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293 records · Page 17

Trace Elemental Abundances in Calcium-Aluminum-Rich Inclusions in CV Chondrites

Introduction: Calcium-aluminum-rich inclusions (CAIs), are the first formed solids that define the age of the Solar System [1,2]. CAIs are thought to have condensed from nebular gas [3,4] within the first <1 Ma of Solar System formation [5,6]. CAIs have experienced numerous early Solar System processes including condensation, evaporation, melting, recrystallization, and aqueous alteration [e.g., 7]. The chemical, mineralogical, and textural diversity among CAIs results from a range of chemical and physical processes recorded during nebular and parent body epoch. This study aims to explore the mineralogical, textural, and chemical compositions of CAIs including the trace elemental abundances in CAI phases to determine the early Solar System processes recorded in them. Samples and Analytical Methods: We analyzed one CAI each from CV3 chondrites Northwest Africa (NWA) 5508 designated as ‘Saguaro’, and Northwest Africa (NWA) 12772 designated as ‘Hoopoe’. Back-scatter electron (BSE) images were collected using a Phenom XL scanning electron microscope (SEM) at the Lunar and Planetary Institute (LPI) and the JEOL JXA-8530F electron probe microanalyzer (EPMA) at Johnson Space Center (JSC)-NASA. Additionally, energy dispersive X-ray spectrometry (EDS) elemental maps of select areas for these samples were collected using a 15.0kV beam energy and a 40µA emission current. Using the EPMA, wavelength-dispersive X-ray spectroscopy (WDS) quantitative data were collected. In-situ trace element measurements for both CAIs were determined at JSC-NASA using a Photon Machines 193nm laser ablation system and a Thermo-Scientific Element-XR inductively coupled plasma mass spectrometer (ICP-MS). Analyses consisted of 30s ablations at 10Hz, spot sizes of 20-25µm, and a fluence of 6.0 J/cm2 for anorthite and melilite, and a 3.5 J/cm2 fluence for all other phases. NIST612 was used to correct for instrument drift, while BHVO-2g was used as a primary calibration standard. BCR-2g and in-house mineral standards were regularly measured as unknowns to ensure accuracy. Results: Saguaro is a coarse-grained CAI, ~11 x 6 mm in dimensions. Saguaro contains spinel, Al-rich pyroxene, anorthite, Mg-rich melilite, and minor perovskite in its interior and is therefore classified as a Type B CAI. Individual melilite grains shows normal compositional zoning with an Ak content ranging from ~24 to 54 with no apparent trend from the core to the edge of the CAI. The spinel appears euhedral and occurs both as clusters and as spinel palisades [8]. Two rim sequences surround most of the sample: the inner rim being a Wark-Lovering (WL) rim (~10-35 µm) containing pyroxene, spinel, and melilite (or anorthite), and the outer rim is a finer-grained, thicker (~100 µm), accretionary rim (Fig. 1). The mineral phases in Saguaro record an overall flat REE pattern with an average negative Eu anomaly in pyroxene, and an average positive Eu anomaly in anorthite and melilite respectively. Anorthite, melilite, and pyroxene have a minor depletion in Tm (Fig. 2). The Hoopoe CAI is a compact, coarse-grained ~6 × 4 mm in size. The major mineralogy includes hibonite, spinel, melilite, anorthite, and perovskite. Therefore, it is classified as a compact transitional type A and B. (?)zoning was observed in some hibonites. Individual melilite grains show both reverse and normal zoning, where the Ak content ranges from ~6- to 28. Melilite shows two distinct textures. One texture consisted of smooth melilite that appeared homogenous, while the second appeared to consist of many fine fractures. The spinel also often appears clustered. The WL-rim sequence surrounding Hoopoe is ~25 µm thick and composed of spinel, perovskite, hibonite, and melilite/anorthite. It is then partially surrounded by an outer accretionary rim (~75µm). Like before, refractory metal nuggets appeared concentrated near the WL rims. Other metal assemblages rich