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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

UT-GOM2-2 Preliminary Report: Terrebonne Basin Northern Gulf of Mexico, 30 July-28 September 2023

In the summer and fall of 2023, the Gulf of Mexico Deepwater Hydrate Coring Expedition (UT-GOM2-2) drilled, cored, made downhole measurements, and analyzed samples from the seafloor to the base of the gas hydrate stability zone in one location (Site H, WR313) in the Terrebonne basin, deepwater Gulf of Mexico. Analyses of data and samples from the expedition will inform biological, geochemical, and geomechanical models to constrain the role of gas hydrates in the carbon cycle and the potential for gas hydrates as an energy resource. Pressure and conventional cores were collected continuously to a depth of 155.1 meters below the seafloor (mbsf). At deeper depths, cores were taken periodically from hydrate-bearing sands and their bounding muds to a total depth of 861.3 mbsf. 162.6 m of conventional core and 54.8 m of pressure core were obtained. Twelve temperature measurements were made between 27.1 and 144.5 mbsf to determine the geothermal gradient. At the seafloor, more than 4 m of sandy silt of unknown origin was encountered. Beneath this sand, to a depth of ~200 mbsf, the section was composed of interbedded mud and biogenic carbonate ooze. The biogenic ooze correlated to low density and high porosity intervals observed in the previously acquired logging while drilling (LWD) data and as measured. Calcareous nannofossil biostratigraphy constrains the entire record to the Pleistocene (< 0.91 million years) with a pronounced increase in sedimentation rate with depth. Beneath 200 mbsf, the section was predominantly composed of mud with two thicker, hydrate-bearing coarse-grained intervals, which are commonly known as the Blue and Orange sands. The dissolved gas concentration was quantified from pressure cores. In the shallow section, dissolved methane concentration increased below the sulfate-methane transition zone (SMTZ) and reaches saturation (the limit of solubility for methane) at 147 mbsf. Gas expansion was very common in conventional and depressurized pressure (conventionalized) cores below the SMTZ. At deeper depths, the methane concentration within muds bounding the Blue and Orange reservoirs was generally found to be less than saturation. The dissolved and hydrate gas composition is consistent with a microbial source, containing greater than 99.99% methane and only trace concentrations of ethane, propane, and butane. The methane to ethane ratio (C 1 /C 2 ) and the methane to ethane plus propane (C 1 /(C 2 +C 3 )) decrease with depth down to at least 678 mbsf, mainly driven by the increase in ethane with depth. It is unclear if this trend continues through the Orange sand interval. The δ 13 C isotopic signature of methane ranges between -69.9 and -78.5 ‰ Vienna Pee Dee Belemnite (VPDB). Pressure core recovery of all sandy intervals was poor. However, pressure core logs of the Orange sand show intervals of low density and high velocity, which are indicative of high hydrate saturation. One core from within the Orange sand was composed of interbedded graded sandy silt and mud. The sandy silts from this core are composed of mainly quartz and feldspar with some lithics. Most of the recovered pressure core samples are maintained at near in-situ pressure and temperature (within the hydrate stability field) at the University of Texas Pressure Core Center awaiting analysis. In the shallow section, samples will be used to determine the flux of organic carbon through the basin system, find the rate at which that carbon was consumed, and understand the microbial population responsible for these processes. In the deeper section, samples from in and around the hydrate reservoirs will be used to determine the petrophysical properties of the reservoir and bounding seals in these systems.

