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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

grain number↗
NASA NTRS1999

"Electrostructural Phase Changes" In Charged Particulate Clouds: Planetary and Astrophysical Implications

There is empirical evidence that freely-suspended triboelectrostatically charged particulate clouds of dielectric materials undergo rapid conversion from (nominally) monodispersed "aerosols" to a system of well-defined grain aggregates after grain motion or fluid turbulence ceases within the cloud. In United States Microgravity Laboratory Space Shuttle experiments USML-1 and USML-2, it was found that ballistically-energized grain dispersions would rapidly convert into populations of filamentary aggregates after natural fluid (air) damping of grain motion. Unless continuously disrupted mechanically, it was impossible to maintain a non-aggregated state for the grain clouds of sand-size materials. Similarly, ground- based experiments with very fine dust-size material produced the same results: rapid, impulsive "collapse" of the dispersed grains into well-defined filamentary structures. In both ground-based and microgravity experiments, the chains or filaments were created by long-range dipole electrostatic forces and dipole-induced dielectric interactions, not by monopole interactions. Maintenance of the structures was assisted by short-range static boundary adhesion forces and van der Waals interactions. When the aggregate containers in the USML experiments were disturbed after aggregate formation, the quiescently disposed filaments would rearrange themselves into fractal bundles and tighter clusters as a result of enforced encounters with one another. The long-range dipole interactions that bring the grains together into aggregates are a product of randomly-distributed monopole charges on the grain surfaces. In computer simulations, it has been shown that when the force vectors of all the random charges (of both sign) on a grain are resolved mathematically by assuming Coulombic interaction between them, the net result is a dipole moment on individual grains, even though the grains are electrically neutral insofar as there is no predominance, on their surface, of one charge sign over another. The random charges of both sign derive from natural grain-to-grain interactions that produce triboelectrification via charge exchange every time grain surfaces make contact with one another. The conversion from a random distribution of grains (upon which there are randomly distributed charges) into an organization of electrostatically-ordered aggregates, can be regarded (within the framework of granular-material science) as an "electrical or Coulombic phase change" of the particulate cloud. It is not totally dissimilar from the more normal phase-change concept in which, for example, a gas with long free-path-molecules suddenly becomes a solid as a result of structural ordering of the molecules (notably, also the result of electronic forces, albeit at a different scale). In both the gas-to-solid case, and the aerosol-to-aggregate case, the same materials and charges are present before and after the phase change, but their arrangement now has a higher degree of order and a lower-energy configuration. An input of energy into the system is required to reverse the situation. The aggregates in the USML experiments were observed to undergo at least two phase changes as noted above. The point about phase changes, and by implication, the "electrostructural" reorganizations in particulate clouds, is the following: (a) they can occur very rapidly, almost spontaneously, above a critical cloud density, (b) in going from a higher energy state to a lower energy state, they convert to a denser system, (c) energy must be required to reverse the situation, implying that energy is released during the high-to-low energy phase change. In applying this information to natural particulate clouds, some inferences can be made (it is stressed that reference is still to dielectric materials attracted by dipole forces). There are several natural settings to which the USML observations apply, and to which the phase-change implications likewise apply. Dense clouds of triboelectrically-charged, kinetically-energized grains are to be found in volcanic eruptions (particularly on earth), aeolian dust storms (particularly on Mars), meteorite impact ejecta curtains (on all planets), in "immature" debris rings around planets (e.g., that from which our own Moon may have condensed), and in gravitationally collapsing protoplanetary dust/planetesimal debris disks where dielectric granules are being increasingly brought into collisional relationships with one another (increasing both charge exchange and physical proximity). It is noted that in many of these cases, the degree of electrical charging on the grains is likely to be much higher than that in the USML experiments where charging was not enhanced above the "normal", naturally encountered level for the particular materials (quartz, glass, and various silicate minerals). Application of the phase-change concept suggests that volcanic, aeolian, and impact debris clouds may, under certain circumstances, undergo rapid, impulsive, or even catastrophic collapse into a denser state that will lead to rapid precipitation or fall-out of suspended particulates. Although this idea has been suggested previously by the author , the phase change concept possibly permits some new insights into cloud-system behavior. For example, in a protoplanetary debris disk, the work of gravity may suddenly be enhanced by electrostatically driven collapse of the system when materials reach a critical intergranular spacing or grain number density. This might reduce the rate of planet formation by orders of magnitude (considering the ratio of g-forces to electrostatic ones for very small grains in close proximity), and indeed, it might drive the collapse into a system configuration that would perhaps not be created by gravity alone. Additional information is contained in the original.

