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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

imaging spectroscopy↗
DOE OSTI2023

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Factor analysis and predictive validity of microcomputer-based tests

11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

Non-NASA Center↗
NASA NTRS2019

The Terrestrial Organism and Biogeochemistry Spatial Sampling Design for the National Ecological Observatory Network

The National Ecological Observatory Network (NEON) seeks to facilitate ecological prediction at a continental scale by measuring processes that drive change and responses at sites across the United States for thirty years. The spatial distribution of observations of terrestrial organisms and soil within NEON sites is determined according to a “design‐based” sample design that relies on the randomization of sampling locations. Development of the sample design was guided by high‐level NEON objectives and the multitude of data products that will be subjected to numerous analytical approaches to address the causes and consequences of ecological change. A requirement framework permeates the NEON design, ensuring traceability from each facet of the design to the high‐level requirements that make the NEON mission statement actionable. Requirements were developed for the terrestrial sample design to guide the key components of the design: Randomizing the sample locations ensures the unbiased collection of data, is appropriate for organisms and soil, and provides data suitable for a variety of analyses. Stratification increases efficiency and allows sampling to focus on those parts of the landscape measured by other NEON observation platforms. Attention to the sample size and spatial plot allocation ensures that data products will be sufficient to inform questions asked of the data and the NEON objectives. Establishing a framework with the capacity for re‐evaluate and design iteration allows for adaption to unexpected challenges and optimization of the sample design based on early data returns. The utility of the NEON sampling design is highlighted by its application across terrestrial systems. The data generated from this unique design will be used to quantify patterns in: the abundance and diversity of small mammals, breeding birds, insects, and soil microbes; vegetation structure, biomass, productivity, and diversity; and soil biogeochemistry.

National Ecological Observatory Network↗
NASA NTRS1979

Optimal estimator model for human spatial orientation

A model is being developed to predict pilot dynamic spatial orientation in response to multisensory stimuli. Motion stimuli are first processed by dynamic models of the visual, vestibular, tactile, and proprioceptive sensors. Central nervous system function is then modeled as a steady-state Kalman filter which blends information from the various sensors to form an estimate of spatial orientation. Where necessary, this linear central estimator has been augmented with nonlinear elements to reflect more accurately some highly nonlinear human response characteristics. Computer implementation of the model has shown agreement with several important qualitative characteristics of human spatial orientation, and it is felt that with further modification and additional experimental data the model can be improved and extended. Possible means are described for extending the model to better represent the active pilot with varying skill and work load levels.

Borah, J.↗
NASA NTRS1995

The Barberplaid illusion: Even Perceived Plaid Motion is Biased by Asymmetric Apertures

Our results show that the perceived direction of motion of plaids windowed by asymmetric spatial Gaussians is biased toward the long axis of the window. The bias increases as the relative angle between the plaid motion and the window increases, peaks at a relative angle of about 40 degrees, and then decreases. The peak bias was 14 degrees for a spatial frequency of 0.6 cpd and a window aspect ratio of 4.0. The biases increase as the window is elongated and decrease as the component spatial frequency increases. We tested the predictions of several models of human motion processing (cross correlation, motion energy, intersection of constraints, and vector sum), and show that none of these can predict our data. These results suggest that spatial integration of motion signals plays a crucial role in the perception of plaid motion.

Beutter, Brent↗
NASA NTRS1992

First results from analysis of coordinated AVIRIS, TIMS, and ISM (French) data for the Ronda (Spain) and Beni Bousera (Morocco) peridotites

