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NASA NTRSDate not supplied

Applicability of Micro X-Ray Fluorescence Spectroscopy to Astromaterials Curation and Research

Introduction: The Astromaterials Acquisition and Curation Office at NASA’s Johnson Space Center (JSC) curates NASA’s astromaterial sample collections which includes: Apollo samples, Luna samples, Ant-arctic meteorites, cosmic dust particles, microparticle impacts into space-flown materials, Genesis solar wind atoms, Stardust comet Wild-2 particles, Stardust inter-stellar particles, Hayabusa asteroid Itokawa particles, Hayabusa 2 asteroid Ryugu particles, and future OSIRIS-Rex asteroid Bennu particles (landing in Sep-tember, 2023) [1–3]. To enhance JSC’s advanced cu-ration capabilities, we have recently installed a high-performance micro-X-ray fluorescence (µXRF) spec-trometer to assist in sample characterization through rapid, non-destructive, in-situ elemental analyses that do not require the sample preparation protocols (i.e., polishing and carbon-coating) commonly needed for electron beam analyses. With this new instrument, we are capable of detecting all elements down to carbon in a variable-pressure or He-purged chamber for anal-ysis of a wide range of sample types. Here we describe the instrumental set-up, capabilities, and applicability of µXRF analysis to astromaterials curation and re-search. Instrumentation and Methodology: The X-ray fluorescence and computed tomography lab (X-FaCT) lab at JSC is now equipped with a Bruker M4 Tornado Plus µXRF (Fig. 1). This system is an energy-dispersive x-ray spectrometer equipped with two 60 mm2 silicon drift detectors (SDD) that are able to be used simulta-neously for output count rates ~500,000 cps. New light element windows allow detecting and analyzing the entire elemental range from carbon to americium. Two x-ray tubes (micro-focus Rh with polycapillary lenses and W with collimators of 0.5, 1.0, 2.0, and 4.5 mm) with max excitation parameters of 50 kV, 30 W and 50 kV, 40 W, respectively, allow for more flexibility of the analysis of high energy lines. The motorized X-Y-Z stage has a mapping range of 190 x 160 mm and can support samples up to 7 kg (~15.5 lbs) and a height of 120 mm [4]. Analytical modes include elemental analysis (down to ~20 µm spot size) via point, line, or area of bulk materials (rock surfaces, thin sections, thick sections, etc.) as well as coating analysis (determination of thickness and composition) of samples. This system has a variable vacuum chamber (1 mbar to 1 atm) that is also equipped with a He-purge system which accommodates vacuum sensitive samples while still allowing detection of light elements at atmospheric pressure. Utility and Applicability of µXRF in Astro-materials research and exploration science (ARES): Elemental analysis using µXRF is commonly em-ployed for both terrestrial and planetary geological science disciplines [5]. It is especially useful for analy-sis of astromaterials given the limited sample prepara-tion required, which is not feasible for certain materi-als. Here we show select applications of µXRF anal-yses of astromaterials that can, have, and will be done at JSC’s X-FaCT lab. Point analysis: In-situ spot analyses (~20 µm spot size) on a cut slab of Martian meteorite NWA 10922 allowed for the discovery, qualitative elemental analy-sis and determination of different feldspar minerals [6]. These point analyses served as an effective prelim-inary step for subsequent quantitative analyses. Ana-lytical standards can be employed for more accurate quantification of µXRF spot analyses. Area analysis: This analytical mode measures all detectable elements (from C to Am) at each pixel (>5 µm pixel size) in a user-defined area. The results are shown as elemental maps which can be extracted as 16-bit TIFF’s for further data processing. In Fig. 2. we show elemental distribution maps of the high-Ti basalt 73001,531 that have been processed using ImageJ software. From these maps you can accurately and quickly (this map took ~50 mins.) identify mineral components, such as pyroxene, plagioclase, oxides, and phosphates, compositional zoning, and mineral textures. Detection of high-Z phases: µXRF techniques are es-pecially effective at analyzing trace minerals with high-atomic-number (high-Z) elements because the high-energy characteristic X-rays used (relative to SEM EDS) allow for mapping of K lines in elements up to La (typically SEM maps use L X-ray lines for elements >Zn, and these can often have interferences). Thus, µXRF is especially suited for identifying minerals like zircon, baddeleyite, REE-rich phosphates, Fe-rich met-als, oxides, sulfides, and phosphides [4]. In Fig. 3 we show elemental distribution maps for 73001,530 where we are able to correlate the original video image with, Zr, Si, Y and Hf elemental maps together identi-fying the location of a zircon. In this location you would expect lower Si compared to surrounding mate-rial, as well as higher Zr, Y, and Hf content compared to surrounding material, all of which is confirmed by our XRF ele-mental distribution maps (Figure 2.) Conclusions: The new M4 Tornado Plus µXRF within the Astromaterials Acquisition and Curation office at NASA JSC allows for rapid and non-destructive elemental analysis of astromaterials with limited or no sample preparation. µXRF analyses pro-vide crucial compositional knowledge for the prelimi-nary examination and curation of astromaterials. This instrument enhances the advanced curation capabili-ties in the X-FaCT laboratory at JSC by allowing pro-ductive, cohesive, and non-destructive multi-modal x-ray analyses on astromaterial samples, which is neces-sary for the comprehensive curation and study of our current and future astromaterial collections. Addition-ally, µXRF can provide complimentary information to researchers for studies on astromaterials. References: [1] Allen, C. et al., (2011). Chemie De Erde Geochemistry, 71, 1-20. [2] McCubbin, F. M. et al., (2016) 47th LPSC, abstract #2668 [3] Zeigler, R. A. et al., (2017) 48th LPSC, abstract #2772 [4] Bruker User Manual [5] Young et al., (2016) Appl. Geochemistry, 72, 77-87 [6] Mor-ris, R. V. et al., (2023) 54th LPSC.