Marshall, J. R.↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗
NASA NTRS1973

Electron Microprobe Analyses of Lithic Fragments and Their Minerals from Luna 20 Fines

The bulk analyses (determined with the broad beam electron microprobe technique) of lithic fragments are given in weight percentages and are arranged according to the rock classification. Within each rock group the analyses are arranged in order of increasing FeO content. Thin section and lithic fragment numbers are given at the top of each column of analysis and correspond to the numbers recorded on photo mosaics on file in the Institute of Meteoritics. CIPW molecular norms are given for each analysis. Electron microprobe mineral analyses (given in oxide weight percentages), structural formulae and molecular end member values are presented for plagioclase, olivine, pyroxene and K-feldspar. The minerals are selected mostly from lithic fragments that were also analyzed for bulk composition. Within each mineral group the analyses are presented according to the section number and lithic fragment number. Within each lithic fragment the mineral analyses are arranged as follows: Plagioclase in order of increasing CaO; olivine and pyroexene in order of increasing FeO; and K-feldspar in order of increasing K2O. The mineral grains are identified at the top of each column of analysis by grain number and lithic fragment number.

Conrad, G. H.↗
DOE OSTI2024

Modeling the Enceladus dust plume based on in situ measurements performed with the Cassini Cosmic Dust Analyzer

We analyzed data recorded by the Cosmic Dust Analyzer on board the Cassini spacecraft during Enceladus dust plume traversals. Our focus was on profiles of relative abundances of grains of different compositional types derived from mass spectra recorded with the Dust Analyzer subsystem during the Cassini flybys E5 and E17. The E5 profile, corresponding to a steep and fast traversal of the plume, has already been analyzed. In this paper, we included a second profile from the E17 flyby involving a nearly horizontal traversal of the south polar terrain at a significantly lower velocity. Additionally, we incorporated dust detection rates from the High Rate Detector subsystem during flybys E7 and E21. We derived grain size ranges in the different observational data sets and used these data to constrain parameters for a new dust plume model. This model was constructed using a mathematical description of dust ejection implemented in the software package DUDI. Further constraints included published velocities of gas ejection, positions of gas and dust jets, and the mass production rate of the plume. Our model employs two different types of sources: diffuse sources of dust ejected with a lower velocity and jets with a faster and more colimated emission. From our model, we derived dust mass production rates for different compositional grain types, amounting to at least 28 kg s –1 . Previously, salt-rich dust was believed to dominate the plume mass based on E5 data alone. The E17 profile shows a dominance of organic-enriched grains over the south polar terrain, a region not well constrained by E5 data. By including both E5 and E17 profiles, we find the salt-rich dust contribution to be at most 1% by mass. This revision also results from an improved understanding of grain masses of various compositional types that implies smaller sizes for salt-rich grains. Our new model can predict grain numbers and masses for future mission detectors during plume traversals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Sorghum SbGhd7 is a major regulator of floral transition and directly represses genes crucial for flowering activation

