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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19

Multiscale Progressive Failure Analysis of 3D Woven Composites

Application of three-dimensional (3D) woven composites is growing as an alternative to the use of ply-based composite materials. However, the design, analysis, modeling, and optimization of these materials is more challenging due to their complex and inherently multiscale geometries. Herein, a multiscale modeling procedure, based on efficient, semi-analytical micromechanical theories rather than the traditional finite element approach, is presented and applied to a 3D woven carbon–epoxy composite. A crack-band progressive damage model was employed for the matrix constituent to capture the globally observed nonlinear response. Realistic microstructural dimensions and tow-fiber volume fractions were determined from detailed X-ray computed tomography (CT) and scanning electron microscopy data. Pre-existing binder-tow disbonds and weft-tow waviness, observed in X-ray CT scans of the composite, were also included in the model. The results were compared with experimental data for the in-plane tensile and shear behavior of the composite. The tensile predictions exhibited good correlations with the test data. While the model was able to capture the less brittle nature of the in-plane shear response, quantitative measures were underpredicted to some degree.

3D woven composites↗

Refill Friction Stir Spot Welding as an Alternative Joining Method for Wing Spar Structures

Since the introduction of refill friction stir spot welding (RFSSW) in the early 2000s, numerous evaluations of properties, performance, and prototypes have been documented. RFSSW is a solid-state spot joining technique that is being evaluated as a rivet replacement technology for aerospace structures and fuselage fabrication. A production evaluation of overlapping wing skin assembly was completed and experimentation on stringer-stiffened curvilinear panels is underway. Weld properties were evaluated for spots produced on bare sheet as well as for sections with sealant applied. Furthermore, evaluations of the performance of repaired spots using the RFSSW process is demonstrated. Characterization of the weld interface, heat-affected zone, and complete through-thickness consolidation via computed tomography is presented.

Solid-state joining↗

ASTM International Conference on Additive Manufacturing – 2022

The In-Situ Project: Correlating In-situ monitoring data and Non-Destructive Evaluation (NDE) methods to characterize defect populations in Laser Powder Bed Fusion (L-PBF) material NDE is critical to enable the safe use of additive manufactured (AM) parts in aerospace applications. However, traditional NDE methods are not fully adaptable to complex AM geometries to appropriately screen for critical defects, and L-PBF processes inherently generate defects. In-situ monitoring techniques can give information about the quality of the build process and indicate process variations that could potentially create defects. Proven, causal correlations between in-situ monitoring indications and resulting defects are needed to inform about the final quality of the part. Thus, the development of a new approach is necessary. NASA started a two-phase study that would investigate techniques for characterizing defect populations in L-PBF material, first in material with induced defects, then in a nominal L-PBF process, by correlating in-situ, NDE, and serial sectioning data. Objectives also include the evaluation of seeded defect methodologies for realistic defect creation, creating a baseline of defect populations in a Qualified Material Process (QMP), characterizing the effect of heat treatment, and correlating defect populations with tensile and fatigue properties. By comparing computed tomography images, in-situ monitoring images, and metallography images, the team has been able to draw preliminary conclusions. They include a better understanding of the limitation of the NDE tools, learning about the “healing” of the samples observed during layer building and a comparison study on different laser power variation samples. Those preliminary conclusions will help dictate the follow-up work that will be presented at the conference.

additive manufacturing↗

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (Metric)

Geological solids are characterized by their mineral structure, elemental composition, and morphology. The Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC) is an instrument payload that will quantify all three. METRIC comprises a suite of instruments in a lander to perform X-ray diffraction (XRD) for mineral structure, X-ray fluorescence (XRF) for elemental composition, and X-ray Micro Computed Tomography (XCT) for 3D internal micromorphology. The instruments are accompanied by an Infrared Spectrometer (IRS) provide geologic context. A Honeybee Robotics pneumatic sampling and transfer system [e.g., 1] will be positioned under the lander to deliver sieved regolith to the X-ray instruments for analysis. This payload is envisioned for deployment to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander but could be carried on a lander or rover to any solid surface in the solar system.