E W O'Neal↗
NASA NTRSDate not supplied

In-Lab Rapid Analytical Detection of Lunar Volatiles By Universal Gas Analyzer With Comparison to GC-MS System

Introduction: The curation of permanently shadowed regions (PSRs) [1] on the lunar surface is centered around studies based upon the observed volatiles from the LCROSS mission [2]. The rapid detection of important volatile gases and vapors present in planetary bodies and Astromaterials by a standalone analytical device is an area of intense research interest in our group and Planetary Exploration & Astromaterials Research Laboratory (PEARL) facility and this work is relevant to the future preparation of viable lunar simulants for testing curation efforts down the road. The groundbreaking results obtained from the LCROSS Mission [2] open the requirements for the direct detection of volatiles present in regolith materials collected from the lunar surface. The mass spectrometry of volatile chemicals is a general technique that utilizes a set of instruments that creates charged ions from a gaseous chemical species and measures the intensities vs. mass-to-charge ratio (m/z) [3]. In this context, we discuss in-lab experimental results and procedures for rapid qualitative analysis of main LCROSS volatiles (water, H2S, NH3, CO2, and CH3OH) by a Universal Gas Analyzer (UGA) instrument. Additionally, the instrument performance was evaluated by measuring the isotopic abundance ratio of atmospheric Ar-40 to Ar-36 present in room air since, argon is a relevant gas in planetary studies as it can provide an insight and reference point to isotope studies [4]. Additional, cross comparisons were attempted and made between the two instruments to develop a robust analytical technique by comparing mass spectral data for H2S headspace samples with a Trace-1310/ ISQ 7000 (ThermoFisher Scientific.) GC-MS system. Background: The benchtop UGA System is equipped with an SRS UGA 300 quadrupole mass spectrometer designed and built by Stanford Research Systems [5]. This system can be configured for several types of gaseous chemical analysis. The inlet line continuously samples gases at low flow rates (several milliliters per minute) through a capillary limiting the intake pressure making the instrument ideal for online analysis of select gases and/or room atmosphere. Moreover, in our current UGA system, a change in composition at the inlet can be detected in about 200 milliseconds and a complete spectrum is acquired (for a range of 1-100 amu) in under 45 sec with masses measured at rates up to 25 msec per point [5]. This system provides a quick upstream analytical data that we can then compare to results obtained by our GC-MS system. Sample Preparation: Small volume (2-4 mL) of analyte sample was taken in a 10 mL glass vial and sealed with a crimped cap and purged with pure Ar or N2 gas to displace air from the top. The headspace sample was scanned by the UGA instrument at analog, histogram, and pressure vs. time modes. The isotopic abundance ratio for 40Ar-to-36Ar was estimated by measuring partial pressure vs. time scans and setting the mass at 40 and 36 respectively. Results and Discussions: In this work, we have investigated the applicability of the UGA system by qualitative analysis of a series of LCROSS volatiles measured individually. Fig. 1 demonstrates a set of vertically offset spectra for the partial pressures measured as a function of mass-to-charge (m/z) ratios. The average acquisition time for each spectrum was less than a minute suggesting that the UGA system is ideal for quick analysis of geochemical volatiles. For the cross-comparison, we analyzed an H2S headspace sample by a Trace-1310/ISQ-7000 system and compared mass spectral data with previously measured UGA histogram scan data (Fig. 2). In both cases, major peak positions are the same, however, the intensities of fragment ions ([1H132S]+ and [32S]+) are higher for UGA suggesting that the fragment ionization process is stronger in UGA compared to that of GC-MS. To investigate how the integrated area under each chromatogram varies with the headspace sample volume, a set of five H2S headspace samples with increasing volumes was analyzed by the GC-MS system (Fig. 3, inset). A small volume (e.g., 200 to 1000 µL) of H2S/H2O vapor was withdrawn from a 20 mL stock sample vial