Molecular genetic understanding of flowering time regulation is crucial for sorghum development. GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (SbGhd7) is one of the six classical loci conferring photoperiod sensitivity of sorghum flowering. However, its functions remain poorly studied. The molecular functions of SbGhd7 were characterized. The gene regulatory network controlled by SbGhd7 was constructed and validated. The biological roles of SbGhd7 and its major targets were studied. SbGhd7overexpression (OE) completely prevented sorghum flowering. Additionally, we show thatSbGhd7is a major negative regulator of flowering, binding to the promoter motif TGAATG(A/T)(A/T/C) and repressing transcription of the major florigen FLOWERING LOCUS T 10(SbFT10) and floral activators EARLY HEADING DATE(SbEhd1),FLAVIN-BINDING,KELCH REPEAT,F-BOX1(SbFKF1) and EARLY FLOWERING 3(SbELF3). Reinforcing the direct effect ofSbGhd7,SbEhd1OE activated the promoters of three functional florigens (SbFT1,SbFT8andSbFT10), dramatically accelerating flowering. Here our studies demonstrate that SbGhd7 is a major repressor of sorghum flowering by directly and indirectly targeting genes for flowering activation. The mechanism appears ancient. Our study extends the current model of floral transition regulation in sorghum and provides a framework for a comprehensive understanding of sorghum photoperiod response.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

The Extreme 2016 Wheat Failure in France

France suffered in 2016 the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.

Extreme weather↗
NASA NTRS1999

The Mars Environmental Compatibility Assessment MECA Abrasion Tool

The Mars Environmental Compatibility Assessment (MECA) experiment, an instrument suite to be flown on Mars Surveyor 2001, will include a tool for doing simple mineralogical scratch and streak tests on particles from the Martian regolith. The Abrasion Tool will be applied to particles that adhere to highly polished substrates of various hardnesses. Granular soil components will be subjected to a compressive force of about 3 N using a leaf spring. The spring will be applied with a paraffin actuator capable of a 0.76 mm throw to achieve a maximum displacement of about 7.5 mm at the tip of the tool. The pressure per grain will be dependent on the grain size, the number of grains that adhere to the substrate and the number of grains in compression. The pressure per particle is expected to be on the order of 100 MPa - 1 GPa. The MECA sample wheel containing the substrates will be rotated after the particles are placed in compression to produce scratches or pits. A primary goal of the Abrasion Tool is to identify quartz (Mohs' hardness = 7) using substrates of varying hardnesses. Quartz is considered hazardous to future human explorers of Mars because it can cause silicosis of the lungs if it is of respirable size. It is also hazardous to machinery, structures, and space suits because of its ability to abrade and scratch surfaces. Since large quantities of minerals harder than quartz are not expected, any scratches produced on polished quartz substrates might be reasonably attributed to quartz particles, although there may be minerals such as impact metamorphic diamond in the soils. Careful calibration of the tool will be necessary to ensure that grains are not overloaded; for example, a steel ball pressed into glass will produce a Hertzian fracture, even though it is softer than glass. Other minerals, such as magnetite (Mohs'hardness = 6.5) have been shown to scratch glass ceramics such as Zerodur (Mohs' hardness = 6.5). Thus, minerals can be differentiated: note that regardless of the mineral species, if any particle is harder than 6.5 it will certainly be an interesting discovery for both planetary geology and human exploration concerns. The scratches will be identified using the 6X optical microscope and profiled with the atomic force microscope included in the MECA instrument suite. Analysis of the scratch morphology will yield evidence concerning the shape of the particle responsible for producing each scratch. For example, angular grains should leave vertical cracks with microconchoidal lateral chipping, while rounded grains might leave chattermarks, or nested partial Hertzian cracks. Particle shape can thus be inferred from these indentation modes, as well as material hardness. In addition, particle size information may also be available if pits caused by rolling particles can be identified. Converse to scratching, the minerals may be crushed at their contact points, and be smeared onto the target substrates to leave what geologists refer to as "streaks". These are coldwelded trails of mineral material that have structure and color indicative of mineral composition. The AFM will determine the morphology of these streaks, while the microscope will ascertain the color. On the harder substrates, we might expect streaking to dominate; on the softer substrates, scratching may dominate. Progressions of material interactions across the substrate selection will be a valuable source of data for mineral discrimination. It should also be noted that many minerals have coatings (such as iron oxides), and these will have to be differentiated from the host mineral grains; laboratory tests will establish the effects of such coatings on the scratch results. Finally, we note that the microscope will provide corroborative data regarding likely mineral species by grain shapes, fracture patterns, surface textures, colr, and UV fluorescence reactions.