03 NATURAL GAS↗
DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗
DOE OSTI2025

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗
DOE OSTI2022

Experimental study of compaction localization in carbonate rock and constitutive modeling of mechanical anisotropy

Abstract Sedimentary rocks are inherently anisotropic and prone to strain localization. While the influence of rock anisotropy on the brittle/dilative regime has been studied extensively, its influence on the ductile/compactive regime is much less explored. This paper discusses the anisotropic behavior of a high‐porosity carbonate rock from central Europe (the Maastricht Tuffeau). A set of triaxial tests with concurrent x‐ray tomography has been performed at different confining pressures. The anisotropic characteristics of this rock have been investigated by testing samples cored at different inclinations of the bedding, thus revealing non‐negligible effects of the coring direction on yielding and compaction behavior. Specifically, samples cored perpendicular to bedding display higher strength and longer stages of post‐yielding deformation before manifesting re‐hardening. Despite such alterations of the inelastic response, Digital Image Correlation has revealed that the strain localization mode is independent of the coring direction, thus being primarily affected by the confinement level. To capture the observed interaction between material anisotropy and compaction behavior at the continuum‐scale, an elastoplastic constitutive law has been proposed. For this purpose, a set of tensorial bases has been introduced to replicate how the oriented rock fabric modulates the yielding and plastic flow characteristics of the material. The analyses show that the impact of the coring direction on yield function and plastic flow rule is fundamentally different, thus requiring the use of distinct projection strategies (a strategy here defined heterotopic mapping). The performance of the model, studied through parametric analyses and by calibrating the experimental results, illustrates the improved capability of the proposed constitutive approach when applied to strongly anisotropic porous rocks.

Shahin, Ghassan↗
DOE OSTI2023

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

NSUF Report EBSD analyses on metallic fuel samples: Tips and improvements in sample preparation

EBSD (Electron Backscatter Diffraction) is an analytic technique used to evaluate the microstructure of a specimen. It can be used to evaluate interesting crystallographic data ranging from grains size to grain orientation, from grain boundaries to stresses. Moreover, in the field of nuclear materials EBSD can aid in estimating properties important for reactor performance, such as dislocation and residual strain [1]. EBSD patterns are generated by focusing a stationary electron gun on the specimen and detecting the backscatter electrons that satisfy Bragg conditions, and thus are diffracted by the crystal planes forming the so called Kikuchi bands. These bands correspond to each of the lattice diffracting crystal planes and are detected on a phosphor screen via a low-light CCD camera [2]. The patterns are generated within a small interaction volume located at a depth of less than 50-100 nm. Because of this, the data quality is extremely sensitive to the integrity of the crystallographic lattice order at the surface of the sample and thus to sample preparation and to oxidation [3]. While conventional sample preparation methods are widely used in materials science, they often do not lead to quality electron backscatter patterns needed for the characterization of nuclear materials [4]. This has been related by many authors to the challenges associated with handling radiological specimens, their rapid oxidation, and artifacts in such samples (e.g. high number of defects, precipitates and/or porosities) [4-8]. EBSD, however, can be an invaluable technique to evaluate microstructural evolution during fabrication and after irradiation at the required mesoscale for model and simulation. It also provides important information on grain structure necessary to understand irradiation effect, such as grain subdivision. Thus, it is of paramount importance to further the application of this technique to nuclear materials and especially irradiated fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Deciphering the Distribution and Crystal-Chemical Environment of Arsenic, Lead, Silica, Phosphorus, Tin, and Zinc in a Porous Ferrihydrite Grain Using Transmission Electron Microscopy and Atom Probe Tomography