containing ~5 mL of 0.4% H2S in water by a gas-tight syringe and added to another 20 mL vial filled with argon and analyzed by the GC-MS system. Finally, the UGA detector sensitivity was evaluated by calculating the atmospheric 40Ar-to-36Ar isotopic abundance ratio in room air by running a partial pressure vs. time scan with setting the atomic mass at 40, and 36. Fig. 4(a) shows a ~25 min duration “P vs. time” scan for 40Ar (plot for 36Ar is not shown). The partial pressure values (~100 points) were corrected by subtracting the corresponding background pressure value for 37Ar and utilized to calculate 40Ar-to-36Ar isotopic abundance ratios as shown by Fig. 4b. The average isotopic abundance ratio is ~306 with a 2*STDEV ~13. This abundance ratio is significantly close to the previously reported value of 298.56 [6] and the ratio obtained by our GC-MS system (303 for a UHP grade Ar sample). Conclusions: Our study strongly evidenced that the benchtop UGA system is a valuable analytical tool for the detection of major LCROSS volatiles. The rapid scanning capability, the inexpensiveness of the whole system, and impressive detection sensitivity prove its worthiness as an essential device for advanced geochemical applications. Moreover, cross comparisons with the GC-MS provide important bridges into advanced curatorial efforts into the future. References: [1] Bickel, V.T., et al. (2021) Nat Commun 12, 5607. [2] Colaprete, A., et al. (2010) Science, 330, 463-468. [3] Glavin, D. P. et al. (2012) 2012 IEEE Aerospace Conference, 1-11. [4] Willett, C. D., et al. (2022) Geochimica et Cosmochimica Acta 329, 119-134. [5] Operation Manual and Programming Reference. (2018) Universal gas Analyzers, Stanford Research Systems. [6] Lee, J. Y., et al. (2006) Geochimica et Cosmochimica Acta 70, 4507–4512. Notes: (4 figures are attached with text as shown by the attached file)

Curation↗
NASA NTRS1995

Image analysis used to count and measure etched tracks from ionizing radiation

We have developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains and plastic dosimeters. Tracks in lunar samples are formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. We worked on two samples identified for a consortium study of lunar weathering effects, 61221 and 67701. They were prepared by the lunar curator's staff as polished grain mounts that were etched in boiling 1 N NaOH for 6 h to reveal tracks. We determined that backscattered electron images taken at 10 percent contrast and approximately 50 percent brightness produced suitable high contrast images for analysis. We used the NIH Image program to cut out areas that were unsuitable for measurement such as edges, cracks, etc. We ascertained a gray-scale threshold of 25 to separate tracks from background. We used the computer to count everything that was two pixels or greater in size and to measure the area to obtain track densities. We found an excellent correlation with manual measurements for track densities below 1 x 10(exp 8) cm(exp -2). For track densities between 1 x 10(exp 8) cm(exp -2) to 1 x 10(exp 9) cm(exp -2) we found that a regression formula using the percentage area covered by tracks gave good agreement with manual measurements. We determined the track density distributions for 61221 and 67701. Sample 61221 is an immature sample, but not pristine. Sample 67701 is a submature sample that is very close to being fully mature. Because only 10 percent of the grains have track densities less than 10(exp 9) cm(exp -2), it is difficulty to determine whether the sample matured in situ or is a mixture of a mature and a submature soil. Although our analysis of plastic dosimeters is at an early stage of development, results are encouraging. The dosimeter was etched in 6.25 N NaOH at 70 deg C for 16 h. We took 200x secondary electron images of the sample and used the NIH Image software to count and measure major and minor diameters of the etched tracks. We calculated the relative track etch rate from a formula that relates it to the major and minor diameters. We made a histogram of the number of tracks versus their relative etch rate. The relative track etching rate is proportional to the linear energy transfer of the particle. With appropriate calibration experiments, the histogram could be used to calculate the radiation dose.