Kuhlman, K. R.↗
NASA NTRS1999

The Mars Environmental Compatibility Assessment (MECA) Abrasion Tool

The Mars Environmental Compatibility Assessment (MECA) experiment, an instrument suite to be flown on Mars Surveyor 2001, will include a tool for doing simple mineralogical scratch and streak tests on particles from the Martian regolith. The Abrasion Tool will be applied to particles that adhere themselves to highly polished substrates of various hardnesses. Granular soil components will be subjected to a compressive force of about 3 N using a leaf spring. The spring will be applied with a paraffin actuator capable of a 0.76 mm throw to achieve a maximum displacement of about 7.5 mm at the tip of the tool. The pressure per grain will be dependent on the grain size, the number of grains that adhere to the substrate and the number of grains in compression. The pressure per particle is expected to be on the order of 100 MPa - 1 GPa. The MECA sample wheel containing the substrates will be rotated after the particles are placed in compression to produce scratches or pits. A primary goal of the Abrasion Tool is to identify quartz (Mohs' hardness = 7) using substrates of varying hardnesses. Quartz is considered hazardous to future human explorers of Mars because it can cause silicosis of the lungs if it is of respirable size. It is also hazardous to machinery, structures, and space suits because of its ability to abrade and scratch surfaces. Since large quantities of minerals harder than quartz are not expected, any scratches produced on polished quartz substrates might be reasonably attributed to quartz particles, although there may be minerals such as impact metamorphic diamond in the soils. Careful calibration of the tool will be necessary to ensure that grains are not overloaded; for example, a steel ball pressed into glass will produce a Hertzian fracture, even though it is softer than glass. Other minerals, such as magnetite (Mohs' hardness = 6.5) have been shown to scratch glass ceramics such as Zerodur (Mohs' hardness = 6.5). Thus, minerals can be differentiated: note that regardless of the mineral species, if any particle is harder than 6.5 it will certainly be an interesting discovery for both planetary geology and human exploration concerns. The scratches will be identified using the 6X optical microscope and profiled with the atomic force microscope included in the MECA instrument suite. Analysis of the scratch morphology will yield evidence concerning the shape of the particle responsible for producing each scratch. For example, angular grains should leave vertical cracks with microconchoidal lateral chipping, while rounded grains might leave chatter marks, or nested partial Hertzian cracks. Particle shape can thus be inferred from these indentation modes, as well as material hardness. In addition, particle size information may also be available if pits caused by rolling particles can be identified. Converse to scratching, the minerals may be crushed at their contact points, and be smeared onto the target substrates to leave what geologists refer to as "streaks". These are cold-welded trails of mineral material that have structure and color indicative of mineral composition. The AFM will determine the morphology of these streaks, while the microscope will ascertain the color. On the harder substrates, we might expect streaking to dominate; on the softer substrates, scratching may dominate. Progressions of material interactions across the substrate selection will be a valuable source of data for mineral discrimination. It should also be noted that many minerals have coatings (such as iron oxides), and these will have to be differentiated from the host mineral grains; laboratory tests will establish the effects of such coatings on the scratch results. Finally, we note that the microscope will provide corroborative data regarding likely mineral species by grain shapes, fracture patterns, surface textures, color, and UV fluorescence reactions. Additional information is contained in the original extended abstract.