Ultramafic rocks are relatively rare at the Earth's surface but constitute the vast majority of the Earth by volume. Exposures of ultramafic bodies are therefore crucial for deducing many important processes that occur in the Earth's mantle. An important science question regarding the spatial distribution, abundance, and composition of mafic minerals in ultramafic bodies that can be examined with advanced sensor data is the melting process. When a lherzolite melts, clinopyroxene (cpx) melts first and therefore variations in the modal amount of cpx remaining in the mantle are a reflection of the amount of fractional melting that has occurred. Fe goes preferentially into the melt during melting but a 20 percent batch melting (i.e. closed system) acquires less Fe relative to 20 percent fractional melting (i.e. open system). Since the strength and wavelength of diagnostic absorptions is a strong function of Fe content, it is possible to make maps of the variation in Fe:Mg ratios which can be related to the general melting process. Accurate ground-truth information about local mineralogy provides internal calibration and consistency checks. Investigations using imaging spectrometer are very complementary to field studies because advanced sensor data can provide a synoptic view of modal mineralogy and chemical composition whereas field studies focus on detailed characterization of local areas. Two excellent exposures of ultramafic lithologies are being investigated with visible to mid-infrared imaging spectrometer data: the Ronda peridotite near Ronda, Spain and the Beni Bousera ophiolitic fragment in northern Morocco. Although separated by the Alboran Sea, these bodies are thought to be related and represent fertile sub-continental mantle. The Ronda peridotite is predominantly spinel lherzolite but grades into harzburgite and shows considerable variation in major and trace element compositions. Mafic layering and dykes (i.e. olivine gabbro) are also observed. This indicates some sections of the peridotite have experienced greater degrees of partial melting. The Beni Bousera peridotite also contains mafic layers and dykes and grades into harzburgite representing similar fundamental shifts in the bulk chemistry of this ultramafic body probably related to an episode of partial melting. The specific mode of emplacement of these bodies is controversial and important for understanding the tectonic evolution of this region. Our investigations are not necessarily designed to help resolve this controversy. Rather, these exposures provide excellent and unusual examples of fertile mantle which have undergone variable degrees of partial melting.

Mustard, J. F.↗
NASA NTRS1983

User alternatives in post-processing for raster-to-vector conversion

A number of Landsat-based coniferous forest stratum maps have been created of the Eldorado National Forest in California. These maps were produced in raster image format which is not directly usable by the U.S. Forest Service's vector-based Wildland Resource Information System (WRIS). As a solution, raster-to-vector conversion software has been developed for processing classified images into polygonal data structures. Before conversion, however, the digital classification images must be simplified to remove high spatial variance ('noise', 'speckle') and meet a USFS ten acre minimum requirement. A post-processing (simplification) strategy different from those commonly used in raster image processing may be desired for preparing maps for conversion to vector format, because simplification routines typically permit diagonal connections in the process of reclassifying pixels and forming new polygons. Diagonal connections are often undesirable when converting to vector format because they permit polygons to effectively cross over each other and occupy a common location. Three alternative methodologies are discussed for simplifying raster data for conversion to vector format.

Logan, T. L.↗
NASA NTRS2011

A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Shi, Y.↗
NASA NTRS1990

Evaluation of the airborne visible-infrared imaging spectrometer for mapping subtle lithological variation

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), flown aboard the NASA ER-2 aircraft in 1987 and 1989, used four linear arrays and four individual spectrometers to collect data simultaneously from the 224 bands in a scanned 614 pixel-wide swath perpendicular to the aircraft direction. The research had two goals. One was to evaluate the AVIRIS data. The other was to look at the subtle lithological variation at the two test sites to develop a better understanding of the regional geology and surficial processes. The geometric characteristics of the data, adequacy of the spatial resolution, and adequacy of the spectral sampling interval are evaluated. Geologic differences at the test sites were mapped. They included lithological variation caused by primary sedimentary layering, facies variation, and weathering; and subtle mineralogical differences caused by hydrothermal alterations of igneous and sedimentary rocks. The investigation used laboratory, field, and aircraft spectral measurements; known properties of geological materials; digital image processing and spectrum processing techniques; and field geologic data to evaluate the selected characteristics of the AVIRIS data.