Here the interaction of contaminants and nutrients with soil constituents is controlled by processes in intergranular and intragranular pore spaces of organic matter or/and common secondary minerals such as ferrihydrite, ~Fe 3+ 10 O 14 (OH) 2 . This contribution shows that distribution and clustering of the contaminants As, P, Pb, Si, Sn, and Zn in a porous ferrihydrite grain is greatly affected by the heterogeneous size distribution and chemical composition of the pores as well as the ability of their polyhedra to polymerize with the same type of polyhedron. Transmission electron microscopy (TEM) and atom probe tomography (APT) studies are conducted on focused ion beam (FIB) sections extracted from a porous ferrihydrite grain from the smelter-impacted topsoil in Sudbury, Ontario, Canada. The ferrihydrite grain has pore spaces ranging in diameter from tens to hundreds of nanometers. TEM and scanning-TEM studies indicate that the surfaces of the pore walls are enriched in Si. APT data in conjunction with First Near Neighbor (1NN) analyses indicate different degrees of clustering of Pb, As, Sn, Zn, Si, and P within the sample and selected domains. Careful evaluations of 3D atomic plots and 1NN distances indicates the occurrence of polymerized arsenite-, silica-, Sn-, and Zn-polyhedra within pore spaces of the ferrihydrite. Deciphering adsorption, polymerization, and nucleation processes in porous Fe-(hydr)oxides and other soil constituents requires multianalytical approaches and, in this regard, we discuss the advantages and disadvantages of the combination of TEM and APT for characterizing complex environmental samples at the atomic to nanometer scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Detailed Method for the Purification of Rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana

The plant cell wall is a dynamic and complex extracellular matrix that not only provides structural integrity and determines cell shape but also mediates intercellular communication. Among its major components, pectins play essential roles in cell adhesion, wall porosity, hydration, and flexibility. Rhamnogalacturonan-I (RG-I), a structurally diverse pectic polysaccharide, remains one of the least understood components of the plant cell wall. Its backbone is substituted with arabinan, galactan, and arabinogalactan side chains that vary in length, branching, and composition across tissues, species, and developmental stages. In addition, RG-I can undergo modifications such as backbone acetylation, further contributing to its structural complexity and functional diversity. To advance understanding of RG-I, we present a detailed method for isolating RG-I from the model plant Arabidopsis thaliana . Leveraging Arabidopsis as a model system provides major advantages owing to its well-characterized genome and powerful molecular toolkit, enabling deeper investigation into the roles of RG-I in plant development and responses to environmental stress. Our method consists of two major steps: an initial chemical extraction using oxalate, followed by endo-polygalacturonase (EPG) digestion to fragment the pectic domains. An advantage of this approach is that it produces a dry material that can be stored at room temperature without special handling and does not introduce chemicals that may interfere with downstream analyses. The purified RG-I can be used for detailed compositional and structural analyses, as well as for functional studies of enzymes involved in pectin biosynthesis, modification, and degradation. Although this protocol was developed for isolating RG-I from Arabidopsis rosette leaves, it is also applicable to other Arabidopsis organs and other plant species.

25 ENERGY STORAGE↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Synthesis of PHI-type zeolite harmotome using barium as an inorganic structure-directing agent inspired from natural mineral compositions

Zeolites are nanoporous aluminosilicates widely used as commercial adsorbents, heterogeneous catalysts, and ion-exchange materials due to their unique porosity, acidity, and thermal stability. The vast majority of synthetically-realized zeolite structures are prepared under hydrothermal conditions in alkaline media, and often in the presence of an organic structure-directing agent that facilitates the crystallization of diverse porous networks. Due to economic and environmental disadvantages of organic-based syntheses, it is often desirable to produce zeolites in organic-free media using alkali metal ions as the most commonly employed inorganic structure-directing agents (ISDAs). Here, in this study, we were inspired by the elemental compositions of natural zeolite minerals to examine the use of an alkaline earth metal ion as the ISDA to prepare zeolites with the PHI framework type. Two natural minerals exhibiting this crystal structure are phillipsite and harmotome. Both structures contain sodium and potassium as extra-framework cations, but only harmotome contains barium cations. Here we examined how the combination of alkali and alkaline earth ISDAs promote the formation of PHI-type zeolites. Our findings reveal that each isostructure is prepared under different synthesis conditions where simply adding barium to a growth mixture does not always lead to harmotome formation. Harmotome is formed in more dilute and alkaline growth media; however, time-resolved analyses of zeolite crystallization reveal that harmotome can be synthesized at low temperatures (ca. 65 °C) with rates that are 5-times faster than syntheses of phillipsite. This seemingly indicates that barium reduces the energetic barrier for PHI-type zeolite nucleation in ways that are not fully understood. Moreover, harmotome crystals exhibit an average particle size of ca. 60 nm, which is nearly 40-fold smaller than phillipsite crystals prepared under similar conditions. Collectively, these findings identify routes to control crystallization of PHI-type zeolites and may provide a broader strategy for using the composition of natural zeolite minerals to optimize the preparation of synthetic analogues.