E B Rampe↗

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission's Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

thermal protection systems↗

Direct Analyses of Aqueous Fluids from C-Class Asteroid 162173 Ryugu

Imaging using X-ray absorption contrast by synchrotron nano-computed tomography (47.4 nm/voxel, 7keV) of a Ryugu pyrrhotite crystal revealed probable fluid inclusions. The inclusions were completely encapsuled in pyrrhotite, suggesting the fluids were trapped in the early stages of crystal growth, and filled with low-Z material. We performed Time-of Flight-Secondary Ion Mass Spectrometry (TOF-SIMS) depth profiling and high-resolution mapping at -120°C to exposure and measure the composition of the trapped fluids in a frozen state. These measurements revealed that the ancient, trapped fluids on Ryugu’s parent asteroid were saline aqueous solutions containing H2O, CO2, sulfur species, and nitrogen- and chlorine-bearing organic compounds identified by representative secondary ion species including O(-), OH(-), CO(-), S(-), Cl(-), C2(-), C2H(-), and CN(-). The inferred presence of CO2 indicates formation of the sulfides, and by implication the Ryugu parent body, beyond the H2O and CO2 snow lines of the early solar system, i.e. > 3-4 au from the Sun.

M Zolensky↗

Sensitivity Analysis of Geometric Imperfection Sources in Honeycomb Cores on Flatwise Compression Behavior

Manufacturing aluminum honeycomb core material using the expansion process can lead to geometric imperfections in the cellular core structures. These imperfections arise due to irregularities introduced in the initial foil bonding, variations in foil thickness, and residual stresses from manufacturing processes. Such geometric imperfections include cell shape distortions, cell wall waviness, non-uniform cell wall thickness, and variability in the shape and height of the adhesive fillet. Imperfections in the cell walls negatively affect the transverse compression and shear strength, while also reducing the resistance to damage under impact loads. Previous work presented the identification and quantification of these manufactured imperfections using high resolution X-ray computed tomography (CT) scans of honeycomb cores in co-cured composite sandwich panels. The present paper presents a sensitivity analysis of individual components of the sources of geometric imperfections on the flatwise compression of aluminum honeycomb cores. The initial geometric imperfections in honeycomb cells are decomposed into three components, namely cell shape (cell edge length and cell internal angles) in-plane cell wall waviness, and out-of-plane waviness along the core thickness. A sensitivity analysis is conducted using finite element (FE) models of the decomposed imperfections to understand how each component affects compression failure.

aluminum honycomb↗

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↗

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission’s Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

Justin B. Haskins↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗

Automated Registration of Multi-Mode Nondestructive Evaluation Data

Registration techniques play a central role in applications of image processing to computer vision, medical imaging, and automatic target tracking. Feature-based techniques such as scale-invariant feature transform (SIFT) and speeded up robust features (SURF) are commonly used to register images derived from a single modality. However, SIFT and SURF struggle to register images from different modalities because the features tend to manifest rather differently and at sometimes very different length-scales. The most successful methods that have been developed to register multi-modal data use information-theoretic approaches. These methods play a key part in nondestructive evaluation scenarios where data that is collected by sensors of different modalities must be registered to be fused. In this paper, automated registration based on normalized mutual information is applied to align data derived from ultrasonic and radiographic inspections of (i) additively manufactured titanium alloy test coupons, and (ii) thin, lithium metal pouch-cell batteries. The quality of the registration is quantified in terms of computational resources and spatial accuracy. In the first case the X-ray computed tomography (XCT) data is captured on a region corresponding to a small subset of the ultrasonic data, while in the case of the lithium batteries the digital radiography (DR) captures a larger region of interest than the ultrasonic data. In both cases the radiographic data resolution is much higher than for ultrasound, but interestingly, in both cases the accuracy of the registration is approximately equal to two-to-three-pixel lengths in the ultrasonic images.

Nondestructive Evaluation↗

Isotopic, Chemical, and Molecular Studies of Insoluble Organic Matter and C-Rich Presolar Grains in Murchison and Sutter'S Mill: Assessing the Impact of XCT and Preparation for Bennu Samples

Spectral observations of B-type asteroid Bennu by the OSIRIS-REx spacecraft show affinities to CM-type carbonaceous chondrites, being organic-rich [1, 2] with abundant hydrated minerals [3-5]. Here we analyzed acid insoluble residues from Bennu analog chondrites Murchison (CM2) and Sutter’s Mill (C) to assess the effects of parent body alteration on the insoluble organic matter (IOM) chemistry and isotopic compositions, as well as abundances of C-rich presolar grains. Because Bennu samples may undergo X-ray computed tomography (XCT) imaging during preliminary examination, it is necessary to understand the effects of irradiation, if any, on IOM. We therefore also analyzed a residue produced from XCT-imaged Murchison powder to assess any X-ray damage.