Kuhlman, K. R.↗
NASA NTRS1990

Influence of low-gravity solidification on heterogeneous nucleation in stable iron-carbon alloys

The effect of gravity on the processes of nucleation and growth of Fe-C alloys during directional solidification was investigated in experiments in which inoculated and uninoculated samples of an alloy of the gray iron type were solidified on ground (1 g) and under the low-gravity (low-g) and high-gravity (high-g) conditions obtained by aircraft parabolic flights. It was found that a higher number of grains was obtained during solidification in high-g condition, due to higher convection in high-g. It was demonstrated that grain multiplication due to convection can contribute up to 23 percent of the total number of grains resulting from heterogeneous nucleation of uninoculated samples. For the case of inoculated samples, it was found that the contribution of the convection-induced nucleation can be as high as 30 percent, but can be zero at very low or very high grain numbers.

Tian, Huameng↗
DOE OSTI2023

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of 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 OSTI2025

The role of specimen size and grain boundary characteristics in the yield strength of tungsten in microtensile tests

To effectively use the measured properties from small-scale tensile tests for bulk material performance predictions, it is essential to understand the threshold of specimen size-effect strengthening and the interaction between dislocations and microstructures within miniaturized specimens. This study uses pure tungsten to investigate the size effect in terms of specimen size, grain size, and grain boundary characteristics relative to the yield strength of tungsten at room temperature. We evaluate the transition from miniaturized specimen properties to bulk properties and the deformation behavior through small-scale tensile tests of three specimen sizes (large: 80 × 100 × 233 µm³; medium: 7 × 7 × 18 µm³; and small: 2 × 2 × 5 µm³). The testing results reveal that the small and medium specimens exhibit high yield strength with ductile behavior, while the large specimens exhibit brittle failure, consistent with the room temperature strength of tungsten, indicating bulk behavior. We further explore the specimen size-effect sensitivity to yield stress and the scaling relationship between yield strength and the number of grains involved in the deformation. A power-law relationship with the exponent value of approximately -0.5 was found in the yield strength–grain number scaling, implying the Hall-Petch like behavior. A minimum of 7–17 effective grain boundaries across the tensile gauge dimension is required to accurately measure bulk properties.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Anisotropic physics-regularized interpretable machine learning of microstructure evolution

Anisotropic Physics-Regularized Interpretable Machine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its neighboring sites to model normal, isotropic, grain growth behavior. This work aims to extend this method by incorporating grain boundary misorientation-based grain growth behavior. APRIMME is trained on anisotropic simulations created using the Monte Carlo-Potts (MCP) model. Furthermore, the results of this work are compared statistically using grain radius, number of sides per grain, mean neighborhood misorientations, and the standard deviation of triple junction dihedral angles, and are found to match in most cases. The exceptions are small and seem to be related to two causes: (1) the deterministic model of APRIMME is learning from the stochastic simulations of MCP, which seems to accentuate triple junction behaviors; and, (2) a bias against very small grains is made evident in a quicker decrease in grains than expected at the beginning of an APRIMME simulation. APRIMME is also evaluated for its general ability to capture anisotropic grain growth behavior by first investigating different test case initial conditions, including a circle grain, three grain, and hexagonal grain microstructures.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Radar observations of Comet Halley

Five nights of Arecibo radar observations of Comet Halley are reported which reveal a feature in the overall average spectrum which, though weak, seems consistent with being an echo from the comet. The large radar cross section and large bandwidth of the feature suggest that the echo is predominantly from large grains which have been ejected from the nucleus. Extrapolation of the dust particle size distribution to large grain sizes gives a sufficient number of grains to account for the echo. The lack of a detectable echo from the nucleus, combined with estimates of its size and rotation rate from spacecraft encounters and other data, indicate that the nucleus has a surface of relatively high porosity.

