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NASA NTRS1991

Spectral-compositional variations in the constituent minerals of mafic and ultramafic assemblages and remote sensing implications

Chemical compositions of the constituent minerals of 13 mafic and ultramafic assemblages containing from one to five mineral components were analyzed with an electron microprobe, and the compositions were correlated with the reflectance spectra of the samples to determine the spectral-compositional relationships of these assemblages. Results indicate that, as more components are added to a mixture, the quality and quantity of compositional information which can be derived from spectral analysis diminishes. It is shown that opaque minerals (such as magnetite for terrestrial occurrences and ilmenite in lunar assemblages) influence reflectance spectra out of proportion to their abundances, reducing overall reflectance and band depths of mafic silicates in small dispersed amounts.

Cloutis, Edward A.↗

DOE OSTI2024

Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning

Abstract Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of XAS/EELS data often relies on matching an unknown experimental sample to a series of simulated or experimental standard samples. This limits analysis throughput and the ability to extract quantitative information from a sample. In this work, we have trained a random forest model capable of predicting the oxidation state of copper based on its L-edge spectrum. Our model attains an R 2 score of 0.85 and a root mean square error of 0.24 on simulated data. It has also successfully predicted experimental L-edge EELS spectra taken in this work and XAS spectra extracted from the literature. We further demonstrate the utility of this model by predicting simulated and experimental spectra of mixed valence samples generated by this work. This model can be integrated into a real-time EELS/XAS analysis pipeline on mixtures of copper-containing materials of unknown composition and oxidation state. By expanding the training data, this methodology can be extended to data-driven spectral analysis of a broad range of materials.

36 MATERIALS SCIENCE↗

NASA NTRS1977

Comparing soil boundaries delineated by digital analysis of multispectral scanner data from high and low spatial resolution systems

The author has identified the following significant results. Computer-aided analysis techniques used with aircraft MSS data showed that the spatial resolution was sufficient to recognize each soil mapping unit of the test site. Some difficulties occurred where different soil series were intricately mixed, and this mixture showed as a separate spectral mapping unit, or where the difference between two soils depended on the depth of silty surface material. Analysis of LANDSAT data with computer-aided techniques showed that it was not possible to find spectrally homogeneous soil features of the seven soil series on the 40 ha test site on the digital display or on a picture print map. Cluster techniques could be used on an extended test area to group spectrally similar data points into cluster classes.

Kristof, S. J.↗

NASA NTRS2013

Joint M3 and Diviner Analysis of the Mineralogy, Glass Composition, and Country Rock Content of Pyroclastic Deposits in Oppenheimer Crater

Here we present our analysis of the near- and mid-infrared spectral properties of pyroclastic deposits within the floor fractured Oppenheimer Crater that are hypothesized to be Vulcanian in origin. These are the first results of our global study of lunar pyroclastic deposits aimed at constraining the range of eruption processes on the Moon. In the near-infrared, we have employed a new method of spectral analysis developed in Horgan et al. (2013) of the 1 m iron absorption band in Chandrayaan-1 Moon Mineralogy Mapper (M3) spectra. By analyzing both the position and shape of the 1 m band we can detect and map the distribution of minerals, glasses, and mixtures of these phases in pyroclastic deposits. We are also using mid-infrared spectra from the Lunar Reconnaissance Orbiter Diviner Lunar Radiometer Experiment to develop ~200 m/pixel Christiansen Feature (CF) maps, which correlate with silica abundance. One of the benefits of using CF maps for analysis of pyroclastic deposits is that they can be used to detect silicic country rock that may have been emplaced by Vulcanian-style eruptions, and are sensitive to iron abundance in glasses, neither of which is possible in the near-infrared. M3 analysis reveals that the primary spectral endmembers are low-calcium pyroxene and iron-bearing glass, with only minor high-calcium pyroxene, and no detectable olivine. The large deposit in the south shows higher and more extensive glass concentrations than the surrounding deposits. We interpret the M3 spectra of the pyroclastic deposits as indicating a mixture of low-calcium pyroxene country rock and juvenile glass, and no significant olivine. Analysis of Diviner CF maps of the Oppenheimer crater floor indicates an average CF value of 8.16, consistent with a mixture of primarily plagioclase and some pyroxene. The average CF values of the pyroclastic deposits range from 8.31 in the SW to 8.24 in the SE. Since CF values within the deposits are as high as 8.49, the lower average CF values of the deposits suggest that each deposit is a mixture of crater floor material and highly mafic juvenile material consistent with either olivine or Fe-bearing pyroclastic glass. Synthesizing our M3 and Diviner results indicates that the crater floor consists of plagioclase with some pyroxene, and the pyroclastic deposits are a mix of this substrate and a glass-rich juvenile material. While we cannot determine the iron content of the glass from M3 spectra alone, the high Diviner CF values suggest that the glass is relatively iron-rich. Indeed, FeO abundances inferred from CF values using the method of Allen et al. (2012) imply that the large southern deposit exhibits a significant enhancement in iron content. This supports our hypothesis that the glass in this deposit is relatively iron-rich.