36 MATERIALS SCIENCE↗
NASA NTRS1999

Forced Mixer Nozzle Optimization

Computational fluid dynamic (CFD) and computational acoustic analyses (CAA) were performed for a TFE731-40 compound nozzle, a TFE731-60 mixer nozzle and an Energy Efficient Engine (E(sup 3)) mixer nozzle for comparison with available data. The CFD analyses were performed with a three dimensional, Navier-Stokes solution of the flowfield on an unstructured grid using the RAMPANT program. The CAA analyses were performed with the NASA Glenn MGB program using a structured grid. A successful aerodynamic solution for the TFE731-40 compound nozzle operating statically was obtained, simulating an engine operating on a test stand. Analysis of the CFD results of the TFE731-40 with the MGB program produced predicted sound power levels that agree quite well with the measured data front full-scale static engine tests. Comparison of the predicted sound pressure with the data show good agreement near the jet axis, but the noise levels are overpredicted at angles closer to the inlet. The predicted sound power level for the TFE731-60 did not agree as well with measured static engine data as the TFE731-40. Although a reduction in the predicted noise level due to the mixed flow was observed, the reduction was not as significant as the measured data. The analysis of the V2 mixer from the E(sup 3) study showed that peak temperatures predicted in the mixer exit flowfield were within 5 percent of the values measured by the exit probes. The noise predictions of the V2 mixer nozzle tended to be 3-5 dB higher in peak noise level than the measurements. In addition, the maximum frequency of the noise was also overpredicted. An analysis of the 3 candidate mixer nozzle configurations demonstrated the feasibility of using centerbody lobes and porosity to improve mixing efficiency. A final configuration was designed with a predicted thermal mixing efficiency that was 5 percent higher than the 3 candidate mixers. The results of the MGB noise calculations show that the final design will exceed the design goal of a 3 dB reduction in noise as compared to the baseline TFE731-40.

Sheoran, Yogi↗
DOE OSTI2021

Seeing through nuclear fuel: Three-dimensional, nondestructive X-ray microscopy and volumetric analyses of neutron-irradiated TRISO-coated fuel kernels

The three-dimensional (3D) characterization of nuclear fuel with X-ray microscopy has historically proven difficult, due to uranium’s high attenuation of easily accessible X-rays, both in a laboratory setting and at a synchrotron user facility. However, this imaging modality provides nondestructive information that can be used to investigate morphological changes arising from external stimuli (e.g., neutron irradiation, high-temperature testing). Using an appropriate X-ray energy spectrum and an adequate X-ray filter, suitable transmissions through properly sized nuclear fuel specimens can be achieved. Here, in this study, we present the methods and results of using a commercially available, laboratory-based X-ray microscope (XRM) to examine the extent of 3D morphological changes of tristructural isotropic (TRISO)-coated fuel particles, specifically uranium oxide/uranium carbide fuel kernels, after high-temperature neutron irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗
NASA NTRS2014

Data Processing and Experimental Design for Micrometeorite Impacts in Small Bodies