Campbell, D. B.↗
DOE OSTI2025

Experiments to validate Thermodynamics and Transport models of Strongly Coupled Dusty Plasma Matter (Final Technical Report for DE-SC0023416)

The goal of this two-year grant is to provide access to the PI to dusty plasma experimental facilities at the DOE-funded Collaborative Research Facility Magnetized Plasma Research Laboratory, Auburn University to become a user of that facility, to obtain experimental data to support another ongoing grant DE-SC0021146 (an Early Career Award to the PI that is focused on modeling of dusty plasma thermodynamics and transport processes), to generate experimental data for funding proposals, and to provide exposure to University of Memphis students to advanced experimental techniques. The following technical accomplishments were made: 1. Development of a novel Bidirectional Electrode Control Arms Assembly (BECAA) for producing perfect 2D grain layers for complex plasma experimentation. BECAA uses movable electrode arms to tilt or move the electrode in a RF discharge from outside the chamber, allowing for the manipulation of grain clouds without needing to change the plasma parameters or gas pressure. This work addresses a longstanding gap in the literature for a method to produce clusters of selectable number of grains and that are perfectly two dimensional as opposed to being only quasi-2D. 2. Experimental investigation of the structural properties of finite-N clusters with N=2 to 50. Individual particle behavior in clusters could vary from grain to grain and this study measured systematically produced clusters for two different grain sizes. Analysis (funded by another grant DE-SC0021146) is currently underway to quantify the differences between grains that are found on the surface vs. the interior of clusters, the shell structure, and the decay of correlations in position, velocity, and kinetic energy. 3. An experimental method to measure the structural entropy of clusters was developed by observing the self-induced structural transitions between various possible arrangements. In a series of heating and cooling cycles, the number of times each possible arrangement was attained was experimentally observed and used to compute the probability of existence of that arrangement, and subsequently the configurational entropy of the cluster. Analysis (funded by another grant DE-SC0021146) is currently underway to produce the entropy of clusters as a function of the number of grains and use the same to compute thermodynamic state variables for 2D complex plasma/grain clusters. 4. A preliminary experimental study of multibody collisions between N grains (N=2 – 10) was conducted. The clusters were produced using the BECAA technique and velocities were imparted to the grains using manipulation laser pulses. Analysis (funded by another grant DE-SC0021146) is currently underway to develop a theoretical framework to describe multibody collisions analogous to classical two-body interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Universal behavior in fragmenting brittle, isotropic solids across material properties

A bonded particle model is used to explore how variations in the material properties of brittle, isotropic solids affect critical behavior in fragmentation. To control material properties, a model is proposed which includes breakable two- and three-body particle interactions to calibrate elastic moduli and mode I and mode II fracture toughnesses. In the quasistatic limit, fragmentation leads to a power-law distribution of grain sizes which is truncated at a maximum grain mass that grows as a nontrivial power of system size. In the high-rate limit, truncation occurs at a mass that decreases as a power of increasing rate. A scaling description is used to characterize this behavior by collapsing the mean-square grain mass across rates and system sizes. Consistent scaling persists across all material properties studied, although there are differences in the evolution of grain size distributions with strain as the initial number of grains at fracture and their subsequent rate of production depend on Poisson's ratio. Importantly, this evolving granular structure is found to induce a unique rheology where the ratio of the shear stress to pressure, an internal friction coefficient, decays approximately as the logarithm of increasing strain rate. The stress ratio also decreases at all rates with increasing strain as fragmentation progresses and depends on elastic properties of the solid.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Grain destruction in interstellar shocks

The destruction of interstellar grains by nonthermal sputtering, thermal sputtering, and grain-grain collisions is discussed. It is concluded that large grains are easily destroyed by shocks in the interstellar medium, but that small grains are much more persistent. Since the MRN model has many more small grains than large ones, this means that the total number of grains is not significantly reduced even when half or more of the grain material is returned to the gas phase. Thus, the small grains are always available as condensation cores for mantle formation or redepletion of refractory grain materials.

Seab, C. G.↗