Bennett, Kristen A.↗

NASA NTRS2002

Low-Cost Evaluation of EO-1 Hyperion and ALI for Detection and Biophysical Characterization of Forest Logging in Amazonia (NCC5-481)

Major uncertainties exist regarding the rate and intensity of logging in tropical forests worldwide: these uncertainties severely limit economic, ecological, and biogeochemical analyses of these regions. Recent sawmill surveys in the Amazon region of Brazil show that the area logged is nearly equal to total area deforested annually, but conversion of survey data to forest area, forest structural damage, and biomass estimates requires multiple assumptions about logging practices. Remote sensing could provide an independent means to monitor logging activity and to estimate the biophysical consequences of this land use. Previous studies have demonstrated that the detection of logging in Amazon forests is difficult and no studies have developed either the quantitative physical basis or remote sensing approaches needed to estimate the effects of various logging regimes on forest structure. A major reason for these limitations has been a lack of sufficient, well-calibrated optical satellite data, which in turn, has impeded the development and use of physically-based, quantitative approaches for detection and structural characterization of forest logging regimes. We propose to use data from the EO-1 Hyperion imaging spectrometer to greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin. Our approach is based on four "biogeophysical indicators" not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes. Our quantitative assessment of Hyperion hyperspectral and ALI multi-spectral data for the detection and structural characterization of selective logging in Amazonia will benefit from data collected through an ongoing project run by the Tropical Forest Foundation, within which we have developed a study of the canopy and landscape biophysics of conventional and reduced-impact logging. We will add to our base of forest structural information in concert with an EO-1 overpass. Using a photon transport model inversion technique that accounts for non-linear mixing of the four biogeophysical indicators, we will estimate these parameters across a gradient of selective logging intensity provided by conventional and reduced impact logging sites. We will also compare our physical ly-based approach to both conventional (e.g., NDVI) and novel (e.g., SWIR-channel) vegetation indices as well as to linear mixture modeling methods. We will cross-compare these approaches using Hyperion and ALI imagers to determine the strengths and limitations of these two sensors for applications of forest biophysics. This effort will yield the first physical ly-based, quantitative analysis of the detection and intensity of selective logging in Amazonia, comparing hyperspectral and improved multi-spectral approaches as well as inverse modeling, linear mixture modeling, and vegetation index techniques.

Asner, Gregory P.↗

DOE OSTI2017

Determining Reactor Fuel Type from Continuous Antineutrino Monitoring

In this work, we investigate the ability of an antineutrino detector to determine the fuel type of a reactor. A hypothetical 5-ton antineutrino detector is placed 25 m from the core and measures the spectral shape and rate of antineutrinos emitted by fission fragments in the core for a number of 90-d periods. Our results indicate that four major fuel types can be differentiated from the variation of fission fractions over the irradiation time with a true positive probability of detection at approximately 95%. In addition, we demonstrate that antineutrinos can identify the burnup at which weapons-grade mixed-oxide (MOX) fuel would be reduced to reactor-grade MOX, on average, providing assurance that plutonium-disposition goals are met. We also investigate removal scenarios where plutonium is purposefully diverted from a mixture of MOX and low-enriched uranium fuel. Lastly, we discuss how our analysis is impacted by a spectral distortion around 6 MeV observed in the antineutrino spectrum measured from commercial power reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1987

A spectral multi-domain technique for analysis of chemically reacting flows

A technique is presented which models the chemical kinetics and flow kinematics of a nonionized air mixture passing through a fully resolved shock wave, thus alleviating the need for artificial viscosity. The quasi-one-dimensional Navier-Stokes equations and the species conversation equation are the governing equations. The validity of the multidomain Navier-Stokes algorithm is demonstrated via comparison with experiment.

Macaraeg, Michele G.↗

NASA NTRS1977

Analysis of steranes and triterpanes in geolipid extracts by automatic classification of mass spectra

A computer method is described for the automatic classification of triterpanes and steranes into gross structural type from their mass spectral characteristics. The method has been applied to the spectra obtained by gas-chromatographic/mass-spectroscopic analysis of two mixtures of standards and of hydrocarbon fractions isolated from Green River and Messel oil shales. Almost all of the steranes and triterpanes identified previously in both shales were classified, in addition to a number of new components. The results indicate that classification of such alkanes is possible with a laboratory computer system. The method has application to diagenesis and maturation studies as well as to oil/oil and oil/source rock correlations in which rapid screening of large numbers of samples is required.

