific mass loading is determined. The application of no correction factor when the ANSI/HPS N13.1-2021 guidance of a 5% threshold for loss is not reached with typical stack sample mass loadings may be reasonable in high-efficiency particulate air filtered systems. For simplicity, it would be conservative in assigning the self-absorption correction factor at the 5% threshold (i.e., 0.95) for general uses but in cases of heavy mass loading to calculate the factor.

air sampling↗

NASA NTRSDate not supplied

Mars Sample Return – An Overview of the Capture, Containment and Return System

The Mars Sample Return campaign aims at bringing back soil, rock and atmospheric samples from Mars to Earth to answer key questions about Mars’ biological evolution by means of four missions. The first one, Mars 2020, landed on the red planet on February 18, 2021 and has to date collected a number of samples through the Perseverance rover. The three subsequent missions will recover the sample tubes, launch them into Mars orbit and transport them back to Earth. These missions are currently in the planning and design stages of development and represent an international effort comprising NASA, ESA and many industry partners. The work presented here provides an overview of the current design and concept of operations of the NASA-provided Capture, Containment, and Return System (CCRS), which is the payload of the ESA-provided Earth Return Orbiter (ERO). ERO will rendezvous with the orbiting samples and CCRS will capture them, contain them and robotically insert them into a capsule that will return the samples to Earth, the Earth Entry System (EES). Three days before arrival on Earth, CCRS will release the EES, which will fly through space, enter Earth’s atmosphere, descend on a well-defined trajectory and safely land at the Utah Test and Training Range. The decision to implement Mars Sample Return will not be finalized until NASA’s completion of the National Environmental Policy Act process. This document is being made available for information purposes only.

Mars Sample Return↗

NASA NTRS2023

Stand Alone Electrical Equipment PRL 227a (Formerly PRL 227 LOC3) Confirmatory Sampling Report Addendum

HydroGeoLogic, Inc. (HGL) prepared this Confirmatory Sampling Report Addendum (CSRA) for the National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), Florida. PRL 227a Location of Concern (LOC) 3 is located on 10th Street, west of the former Vertical Processing Facility (M7-1469), SWMU 077. The Load Break Switches (LBS) were installed in 1986 and are suspected to have formerly contained dielectric fluid that contained polychlorinated biphenyls (PCBs). The LBS were replaced in 1993 with new LBSs that do not contain PCBs. The LBS are located on a concrete pad surrounded by grass that is mowed and maintained. A total of 330 soil samples were collected between June 2020 and December 2022 from 88 locations at depths ranging from 0-0.5 to 19-20 ft bls. In general, soil samples collected from depths less than 5 ft were collected via hand auger and samples collected beyond 5 ft bls were collected using a direct-push technology drill rig. Soil samples collected from greater than 5 ft bls to 20 ft bls were collected to confirm PCBs were not present at depth in the aquifer matrix. Delineation samples were collected using an approximately 20 ft horizontal spacing. PCB impacted soil has been completely delineated to the State of Florida residential soil cleanup target level (SCTL) at PRL 227a horizontally and vertically. PCB concentrations have been identified above the residential and industrial SCTL as well as concentrations greater than or equal to 50 ppm requiring coordination with EPA and disposal at a facility authorized under TSCA. Based upon the CSRA sampling, an interim measure is recommended to remove PCB impacted soil above the residential SCTL. The total volume of PCB impacted soil to be removed is 591.6 cubic yards. This includes approximately 9.3 cubic yards of soil with PCB concentrations greater than or equal to 50 ppm. An interim measure work plan is included as an attachment to this report.