Kruse, Fred A.↗
DOE OSTI2021

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗
DOE OSTI2025

Initial Stage of Nanoscale Imaging in Positive Tone Extreme UV Photoresists: The Influence of the Polymer Sequence

Photolithographic patterning using extreme ultraviolet (EUV, 92.5 eV) light is a radiolytic process that initially forms electrons, radical cations, anions, and neutral radicals in the polymeric photoresist matrix. These species may participate in the chemical reactions that define the ultimate resolution of the printed image, and their concentrations and nanometer-scale stochastic variations in their formation influence printed image quality. Proposals have been made that polymer chain uniformity may be advantageous in reducing stochastics due to spatial inhomogeneities, and this aspect of radiolysis is examined in this work. We have simulated the initial subpicosecond stages of the imaging process for a series of photoresist films that are identical in composition but vary in their polymer chain structures. We use detailed, physically accurate stochastic reaction-diffusion calculations to evaluate the influence of defined sequence and random copolymer structures on radiolytic spur formation, i.e., a cluster of species formed by electron-polymer interactions that defines the initial spatial characteristic of the imaging process. Predictions of electron thermalization in the present work are shown to be consistent with the literature, indicating that our overall computational approach for ultrafast nanoscale processes is sound. The computational results show that the polymer sequence has no significant effect on the spur composition. This suggests that any potential imaging improvements to be gained by sequence control must originate from postimaging lithographic process steps.

Absorption↗
DOE OSTI2022

Fatigue crack growth resistance of a mesoscale composite microstructure Haynes 282 fabricated via electron beam melting additive manufacturing

Materials synthesis via additive manufacturing gives unprecedented control over the solidified microstructure. While a number of studies have demonstrated the ability to produce spatially varying microstructures, little work exists to understand the behavior of such “composite” materials. In this work, we utilized electron beam melting to process Ni-based superalloy Haynes 282 and produce compact tension samples with a spatially varying mesoscale structure. Fatigue crack growth experiments reveal that the crack growth rate is dependent on the degree of microstructural heterogeneity. This work demonstrates that the crack growth resistance can be tailored within a component using electron beam melting additive manufacturing.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Spatial analysis of IRAS observations of nearby spirals

The unbiased survey of the infrared sky carried out by the Infrared Astronomy Satellite (IRAS) satellite has greatly accelerated advances in understanding the dust component of our own and external galaxies. However, most extragalactic studies to date have been based on the IRAS Point Source Catalog (PSC), which has two serious limitations. First, in sources where a significant fraction of the flux is extended, significant errors may result from using PSC fluxes in comparative studies, and these errors could be systematic if the tendency to be non-pointlike depends on physical properties of the galaxy. Additionally, use of PSC fluxes rules out any direct investigation of the spatial distribution of the IRAS emission from disks in external galaxies. Since work on the Galactic IRAS results has shown that very different physical processes can make varying contributions to the observed flux, it is important to look at a wide sample of galaxies with some spatial resolution to study the relative dominance of these processes under a variety of conditions. Here, researchers report on work they are doing to carry out this program for many nearby spirals, using an analysis package that was developed for this purpose. Researchers carried out analysis for a sample of 121 nearby spirals. The fraction of the flux contained in a point source varies from 0 to 1 across the sample, all of which are well resolved at their nominal optical diameters. There is no evidence that the galaxies of smaller angular size are less likely to be resolved by IRAS at this level. The program gives results which are quite repeatable from scan to scan; the fraction f (point source flux over total flux) at 60 microns has typical errors of 0.03 when different scans are combined. Approximately two-thirds of the sample have more flux in the extended than in the nuclear component. There is a tendency for earlier-type spirals to be less centrally concentrated, but this effect is slight and the degree of variation is large for all types. Barred spirals are also found across the spectrum of f, but are much more likely to have little or no nuclear emission.

Ball, Roger↗
NASA NTRS2010

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Dungan, Jennifer L.↗
DOE OSTI2020