Blanford, George E.↗
NASA NTRS2015

Finding Atmospheric Composition (AC) Metadata

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

metadata search↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Catalog Rock Fragments in Apollo Drive Tube 73002

Overview: The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the nearside of the Moon. Approximately 84% by mass of the Apollo collection remains in pristine condition within the curation facility at Johnson Space Center (i.e., never allocated, continuously stored in dry-N2 purged cabinets, exposure history restricted to Teflon, stainless steel, and Al-metal). Although most Apollo samples have been well characterized, there are several types of samples that have remained wholly or largely unstudied since their return, and/or that have been cu-rated under special conditions, e.g., frozen samples, samples stored in He-purged environment, and previously unopened drive tubes. NASA solicited proposals for the Apollo Next Generation Sample Analysis Pro-gram (ANGSA), and 9 teams were selected to study a subset of the unopened and frozen samples [1]. The first sample opened as part of the ANGSA pro-gram was drive tube 73002. This was originally a ~30 cm long, 4 cm diameter drive tube collected on a land-slide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube collected, and the bottom half of the tube (73001) was sealed under vacuum on the Moon [2]. Prior to opening sample 73002, the sample was imaged with a high resolution X-ray Computed Tomography (XCT) scan of the entire tube [3], which provided invaluable information during the dissection process [4]. In addition to the pre-dissection XCT scans, individual >4 mm particles were separated from the 73002 regolith during processing and scanned at high resolution by XCT. Here we pre-sent the initial lithologic classification of 134 individual >4 mm rock fragments separated from the 73002 core during the dissection process. Methodology: Drive tube 73002 was manually dissected in 0.5 cm depth intervals in three passes (Fig. 1) [4,5]. Each interval from pass 1 and 2 was sieved to <1 mm and >1 mm size fractions, and >1 mm particles were further manually subdivided into 1-2, 2-4, 4-10, and >10 mm size fractions. Pass 3 was not sieved, but >10 mm clasts were separated manually. Each 4-10 mm and >10 mm fragment was individually weighed, triply bagged in Teflon, and scanned by XCT. There are 60 rock fragments in Pass 1, 64 rock fragments in Pass 2 (from the 4-10 mm and >10 mm size fractions), and 8 rock fragments from Pass 3 (>10 mm size fraction). Each individually bagged rock fragment was scanned using the 180 kV nano-focus transmission source on the Nikon XTH 320 XCT system at NASA Johnson Space Center [6]. Scanning conditions varied considerably for individual particles, in large part be-cause of the large variation in size (0.008-19.623 g). All scans fell within the following range of scan conditions: 2.8-20.6 um voxel size; 90-155 kV voltage; 18-39 uA current; 1891-3141 projections; and 902-2000 slices. Results and Discussion: The 132 rock fragments from sample 73002 fall into the following general cat-gories: agglutinates (n = 6); basalts (13); impact melts (5); impact melt breccias (IMB; 42); regolith breccias (62); and soil breccias (4); see Figure 2 for representative examples of each lithology. Within most of these broad lithologic groups are recognizable subgroups. For example, a significant portion of regolith breccia fragments contain some agglutinate-like glass (n = 9) or are dilithologic (7) because they contain a single large clast (~50% or more by volume). Subgroups can be based on similarities to previously identified lunar lithologies, such as high-Ti basalts (9) and VLT basalts (4; Fig. 3), or based on commonly seen features within the fragments, such as poikilitic ilmenite IMB (10), ilmenite-lath IMB (12), or vesicular IMB (11) “groups”. Particles in the same “group” are not necessarily intended to be genetically related, but rather identify particles that are similar and that follow-up studies can classify in more detail [7]. Conclusion: Identification of lithologies based on XCT is a powerful tool, but a more absolute classification will sometimes require additional textural information from thin sections (e.g., glassy-matrix regolith vs. impact-melt vs. granulitic breccia) or quantitative mineral compositions (e.g., basalt vs. monomict breccia).

R A Zeigler↗