Comets and asteroids have been altered from their original "pristine" state by impacts occurring throughout their 4.5 billion year lives: [1]. Proof of shock deformation has been detected in the crystal structure of several Stardust samples from Comet Wild 2 [2, 3]. Analyses indicated that the planar dislocations in the crystal structure of the minerals had been imparted by impacts sustained during their lives, and not due to the aerogel capture process. Distortions to crystal structure also affect the ideal absorption spectra in the infrared, and [4], thus providing indirect evidence of its impact history and a means of remotely investigating the impact history of small bodies through comparing laboratory spectra with spectra observed by telescopes or spacecraft. -The effects of impacts propagating shock waves through minerals were investigated through laboratory impact experiments. Utilizing NASA Johnson Space Center's Experimental Impact Laboratory, projectiles were fired from the vertical gun at velocities ranging from 2.0 to 2.8 km/sec, projected impact velocities between Kuiper Belt Objects. Two types of projectiles were used, including spherical alumina ceramic, whose density mimics that of rock, and cylinders made from the same material that they impacted. The target materials chosen for testing included: OLIVINES forsterite (Mg2SiO4) and fayalite, Fe2SiO4); PYROXENES enstatite (Mg2Si2O6) and diopside (MgCaSi2O6); and CARBONATES magnesite (MgCO3) and siderite (FeCO3). Targets were impacted at either 25 C or cooled to -20 C to examine the effects of temperature, if any, on lattice distortions during the shock propagation. As comets and asteroids can undergo a wide range of temperatures in their orbital lifetimes, the effect of temperature on the equation of state of minerals being shocked needs to be examined for interpreting the results of these experiments. The porosity of the target mineral is varied by either grinding it into a powder/granular texture or as whole mineral rocks to investigate the differences in shock propagation when voids are present. By varying velocity, ambient temperature, and porosity, we can investigate different variables affecting impacts in the solar system. -Data indicates that there is a non-linear relationship between peak shock pressure and the variation in infrared spectral absorbances by the distorted crystal structure. The maximum variability occurs around 37 GPa in enstatite and forsterite. The particle size distribution of the impacted material similarly changes with velocity/peak shock pressure. -The experiments described above are designed to measure the near- to mid-IR effects from these changes to the mineral structure. See Lederer et al., this meeting for additional experimental results.

Jensen, E.↗
NASA NTRS2003

Wind Tunnel Testing of Various Disk-Gap-Band Parachutes

Two Disk-Gap-Band model parachute designs were tested in the NASA Langley Transonic Dynamics Tunnel. The purposes of these tests were to determine the drag and static stability coefficients of these two model parachutes at various subsonic Mach numbers in support of the Mars Exploration Rover mission. The two model parachute designs were designated 1.6 Viking and MPF. These model parachute designs were chosen to investigate the tradeoff between drag and static stability. Each of the parachute designs was tested with models fabricated from MIL-C-7020 Type III or F-111 fabric. The reason for testing model parachutes fabricated with different fabrics was to evaluate the effect of fabric permeability on the drag and static stability coefficients. Several improvements over the Viking-era wind tunnel tests were implemented in the testing procedures and data analyses. Among these improvements were corrections for test fixture drag interference and blockage effects, and use of an improved test fixture for measuring static stability coefficients. The 1.6 Viking model parachutes had drag coefficients from 0.440 to 0.539, while the MPF model parachutes had drag coefficients from 0.363 to 0.428. The 1.6 Viking model parachutes had drag coefficients 18 to 22 percent higher than the MPF model parachute for equivalent fabric materials and test conditions. Model parachutes of the same design tested at the same conditions had drag coefficients approximately 11 to 15 percent higher when manufactured from F-111 fabric as compared to those fabricated from MIL-C-7020 Type III fabric. The lower fabric permeability of the F-111 fabric was the source of this difference. The MPF model parachutes had smaller absolute statically stable trim angles of attack as compared to the 1.6 Viking model parachutes for equivalent fabric materials and test conditions. This was attributed to the MPF model parachutes larger band height to nominal diameter ratio. For both designs, model parachutes fabricated from F-111 fabric had significantly greater statically stable absolute trim angles of attack at equivalent test conditions as compared to those fabricated from MILC-7020 Type III fabric. This reduction in static stability exhibited by model parachutes fabricated from F-111 fabric was attributed to the lower permeability of the F-111 fabric. The drag and static stability coefficient results were interpolated to obtain their values at Mars flight conditions using total porosity as the interpolating parameter.