in Fe and Ni were also observed. All major mineral phases in Hoopoe display relatively flat REE patterns, except for varying Eu and Tm between phases (Fig. 2). There is a prominent negative Eu anomaly in perovskite and an average positive Eu anomaly in spinel, anorthite, and hibonite respectively (Fig. 2, 3). The mixed phases along the rim of the CAI also display a negative Eu anomaly, and all phases the CAI were depleted in Pb. Discussion: The CV3 CAIs analyzed in this study were classified based on their mineralogy and textures into Type A versus Type B CAIs [10]. Hibonite appears to be pseudomorphically replacing the spinel, (i.e., is hibonite in composition, but appears in the shape of spinel). Spinel palisades. The presence of spinel palisades present in Saguaro are consistent with the melting and recrystallization experienced by this CAI. Trace elemental analyses. Saguaro and Hoopoe display similar trace element patterns to each other, with both appearing generally flat, with anomalies in Eu, and Tm. Melilite and anorthite display positive Eu anomalies in both CAIs, in addition to the hibonite in Hoopoe (Fig. 2). The phases that are depleted in Eu are pyroxene and perovskite in both Saguaro and Hoopoe, respectively (Fig. 3). Given that Eu is volatile in reducing environments [11], this could possibly indicate reducing conditions at the time anorthite and melilite crystallized, with the gas they formed from containing Eu. As these CAIs continued to form, this gas as a result would become depleted in Eu. This also could be supported by the propensity of anorthite and melilite to take up Eu from its surroundings and incorporate it into their structure [12]. In addition, analyzing the assemblage of the phases in the Saguaro, melilite and anorthite (Eu enriched) often surround the pyroxene (Eu depleted) as they are crystallized. This intergrowth of phases and the proximity of the phases would support that the Eu is being incorporated into some phases, preventing it from incorporating into other. Trace elemental analyses of the CAI rims will be evaluated in more detail, as they are complicated by the transient signal being composed of a mixture of mineral phases. Broadly, however, the patterns in the rims of both CAIs are comparable to each other, and for Hoopoe, to the mixed phase patterns in the core (Fig. 3). Other studies have found that CAI rims can be depleted in Ce and Yb [13], however we did not observe these anomalies in the two CAIs discussed here. Given their similarity, the trace elemental analyses of the mixed interior (i.e. core) and rim phases could be interpreted as forming from similar, if not the same, reservoirs. The REE abundance between the rim and core of Hoopoe are also similar, indicating they may have formed from a gas of the same or similar composition. Acknowledgments: We thank the ASU Center for Meteorite Studies for loaning the samples used in this work and Tabb Prissel for his assistance with the analysis. Mouti Al-Hashimi thanks Sam Crossley and Cyrena Goodrich for their help with the LPI SEM training. This work was supported by the LPI Summer Intern Program in Planetary Science and the LPI Cooperative Agreement. References: [1] Connelly J.N. (2012) Science, 338, 651-655. [2] MacPherson G. J. (2014) Treatise on Geochem., 2, 139-179. [3] Grossman L. (1972) GCA, 36, 597-619. [4] Ebel, D.S. (2006) Meteorites and the Early Solar System II (D. S. Lauretta & H. Y. McSween, Eds.) 253-277. [5] MacPherson G. J. (2012) Earth Planet. Sci. Lett., 331-332, 43-54. [6] MacPherson G.J. (2017) GCA, 201, 65-82. [7] Krot A.N. (1995) Meteoritics & Planet. Sci., 30, 748-775. [8] Wark and Lovering (1982) GCA, 46, 2595-2607. [9] Palme H. and Jones A. (2003) Treatise on Geochemistry (H. D. Holland and K. K. Turekian Eds.), 1, 41-61. [10] Grossman L. (1980) Ann. Rev. Earth Planet. Sci., 8, 559-608. [11] Floss C. et al. (1996) GCA, 60, 1975-1997. [12] Mason B. and Martin P. M. (1974) Earth Planet. Sci. Lett., 22, 141-144. [13] Wark B. and Boynton W. V. (2001) Meteoritics & Planet. Sci., 36, 1135-1166.