Reaction heterogeneity in practical high-energy lithium–sulfur pouch cells

The lithium–sulfur (Li–S) battery is a promising next-generation energy storage technology because of its high theoretical energy and low cost. Extensive research efforts have been made on new materials and advanced characterization techniques for mechanistic studies. However, it is uncertain how discoveries made on the material level apply to realistic batteries due to limited analysis and characterization of real high-energy cells, such as pouch cells. Evaluation of pouch cells (>1 A h) (instead of coin cells) that are scalable to practical cells provides a critical understanding of current limitations which enables the proposal of strategies and solutions for further performance improvement. Herein, we design and fabricate pouch cells over 300 W h kg -1 , compare the cell parameters required for high-energy pouch cells, and investigate the reaction processes and their correlation to cell cycling behavior and failure mechanisms. Spatially resolved characterization techniques and fluid-flow simulation reveal the impacts of the liquid electrolyte diffusion within the pouch cells. We found that catastrophic failure of high-energy Li–S pouch cells results from uneven sulfur/polysulfide reactions and electrolyte depletion for the first tens of cycles, rather than sulfur dissolution as commonly reported in the literature. The uneven reaction stems from limited electrolyte diffusion through the porous channels into the central part of thick cathodes during cycling, which is amplified both across the sulfur electrodes and within the same electrode plane. A combination of strategies is suggested to increase sulfur utilization, improve nanoarchitectures for electrolyte diffusion and reduce consumption of the electrolytes and additives.

25 ENERGY STORAGE↗
NASA NTRS1992

Measurement of subresolution terrain displacements using SPOT panchromatic imagery

SPOT panchromatic imagery is used to measure subresolution horizontal terrain displacements that are associated with earthquakes, sand dune migration, coastal processes, and glacial motion. The approach is aimed at detecting and measuring surface processes by statistically matching the radiometric patterns in the data that differ spatially in a consistent direction over many pixels. Data obtained from the satellite-derived imagery can facilitate the understanding of natural hazards and the determination of the rates of many environmental processes worldwide.

Crippen, Robert E.↗
NASA NTRS2014

X-Ray Micro-Computed Tomography of Apollo Samples as a Curation Technique Enabling Better Research

X-ray micro-computed tomography (micro-CT) is a technique that has been used to research meteorites for some time and many others], and recently it is becoming a more common tool for the curation of meteorites and Apollo samples. Micro-CT is ideally suited to the characterization of astromaterials in the curation process as it can provide textural and compositional information at a small spatial resolution rapidly, nondestructively, and without compromising the cleanliness of the samples (e.g., samples can be scanned sealed in Teflon bags). This data can then inform scientists and curators when making and processing future sample requests for meteorites and Apollo samples. Here we present some preliminary results on micro-CT scans of four Apollo regolith breccias. Methods: Portions of four Apollo samples were used in this study: 14321, 15205, 15405, and 60639. All samples were 8-10 cm in their longest dimension and approximately equant. These samples were micro-CT scanned on the Nikon HMXST 225 System at the Natural History Museum in London. Scans were made at 205-220 kV, 135-160 microamps beam current, with an effective voxel size of 21-44 microns. Results: Initial examination of the data identify a variety of mineral clasts (including sub-voxel FeNi metal grains) and lithic clasts within the regolith breccias. Textural information within some of the lithic clasts was also discernable. Of particular interest was a large basalt clast (approx.1.3 cc) found within sample 60639, which appears to have a sub-ophitic texture. Additionally, internal void space, e.g., fractures and voids, is readily identifiable. Discussion: It is clear from the preliminary data that micro-CT analyses are able to identify important "new" clasts within the Apollo breccias, and better characterize previously described clasts or igneous samples. For example, the 60639 basalt clast was previously believed to be quite small based on its approx.0.5 sq cm exposure on the surface of the main mass. These scans show the clast to be approx.4.5 g, however (assuming a density of approx.3.5 g/cc). This is large enough for detailed studies including multiple geo-chronometers. This basalt clast is of particular interest as it is the largest Apollo 16 basalt, and it is the only mid-TiO2 basalt in the Apollo sample suite. By identifying the location of interesting clasts or grains within a sample, we will be able to make more informed decisions about where to cut a sample in order to best expose clasts of interest for future study. Moreover, knowing the location of internal defects (e.g., fractures) will allow more precise chipping and extraction of clasts or grains. By combining micro-CT scans with compositional techniques like micro x-ray fluorescence (particularly on sawn slabs), we will be able to provide even more comprehensive information to scientists trying to best select samples that fit their scientific needs.

Ziegler, R. A.↗