Cruz, Juan R.↗
DOE OSTI2021

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a through going network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density. This submission includes the published journal article detailing this work, the published 3-D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3-D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using existing R programs.

15 GEOTHERMAL ENERGY↗
NASA NTRS2016

Precision Oxygen Isotope Measurements of Two C-Rich Hydrated Interplanetary Dust Particles

Introduction: Chondritic-smooth IDPs (Interplanetary Dust Particles) are low porosity objects whose mineralogy is dominated by aqueous alteration products such as Mg-rich phyllosilicates (smectite and serpentine group) and Mg-Fe carbonate minerals. Their hydrated mineralogy combined with low atmospheric entry velocities have been used to infer an origin largely from asteroidal sources. Spectroscopic studies show that the types and abundance of organic matter in CS IDPs is similar to that in CP IDPs. Although CS IDPs show broad similarities to primitive carbonaceous chondrites, only a few particles have been directly linked to specific meteorite groups such as CM and CI chondrites based on the presence of diagnostic minerals. Many CS IDPs however, have carbon contents that greatly exceed that of known meteorite groups suggesting that they either may derive from comets or represent samples of more primitive parent bodies than do meteorites. It is now recognized that many large, dark primitive asteroids in the outer main belt, as well as some trans-Neptunian objects, show spectroscopic evidence for aqueous alteration products on their surfaces. Some CS IDPs exhibit large bulk D enrichments similar to those observed in the cometary CP IDPs. While hydrated minerals in comets have not been unambiguously identified to date, the presence of the smectite group mineral nontronite has been inferred from infrared spectra obtained from the ejecta from comet 9P/Tempel 1 during the Deep Impact mission. Recent observations of low temperature sulfide minerals in Stardust mission samples suggest that limited aqueous activity occurred on comet Wild-2. All of these observations, taken together, suggest that the high-carbon hydrated IDPs are abundant and important samples of primitive solar system objects not represented in meteorite collections. Oxygen isotopic compositions of chondrites reflect mixing between a 16O-rich reservoir and a 17O,18O-rich reservoir produced via mass-independent fractionation. The composition of the 16O-rich reservoir is well constrained but material representing the 17O,18O-rich end-member is rare. Self-shielding models predict that cometary water, presumed to represent this reservoir, should be enriched in 17O and 18O by greater than 200 per mille. The high-carbon hydrated IDPs may be among the best materials available to search for preserved "cometary" H2O signatures. In order to better understand the origin and evolution of these particles, we have obtained 10 hydrated interplanetary dust particles for coordinated mineralogical, isotopic and organic analyses. We have previously reported the results of mineralogical and O isotopic measurements of two hydrated IDPs; here we present results of O isotopic measurements of three additional IDPs. Samples and Methods: Three interplanetary dust particles (L2079C35, L2083D46 and L2083E46) were embedded in S and partially ultramicrotomed into approximately 70 nanometer sections for analysis via transmission electron microscopy (TEM). The remainders of the unsliced particles were removed from S and pressed into high purity Au foil that was cleaned with HF acid and annealed at 800 degrees Centigrade. The pressed IDPs were analyzed via electron microprobe analysis (EPMA) for quantitative bulk chemical analysis. After EPMA analysis, the IDPs were subjected to precision O isotope analysis with the UCLA Cameca IMS-1270 ion probe. A 20 kiloelectronvolt, 0.5 nanoangstrom Cs+ primary beam of approximately 15 micrometers diameter was used for each measurement. Small particles of San Carlos olivine and Burma spinel were pressed into the Au foil for use as standards to correct for instrumental mass fractionation. The detection system was configured