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At least 1,441 records · Page 80

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography–Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method

Here, in this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

09 BIOMASS FUELS↗

A supercluster catalog

The largest available complete redshift sample of rich clusters of galaxies is used to construct a three-dimensional catalog of superclusters complete to redhsift of about 0.08 or less. The criterion of membership in the catalog is the density enhancement of clusters over the mean density; the catalog is presented for various values of this parameter. The dependence of the identified sample of superclusters on the overdensity is studied, and the sensitivity of the identified superclusters to various quantities and selection procedures is investigated. The validity of the identification procedure is established by comparisons with random catalogs.

Bahcall, N. A.↗

Effect of Ce/Zr molar ratio on the performance of Cu–Ce{sub x}–Zr{sub 1−x}/TiO{sub 2} catalyst for selective catalytic reduction of NO{sub x} with NH{sub 3} in diesel exhaust

Graphical abstract: The Cu–Ce{sub 0.25}–Zr{sub 0.75}/TiO{sub 2} catalyst exhibited excellent SCR activity at 165–450 °C within the range of exhaust temperatures of diesel engines. - Highlights: • Cu–Ce{sub x}–Zr{sub 1−x}/TiO{sub 2} catalysts were prepared by a wet impregnation method. • The property for NH{sub 3}-selective catalytic reduction of NO{sub x} were investigated. • The Ce/Zr molar ratio had effects on the performance of Cu–Ce–Zr/TiO{sub 2} catalysts. • The Cu–Ce{sub 0.25}–Zr{sub 0.75}/TiO{sub 2} sample exhibited 100% NO{sub x} conversion between 165 °C and 450 °C. • The factors that govern the activity enhancement were extensively investigated. - Abstract: Copper–cerium–zirconium catalysts loaded on TiO{sub 2} prepared by a wet impregnation method were investigated for NH{sub 3}-selective catalytic reduction of NO{sub x}, aiming to study the effects of the Ce/Zr molar ratio on the performance of Cu–Ce–Zr/TiO{sub 2} catalysts. The Cu–Ce{sub 0.25}–Zr{sub 0.75}/TiO{sub 2} sample exhibited nearly 100% NO{sub x} conversion over a wide temperature range (165–450 °C), which is strikingly superior to that of Cu/TiO{sub 2} (210–389 °C) within the range of exhaust temperatures of diesel engines. The factors that govern the activity enhancement were extensively investigated by using a series of characterization techniques, namely X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and temperature-programmed reduction by hydrogen (H{sub 2}-TPR). The results showed that the addition of zirconium and/or cerium refined the copper dispersion, prevented copper crystallization and partially incorporated the copper ions into the zirconia (ceira) lattice, which led to enhance the redox abilities of Cu–Ce–Zr/TiO{sub 2} catalysts.

36 MATERIALS SCIENCE↗

Quantitative X-ray dark-field and phase tomography using single directional speckle scanning technique

X-ray dark-field contrast tomography can provide important supplementary information inside a sample to the conventional absorption tomography. Recently, the X-ray speckle based technique has been proposed to provide qualitative two-dimensional dark-field imaging with a simple experimental arrangement. In this letter, we deduce a relationship between the second moment of scattering angle distribution and cross-correlation degradation of speckle and establish a quantitative basis of X-ray dark-field tomography using single directional speckle scanning technique. In addition, the phase contrast images can be simultaneously retrieved permitting tomographic reconstruction, which yields enhanced contrast in weakly absorbing materials. Such complementary tomography technique can allow systematic investigation of complex samples containing both soft and hard materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Mannino, Antonio↗

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗

Revisiting OSIRIS-REx Touch-And-Go (TAG) Performance Given the Realities of Asteroid Bennu