Wardroper, A. M. K.↗

NASA NTRS1993

A tool for manual endmember selection and spectral unmixing

Sampling a continuous radiance spectrum in many narrow contiguous spectral bands results in a high covariance between the bands. Hence, the true dimensionality of imaging spectrometer data is not determined by the number of spectral bands, but by the number of spectrally unique signatures whose mixtures reproduce the spectral variance observed in an image. Methods to unmix high dimensional multispectral data use principal components analysis to reduce the dimensionality. The variance of the spectral data is modeled as a linear combination of a finite set of endmembers in the space of the eigen-vectors that account for most of the variance. The number and characteristics of these endmembers are determined not only by the number and characteristics of the spectrally unique materials on the surface but also by processes (e.g., illumination, atmospheric scattering and absorption) affecting the signal received by the sensor. Selection of endmember spectra has typically been from a library. However, since most libraries are incomplete and do not account for the processes mentioned above, we have devised a computer display that allows researchers to explore interactively the eigenvector space of a representative and mean-corrected subset of the image data in search of extreme spectra to designate as endmembers. This display, which is based on parallel coordinates, is unique in the area of multidimensional visualization in that it includes not only a passive view of higher dimensional data but also the capability to interact and move geometrical objects in higher dimensional spaces.

Bateson, C. Ann↗

NASA NTRS1974

Chemical composition of Luna 16 lunar regolith

Data on the chemical composition of regolith returned by the Luna 16 automatic station and two fragments of basalts from the lower layer of the core are presented. Spark mass spectrometric, primary X-ray spectral, emission spectral, and atomic absorption methods were used in the analysis. The regolith of mare provinces were shown to be a mixture of material of various origins. The source of the material of the mare regolith was principally basalts of the corresponding lunar lava maria. The regolith is genetically related to it. This follows from a comparison of the chemical composition, mineralogical, and petrochemical features of the basesalts and the regolith from the Sea of Fertility, Sea of Tranquillity, and Ocean of Storms, respectively.

Vinogradov, A. P.↗

DOE OSTI2016

X-ray Spectral Analysis for Void Fraction Measurement

X-ray attenuation technique has been widely used in two-phase flow measurement. In general, an x-ray system measures the overall attenuation of the two-phase mixture existing between an x-ray source and a detector. One can obtain the void fraction from the intensity of the attenuated x-ray beam and known attenuation coefficients of each phase. Fig. 1 shows a schematic of the line detector system developed at Virginia Tech, and the reconstructed image of a sample slug bubble. The system is capable of obtaining high-resolution (100 {mu}m or less) x-ray images of two-phase flow at a frame rate exceeding 1000 Hz. Note that the intensity of the image can be converted into the line-averaged void fraction data measured by each detector pixel. Typical x-ray systems do not resolve the energy spectrum. Instead, they only measure the total energy deposited in the detector during the exposure period. However, the x-ray source generated from x-ray tubes present polychromatic characteristics. The attenuation coefficient and detector efficiency strongly depend on the energy of x-ray photons. In relation to this, this paper presents the spectral characteristics of a typical x-ray system used for void fraction measurement in two-phase flows. The photon-energy-dependent efficiency of the detector is determined by a calibration test. (authors)

42 ENGINEERING↗

NASA NTRS1973

Determination of the temperature of gas mixtures by using laser Raman scattering

A theoretical model for the Raman rotational spectrum of air was formulated, yielding the spectral temperature dependence; and an error analysis of temperature measurement accuracies was performed. The theoretical spectra and the predicted temperature measurement error of + or - 20 K (7 percent) compared well with experimental data. These experimental data consisted of Raman spectra of air obtained for temperatures ranging from 243 to 313 K at a pressure of 1 atmosphere. The use of selected lines resulted in an experimental accuracy of + or - 13 K (-5 percent).

Coney, T. A.↗

NASA NTRS1977

Storage and retrieval of mass spectral information

Computer handling of mass spectra serves two main purposes: the interpretation of the occasional, problematic mass spectrum, and the identification of the large number of spectra generated in the gas-chromatographic-mass spectrometric (GC-MS) analysis of complex natural and synthetic mixtures. Methods available fall into the three categories of library search, artificial intelligence, and learning machine. Optional procedures for coding, abbreviating and filtering a library of spectra minimize time and storage requirements. Newer techniques make increasing use of probability and information theory in accessing files of mass spectral information.