for multicollection, with 16O measured on a Faraday cup, and 17O and 18O measured on electron multipliers (EMs). Individual analyses consisted of 15 cycles of 10 seconds per cycle. Additionally, two microtome thin sections were measured for H isotopic compositions with the JSC NanoSIMS 50L ion probe. An 8 picoangstrom, 16 kiloelectronvolt Cs plus primary beam was used. Measurements consisted of H, C, 12C, 16O, and 18O collected with EMs in multicollection. Terrestrial biotite and kerogen were used for isotopic standards. A significant challenge in O isotope measurement of hydrated minerals is the interference from 16OH at mass 17O. We ensured that the 17O and 16OH peaks were fully resolved by using a mass resolution of greater than 7000 and by careful analyses of San Carlos olivine, Burma spinel and chlorite hydrated mineral standards. The hydride was further suppressed with a cold finger attached to an LN2 dewar to trap volatiles in the sample chamber. All sputtered ions were counted (i.e. presputtering was not used); after applying background, yield and deadtime corrections, we performed a change-point analysis on our data via R in order to determine when the sample reached sputtering equilibrium; data points collected prior to the change point were excluded. Change-point analysis was also used to determine whether the IDP had completely sputtered. Results: Mineralogy. IDPs C35 and E46 exhibited hydrated mineralogies, Fe-Ni sulfide grains, nanoglobules and occasional enstatite grains distributed throughout a fine-grained Mg-Fe saponite matrix. C35 also contained breunnerite (Mg,Fe)CO3; solar flare tracks were observed in enstatite, indicating minimal atmospheric entry heating. The mineralogy of D46 is dominated by a large FeS grain with a minor component of adhering silicate material. D46 was strongly heated during atmorpheric entry as evidenced by a well-developed magnetite rim. EPMA analyses show that both C35 and E46 have high carbon contents of 20 weight percentage (approximately 6X CI). D46 contains approximately 6 wt.weight percentage C. A significant amount of the carbon is present as carbon nanoglobules. Results: Hydrogen isotopes: Although the bulk delta D values of both sections of L2079C35 were within error of SMOW (minus 33 plus or minus 19 per mille, 1 plus or minus 14 per mille 1 sigma), several delta D-rich hotspots were also identified, reaching 2000 per mille. As shown in Fig. 1, these hotspots are clearly associated with discrete carbonaceous inclusions that are akin to nanoglobules found in many meteorites and other IDPs. Oxygen Isotopes. Results of the oxygen isotope measurements are shown in Figure 1. The oxygen isotope composition for L2079C35 was delta 18O equals plus11.6 plus or minus 1.9per mille, delta 17O equals plus 7.9 plus or minus 1.9per mille (2 standard errors). The oxygen isotope composition for L2083D46 was delta 18O equals minus 8.1 plus or minus 1.9 per mille, delta 17O equals minus 6.4 plus or minus 3.1 per mille (2 standard errors). The oxygen isotope composition for L2083E46 was delta 18O equals plus 12.0 plus or minus 1.9 per mille, delta 17O equals plus 9.2 plus or minus 2.0 per mille (2 standard errors). Discussion: Despite mineralogical similarities to highly aqueously altered carbonaceous chondrites, the hydrated IDPs we analyzed have oxygen isotopic compositions that are distinct from matrix materials in the CI, CM, and CR chondrites. The IDPs plot along the Young-Russell line, with delta 17O values for C35 and E46 suggestive of interaction with a 16O-poor reservoir. However, we have thus far not observed evidence of extreme 16O-poor reservoirs expected from self-shielding models and observed in Acfer 094 simplectite. The high carbon contents of the IDPs also set them apart from known meteoritic samples. The lack of atmospheric entry heating effects are consistent with low encounter velocities and suggest either an asteroidal source, or a low inclination, low eccentricity cometary origin. Conclusions: The unusual oxygen isotopic compositions, high carbon contents, and the abundance of Drich nanoglobules, together, suggest that the high-carbon, hydrated IDPs are derived from a primitive source that is not yet represented in meteorite collections.

Snead, C. J.↗