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission is a NASA New Frontiers mission that launched in 2016 and rendezvoused with the near-Earth asteroid (101955) Bennu in late 2018. Upon arrival, the surface of Bennu was found to be much rockier than expected. The original Touch-and-Go (TAG) requirement for sample collection was to deliver the spacecraft to a site with a 25-meter radius; however, the largest hazard-free sites are no larger than 8 meters in radius. To accommodate the dearth of safe sample collection sites, the project reevaluated all aspects of flight system performance pertaining to TAG in order to account for the demonstrated performance of the spacecraft and navigation prediction accuracies. More-over, the project has base lined on board natural feature tracking instead of lidar for providing the on board navigation state update during the TAG sequence. This paper summarizes the improvements in error source estimation, enhancements in on board trajectory correction, and results of recent Monte Carlo simulation to en-able sample collection with the given constraints. TAG delivery and on board navigation performance are presented for the final four candidate TAG sites.

Berry, Kevin↗

Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters

Purpose: Dynamic contrast-enhanced (DCE) MRI-extracted parameters measure tumor microvascular physiology and are usually calculated from an intratumor region of interest (ROI). Optimal ROI delineation is not established. The valid clinical use of DCE-MRI requires that the variation for any given parameter measured within a tumor be less than that observed between tumors in different patients. This work evaluates the impact of tumor ROI selection on the assessment of intra- and interpatient variability. Method and Materials: Head and neck cancer patients received initial targeted therapy (TT) treatment with erlotinib and/or bevacizumab, followed by radiotherapy and concurrent cisplatin with synchronous TT. DCE-MRI data from Baseline and the end of the TT regimen (Lead-In) were analyzed to generate the vascular transfer function (K{sup trans}), the extracellular volume fraction (v{sub e}), and the initial area under the concentration time curve (iAUC{sub 1min}). Four ROI sampling strategies were used: whole tumor or lymph node (Whole), the slice containing the most enhancing voxels (SliceMax), three slices centered in SliceMax (Partial), and the 5% most enhancing contiguous voxels within SliceMax (95Max). The average coefficient of variation (aCV) was calculated to establish intrapatient variability among ROI sets and interpatient variability for each ROI type. The average ratio between each intrapatient CV and the interpatient CV was calculated (aRCV). Results: Baseline primary/nodes aRCVs for different ROIs not including 95Max were, for all three MR parameters, in the range of 0.14-0.24, with Lead-In values between 0.09 and 0.2, meaning a low intrapatient vs. interpatient variation. For 95Max, intrapatient CVs approximated interpatient CVs, meaning similar data dispersion and higher aRCVs (0.6-1.27 for baseline) and 0.54-0.95 for Lead-In. Conclusion: Distinction between different patient's primary tumors and/or nodes cannot be made using 95Max ROIs. The other three strategies are viable and equivalent for using DCE-MRI to measure head and neck cancer physiology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

AugerPrime surface detector electronics

Operating since 2004, the Pierre Auger Observatory has led to major advances in our understanding of the ultra-high-energy cosmic rays. The latest findings have revealed new insights that led to the upgrade of the Observatory, with the primary goal of obtaining information on the primary mass of the most energetic cosmic rays on a shower-by-shower basis. In the framework of the upgrade, called AugerPrime, the 1660 water-Cherenkov detectors of the surface array are equipped with plastic scintillators and radio antennas, allowing us to enhance the composition sensitivity. To accommodate new detectors and to increase experimental capabilities, the electronics is also upgraded. This includes better timing with up-to-date GPS receivers, higher sampling frequency, increased dynamic range, and more powerful local processing of the data. In this paper, the design characteristics of the new electronics and the enhanced dynamic range will be described. The manufacturing and test processes will be outlined and the test results will be discussed. The calibration of the SD detector and various performance parameters obtained from the analysis of the first commissioning data will also be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗

Reduction Behavior of Dolomite-Fluxed Magnetite: Coke Composite Pellets at 1573 K (1300 °C)