Hohn, M. E.↗

NASA NTRS1985

Geologic mapping using Landsat MSS and TM images - Removing vegetation by modeling spectral mixtures

Semi-arid regions of the island of Hawaii and of the Tucson Mountains, AZ, having less than 50 percent green vegetation cover were mapped into rock/soil types by first identifying spectral mixtures of vegetation and rock/soil, and then removing the vegetation information. Landsat MSS images were used for Hawaii, and a Landsat TM image was used for the Tucson Mountains. Following analysis of the images field transects were done in test areas to determine percent vegetation cover and vegetation community characteristics, and to observe rock and soil types. For both Hawaii and the Tucson Mountains 20 percent or more of green vegetation caused potential misidentification of the rock/soil units unless spectral mixing was taken into account.

Adams, J. B.↗

NASA NTRS1992

Ejecta patterns of Meteor Crater, Arizona derived from the linear un-mixing of TIMS data and laboratory thermal emission spectra

Accurate interpretation of thermal infrared data depends upon the understanding and removal of complicating effects. These effects may include physical mixing of various mineralogies and particle sizes, atmospheric absorption and emission, surficial coatings, geometry effects, and differential surface temperatures. The focus is the examination of the linear spectral mixing of individual mineral or endmember spectra. Linear addition of spectra, for particles larger than the wavelength, allows for a straight-forward method of deconvolving the observed spectra, predicting a volume percent of each endmember. The 'forward analysis' of linear mixing (comparing the spectra of physical mixtures to numerical mixtures) has received much attention. The reverse approach of un-mixing thermal emission spectra was examined with remotely sensed data, but no laboratory verification exists. Understanding of the effects of spectral mixing on high resolution laboratory spectra allows for the extrapolation to lower resolution, and often more complicated, remotely gathered data. Thermal Infrared Multispectral Scanner (TIMS) data for Meteor Crater, Arizona were acquired in Sep. 1987. The spectral un-mixing of these data gives a unique test of the laboratory results. Meteor Crater (1.2 km in diameter and 180 m deep) is located in north-central Arizona, west of Canyon Diablo. The arid environment, paucity of vegetation, and low relief make the region ideal for remote data acquisition. Within the horizontal sedimentary sequence that forms the upper Colorado Plateau, the oldest unit sampled by the impact crater was the Permian Coconino Sandstone. A thin bed of the Toroweap Formation, also of Permian age, conformably overlays the Coconino. Above the Toroweap lies the Permian Kiabab Limestone which, in turn, is covered by a thin veneer of the Moenkopi Formation. The Moenkopi is Triassic in age and has two distinct sub-units in the vicinity of the crater. The lower Wupatki member is a fine-grained sandstone, while the upper Moqui member is a fissile siltstone. Ejecta from these units are preserved as inverted stratigraphy up to 2 crater radii from the rim. The mineralogical contrast between the units, relative lack of post-emplacement erosion and ejecta mixing provide a unique site to apply the un-mixing model. Selection of the aforementioned units as endmembers reveals distinct patterns in the ejecta of the crater.

Ramsey, Michael S.↗

DOE OSTI2021

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

Measured rotational and vibrational temperature differences in arc jet shock layers

Shock-layer-radiation emission spectra from the first negative system of the nitrogen molecular ion N2(+) are analyzed over the wavelength region between 370 and 430 nm. The shock layer is produced by a blunt body placed in the expanded flow from an arc heater employing either pure nitrogen or a nitrogen-oxygen air mixture. A rotational temperature is obtained from analysis of (0,1) band emission from N2(+). Vibrational temperatures are extracted from population distributions obtained through spectral fitting of the N2(+) (B-X) band sequences. Rotational temperatures up to 9500 K near the front of the shocks are determined for different energy and flow conditions. The rotational temperatures are found to be lower than those obtained for vibration confirming previous measurements and contrary to expectation based on theory.

Blackwell, Harvel E.↗

DOE OSTI2018

Chemical variability in mineralized veins observed by ChemCam on the lower slopes of Mount Sharp in Gale crater, Mars

ChemCam has observed a wide range of diagenetic features along the Curiosity rover traverse including pervasive Ca-sulfate veins. Observations by multiple instruments on Curiosity indicate that these veins are hydrated, formed during diagenetic fluid event(s). In this study, we delve into the chemical variability in these Ca-sulfate bearing veins and have identified two subsets in the Murray formation with enrichments in Fe and Fe + Mg. These chemical trends do not reflect a sampling mixture with the surrounding host rock but likely indicates the presence of authigenic phases formed during the emplacement of these veins. Based on passive reflectance spectral analysis and correlation with other elements, Fe 3+ oxides and/or sulfates are proposed to account for the Fe-rich observations in the vicinity of the Naukluft Plateau whereas the Fe + Mg trend is also observed in adjacent dark-toned features with elevated Mn and P near the Old Soaker outcrop. In conclusion, the specific localization of these observations in the Gale stratigraphy implies changing pH and redox conditions in the groundwater at the time of formation of these veins, from oxidizing and likely more acidic near the Naukluft Plateau to more reducing conditions in the upper part of the Murray formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