A. N. Nguyen↗

Characterization of Low-Velocity Impact Damage in Thermoplastic Laminated Composites

The impact damage response of two thermoplastic material systems were compared over a range of impact energies. Eight-inch-square impact specimens with a 24-ply quasi-isotropic layup were manufactured from TC1225 LMPAEK T700G from Toray Industries and APC AS4D/PEKK-FC from Solvay. The effect of the degree of crystallinity (DOC) on the damage response was also investigated using a third set of specimens from the Toray material manufactured with reduced crystallinity. Using a combination of data obtained from X-ray computed tomography (CT) scans and ultrasonic testing (UT), detailed damage maps were created for every interface and ply for selected specimens. Using these damage maps, the delamination size, shape, and area were evaluated at each interface. The presence of fractured fibers was also identified on each ply. The LMPAEK material was found to have fewer and smaller delaminations than the PEKK specimens for impacts at the same energy. However, the LMPAEK specimens contained a larger number of fiber breaks. A similar trend was observed when comparing the baseline LMPAEK specimens with the low-crystallinity LMPAEK specimens. The low-crystallinity specimens had very little delamination but had a large number of plies with fiber breaks. In addition, the LMPAEK specimens often contained lines of fiber fractures in near-surface plies emanating from the contact region that were not present in the PEKK specimens.

Composite Materials↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

High-Temperature Mechanical Tensile Testing of Unidirectional Sic/Sic Composites Using A Versatile Lamp Furnace

Silicon carbide (SiC) based ceramic matrix composites (CMCs) are of interest for high-temperature structural applications, including use in turbine engine components. To understand damage mechanisms and predict durability of these systems, in-depth knowledge of their behavior at ambient and high temperatures is necessary. A method for high temperature testing of SiC/SiC minicomposite specimens up to 1500oC in both tensile fast fracture and creep conditions to investigate their thermomechanical behavior will be presented. This method utilizes a novel radiation heat furnace, equipped with infrared lamps with ellipsoidal reflectors, to heat the specimen at the furnace center in user-defined atmospheres. The housing structure of the lamps allows for observation of the specimen during testing using optical methods and for conducting other experimental studies. The goal is to employ nondestructive health monitoring techniques in-situ, including acoustic emission (AE), electrical resistance (ER), and digital image correlation (DIC) to evaluate damage initiation and evolution in the minicomposite specimens during tensile testing. Results from mechanical testing and nondestructive techniques will be presented. Electron microscopy and X-ray micro-computed tomography were used to further characterize specimen damage after testing.

Aeronautics↗

Fluid Inclusions in Extraterrestrial Samples: Failures, Successes, Possibilities, and A Note of Caution

Over the past half century the search for life in the solar system and beyond has become a major research focus, with much effort devoted to finding evidence for liquid H2O and reduced carbon-bearing (organic) species in extraterrestrial samples. The most direct and convincing evidence for the presence of water and organic molecules is provided by fluid inclusions (FI)trapped in minerals that formed on the parent bodies. Beginning in the 1970s, reports of FI in extraterrestrial samples generated much enthusiasm within the planetary sciences community. However, many of the reported FI were determined to be artifacts of sample preparation, or incomplete characterization of features that appear to be FI, or were inconsistent with the inferred PT history of the meteorite sample. An early report of aqueous (and hydrocarbon-bearing) FI in stony meteorites and the subsequent follow-up study that showed that most or all of the “FI” contained water used during cutting and polishing of the samples led to a general unwillingness to believe later reports of FI in meteorites. One of the first confirmed occurrences of extraterrestrial aqueous (liquid) fluid inclusions in a meteorite was reported by Zolensky et al. (1999; Science), who described aqueous inclusions in halite in the Monahans and later the Zag meteorites. These meteorite falls were collected shortly after landing on earth and were prepared without using water or other fluids that could introduce artifacts. The oxygen and hydrogen isotopic composition of water in FI in these same samples was later measured, showing that the fluids represent various degrees of water-rock interaction on the parent body .In more recent years, careful studies of FI trapped in extraterrestrial samples combining synchrotron X-ray computed tomography to locate FI in samples followed by cryo-TOF-SIMS analysis of the FI have identified the presence of molecular fragments suggesting the presence of H2O and various organic molecules in the fluids. Challenges associated with studying FI in extraterrestrial samples include the limited abundance of potential host phases for FI, such as carbonates and phosphates, the often poor optical quality of the host phases, and the small size of the FI, with few as large as 5 microns and most less than 1-2 microns in maximum dimension

Robert Bodnar↗