X Mouti↗

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 4.

To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 1.0 in 2017, followed by 2.0 in 2018, and 3.0 in 2021. This new release of FRED 4.0 now has 213,941 observations of 238 root traits, for a combined total of roughly 3.4 million data fields for root traits and ancillary data together. FRED 4.0 has 39.8% more root trait observations than FRED 3.0 and a 34.4% increase in unique data sources. This release of FRED 4.0 also includes significant increases in geographic regions that have long been underrepresented in global datasets, notably in the tropical low latitudes. Ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently with root trait observations. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. Despite this fine-root focus, FRED accepts data collected from roots of all sizes and contains observations of many root classes including coarse roots. Data collection will continue for the foreseeable future. The FRED4_Entire_Database_2026.csv file is the flat csv data file for FRED 4.0, and the FRED4_dd.csv file is the data dictionary of all columns available in FRED, including column IDs, column names, definitions, and unit (where applicable).

54 ENVIRONMENTAL SCIENCES↗

Dynamics of the Molten Contact Line

The purpose of this program is to develop a basic understanding of how a molten material front spreads over a solid that is below its melting point, arrests, and freezes. Our hope is that the work will contribute toward a scientific knowledge base for certain new applications involving molten droplet deposition, including the "printing" of arbitrary three-dimensional objects by precise deposition of individual molten microdrops that solidify after impact. Little information is available at this time on the capillarity-driven motion and arrest of molten contact line regions. Schiaffino and Sonin investigated the arrest of the contact line of a molten microcrystalline wax spreading over a subcooled solid "target" of the same material. They found that contact line arrest takes place at an apparent liquid contact angle that depends primarily on the Stefan number S=c(T(sub f) -T(sub t)/L based on the temperature difference between the fusion point and the target temperature, and proposed that contact line arrest occurs when the liquid's dynamic contact angle approaches the angle of attack of the solidification front just behind the contact line. They also showed, however, that the conventional continuum equations and boundary conditions have no meaningful solution for this angle. The solidification front angle is determined by the heat flux just behind the contact line, and the heat flux is singular at that point. By comparing experiments with numerical computations, Schiaffino and Sonin estimated that the conventional solidification model must break down within a distance of order 0.1 - 1 microns of the contact line. The physical mechanism for this breakdown is as yet undetermined, and no first-principles theory exists for the contact angle at arrest. Schiaffino and Sonin also presented a framework for understanding how to moderate Weber number molten droplet deposition in terms of similarity laws and experimentation. The study is based on experiments with three molten materials- molten wax on solid wax, water on ice, and mercury on frozen mercury- which between them span a considerable range of the deposition/solidification similarity parameters. Correlations are obtained for the spreading velocity, spreading time scales, the spreading factor (i.e. ratio of deposited drop's final footprint radius and the drop's initial radius), post-spreading liquid oscillation amplitudes and time scales, and bulk solidification time scales. Duthaler carried out an experimental and theoretical investigation of the relationship between the liquid's apparent contact angle and the Capillary number Ca=mu U/sigma based on contact line speed, for molten materials spreading over subcooled solids. This relationship is required for modeling of melt spreading. We have adapted Voinov's methodology to the molten contact line and formulated a theoretical model for the Ca vs. contact angle relationship, based Schiaffino and Sonin#s (1997a,b) wedge-like solidification front model. With the solidification front angle taken from Schiaffino and Sonin, the model is in good agreement with the experimental results for Ca vs. contact angle. Duthaler also extended the experimental investigation of droplet deposition and contact line freezing to more materials, including solder on glass, solder on solder, water on ice, and molten microcrystalline wax on wax. The latter also included tests on inclined targets. Deposition tests have also been done with molten octacosane (C28H58) on various targets. An important objective of our program has been the development of micron-scale sensors for measuring the transient temperature at a point on the substrate surface as a molten contact line moves over it. The expectation is that this temperature history will yield a better understanding of the thermal process in the contact line region. The sensors are of the thermistor type, either 2.5 microns or 1.5 microns square, microfabricated with silicon-based technology on either pure silicon or amorphous silicon dioxide chips. Each chip has 32 sensors distributed on its surface in arrays. The time response is better than 10 ms. At the time of writing, sensor calibration is in progress. Results on thermal transients during contact line passage will be discussed at the conference. While we expect that the data will provide information on the near-contact-line heat transfer process, we also foresee possible problems. First, the spatial resolution of the sensors may be insufficient to resolve the near-contact-line region. Second, the sensors protrude about 0.5 microns above the substrate surface, and may affect the contact line motion. Third, a sensor's temperature history depends on both the heat flux distribution into it from the fusion front and the thermal properties of the substrate below it and the solidified melt between it and the fusion front. The heat flux distribution in the contact line region must therefore be unfolded from computations of the overall system's transient thermal response.