electrical equipment↗

NASA NTRSDate not supplied

The Venus Atmospheric Sample Return (VATMOS-SR) Mission Concept

VATMOS-SR (Venus ATMOSpheric - Sample Return) is a small space- craft mission concept that would return several gas samples from the upper atmosphere of Venus (< 110 km) to Earth for scientific analysis. This could be the first sample return mission for an extraterrestrial atmosphere and potentially the first sample return from an Earth-sized planet. The VATMOS-SR mission concept consists of a SmallSat atmospheric sampling probe (45 deg. sphere/cone geometry, <1 m diameter) that is designed to skim through the Venus upper atmosphere and ac- quire gas samples below the homopause altitude (around ~110 km altitude), where the different atmospheric gases are mixed. The velocity of the spacecraft where sampling would occur is expected to be between ~10.5 km/s and ~13.1 km/s, depending on the trajectory chosen (e.g. trajectory shown in Fig. 1).

direct simulation Monte Carlo↗

NASA NTRSDate not supplied

The Venus Atmospheric Sample Return (VATMOS-SR) Mission Concept

direct simulation Monte Carlo↗

NASA NTRS2012

Evaluating Core Quality for a Mars Sample Return Mission

Sample return missions, including the proposed Mars Sample Return (MSR) mission, propose to collect core samples from scientifically valuable sites on Mars. These core samples would undergo extreme forces during the drilling process, and during the reentry process if the EEV (Earth Entry Vehicle) performed a hard landing on Earth. Because of the foreseen damage to the stratigraphy of the cores, it is important to evaluate each core for rock quality. However, because no core sample return mission has yet been conducted to another planetary body, it remains unclear as to how to assess the cores for rock quality. In this report, we describe the development of a metric designed to quantitatively assess the mechanical quality of any rock cores returned from Mars (or other planetary bodies). We report on the process by which we tested the metric on core samples of Mars analogue materials, and the effectiveness of the core assessment metric (CAM) in assessing rock core quality before and after the cores were subjected to shocking (g forces representative of an EEV landing).

Mars samples↗

DOE OSTI2024

Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Abstract Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain ( https://centilebrain.org/#/brainAGE2 ), an open‐science, web‐based platform for individualized neuroimaging metrics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Improved sampling technique to collect natural gas from hydrate-bearing pressure cores

High quality gas compositional data are an important factor in interpreting the genetic source of natural gas hosted in hydrate-bearing sediments and other subsurface systems. In order to accurately characterize the composition of gas samples degassed from hydrate-bearing pressure cores, one must use a reproducible sampling technique that minimizes artifacts of the sampling process. Herein, we review sediment core degassing techniques and compare data obtained from a commonly used degassing approach, which we term the standard quantitative degassing (SQD) technique, to our newly developed modified quantitative degassing (MQD) method designed to minimize atmospheric contamination and gas-water interactions. The SQD method allows sample gas to interact with water in a bubbling chamber, which we hypothesize could alter the gas composition following mixing with water or dissolved gases in the bubbling chamber. Whereas, the MQD method allows for the collection of sample gas prior to the bubbling chamber. To compare the SQD and MQD methods, we performed a side-by-side comparison of noble (He, Ne, Ar, Kr, and Xe), major (H 2 , N 2 , O 2 , and CO 2 ), and hydrocarbon (CH 4 , C 2 H 6 , C 3 H 8 , i-C 4 H 10 , C 4 H 10 , i-C 5 H 12 , C 5 H 12 ) gas concentrations and select isotopic compositions obtained using both sample collection techniques. Gas samples were collected from hydrate-bearing pressure cores recovered and maintained under hydrate stable conditions from the northern Gulf of Mexico during the UT-GOM 2 -1 Expedition. The MQD method displayed significantly lower concentrations of atmospheric gases, higher proportions of hydrocarbon gases, lower ratios of C 1 /C 2 + , and heavier stable carbon and hydrogen isotopes of methane than the SQD method. These results demonstrate that the MQD method reduced air contamination and minimized alteration of the hydrocarbon gases. Finally, we conclude this method may be important for future work that seeks to determine the composition of natural gas from pressure cores using quantitative degassing experiments, especially those seeking to measure major (e.g., N 2 ) and noble gases.

58 GEOSCIENCES↗