High-temperature behavior of magnetite—coke composite pellet fluxed with dolomite was investigated by customized thermogravimetric analyzer (TGA) at 1573 K (1300 °C). The overall reaction was influenced by C/O ratio and dolomite content. The reduction was accelerated by increased amount of dolomite, while the samples with higher C/O ratio showed the improved reduction degree. X-ray diffraction (XRD) pattern of reduced pellet showed the phase changes of the iron oxides. Noticeable iron peaks were observed when the sample reached the final stage of reduction. CO and CO{sub 2} gases released from the reaction were measured by Infrared (IR) gas analyzer. Relation between enhanced reducibility of pellets and larger CO gas evolution from the Boudouard reaction was confirmed from the analysis. Compressive strengths were studied for the practical assessment of reduced pellets. Samples with low-reduction degree showed better physical property. Excessive amount of dolomite also deteriorated the integrity of pellets.

36 MATERIALS SCIENCE↗

Graphene addition to MgB{sub 2} superconductor obtained by ex-situ spark plasma sintering technique

Highlights: • Graphene-added dense MgB{sub 2} was prepared by ex-situ spark plasma sintering. • There is a limited interaction between graphene and MgB{sub 2}. • Addition of graphene (G) shows a small enhancement of J{sub c} and μ{sub 0}H{sub irr}. • G is one of the least effective C-containing additions. - Abstract: Graphene nanopowder (G) with average thickness particle size of about 6–8 nm was added to MgB{sub 2} commercial powder. Starting composition was (MgB{sub 2}){sub (1−x)}(G){sub x}, x = 0.0125, 0.025, 0.05. Processing was performed by Spark Plasma Sintering (SPS) technique. All added samples have high density (above 95%). The critical temperature (T{sub c}) and the lattice parameter a (c-axis lattice parameter is constant) show a small variation suggesting that carbon substitution for boron is low. TEM observations show the presence of un-reacted graphene plates supporting the T{sub c} and structural results. It also indicates that G-addition does not modify the MgB{sub 2} microstructure. Despite this, there is an optimum doped sample (MgB{sub 2}){sub 0.9875}(G){sub 0.0125} for which the critical current density at temperatures below 25 K is slightly higher at high magnetic fields than for the pristine sample. The addition of G is found as one of the least effective C-source additions enhancing J{sub c}. We discuss results as being strongly related to variation of the residual stress.

36 MATERIALS SCIENCE↗

Photoluminescence, enhanced ferroelectric, and dielectric properties of Pr{sup 3+}-doped SrBi{sub 2}Nb{sub 2}O{sub 9} multifunctional ceramics

Pr{sup 3+}-doped SrBi{sub 2}Nb{sub 2}O{sub 9} (SBN) multifunctional ceramics were synthesized by the conventional solid state method. The photoluminescence (PL) excitation and emission spectra, enhanced ferroelectric and dielectric properties were investigated. The X-ray diffraction (XRD) and FESEM analyses indicated that the samples were simple phase and uniform flake-structure. Under the 250–350 nm ultraviolet (UV) excitations, the red emission was obtained and the optimal emission intensity was investigated when Pr doping level was 0.005 mol. With the increasing of the Pr{sup 3+} ion contents, the ferroelectric properties were enhanced obviously. As a new multifunctional material, the Pr{sup 3+}-doped SBN ceramics could be used for a wide range of application, such as integrated electro-optical devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Infrared observations of interacting/merging galaxies

The present sample of 20 galaxy systems, selected on the basis of morphological evidence for the tidal interaction or merger of two galaxies and observed at 1-10 microns, is noted to include 11 systems, detected at 10 microns, which have on average a significantly higher IR luminosity than noninteracting galaxies. The enhanced IR radiation is due to star formation bursts. On the basis of IR Astronomical Satellite results for a sample of galaxies, as much as 30 percent of all the far-IR emission observed arises in bursts of star formation that are triggered by interactions, and massive stars account for most of the luminosity in these bursts. It is suggested, in view of a massive star formation rate in the interacting and merging galaxies that is about 3 times higher than in noninteracting systems, that much of this star formation occurred in either nuclear regions or merger remnants.

Lonsdale, C. J.↗

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↗