Sonin, Ain A.↗

Investigating Low-Altitude Constellations of Ad-Hoc Lunar PNT System for Distributed Spacecraft Autonomy

In this study, we examine a low-altitude Lunar Position, Navigation, and Timing (LPNT) constellations and the localization performance of Centralized Extended Kalman Filter (CEKF) and Decentralized Extended Kalman Filter (DEKF) algorithms. The primary investigation involves a 100-node swarm operating at a 100 km altitude, in contrast to previous studies that examined a 21-node asset in a frozen-orbit at 5,500 km. The autonomous operation of large-scale swarm is based on two-way Inter-Satellite Link (ISL) measurements, which involve pseudoranges and relative velocities among swarm nodes. We perform a numerical assessment of the two filtering approaches, utilizing ‘fully sampled’ measurements from all available assets as well as ‘two ISL’ measurements where each spacecraft is restricted to only two antennas. This research includes an analysis of CEKF under 2-ISL constraints and evaluates the performance of DEKF in a 100-node swarm, which has not been explored in previous studies. In addition, we examine the impact of increasing the sampling frequency for DEKF, showing that the update cycle can be shortened from a 10-minute interval. A novel approach for ‘2-ISL limited’ DEKF will also be introduced, using a matching formulation that exhaustively enumerates all potential matches. This study provides valuable insights into large-scale distributed swarm operations, considering various filter configurations, sampling frequencies, matching strategies, and scalability of CEKF and DEKF for low-altitude LPNT applications. The Lunar PNT technology plays a key role in providing reliable and robust navigation services on the Moon's surface and the South pole, where the primary Lunar missions are planned. To support upcoming Lunar missions, including small satellites from NASA's Commercial Lunar Payload Services program, the Lunar PNT system must be adaptable to smaller platforms like CubeSats. Driven by the growing involvement of public and private exploration partnerships, the traditional low Earth orbit missions are shifting to beyond geosynchronous orbit [1]. These upcoming missions aim to foster a sustainable and innovative exploration program, in collaboration with commercial and international partners, to facilitate human expansion throughout the solar system and return new knowledge and opportunities to Earth [2]. As part of this trend, there are increasing efforts to utilize science missions in Lunar orbit to develop a non-dedicated and ad-hoc PNT network system. Two traditional approaches, the Deep Space Network (DSN) and the weak signal Global Positioning System (GPS), are established deep-space navigation technologies for missions beyond the geosynchronous orbit. Beginning in 1958, the DSN was developed to communicate with the Explorer 1 spacecraft based on the use of radiometric tracking in spacecraft navigation [3]. The DSN is capable of providing nearly unfettered coverage to spacecraft beyond low-Earth orbit (LEO), however, increased space mission volume has created concerns about future expectations of DSN usage for spacecraft navigation [4]. For cislunar mission applications, the position accuracy using DSN achieves 100 m (3σ) with at least three geometrically diverse ground stations when using radiometric tracking alone [5]. The DSN's dependence on Earth-based ground stations restricts its operational capabilities to periods of Earth visibility. This limitation, coupled with its poor localization performance, renders the DSN unsuitable for future lunar missions that demand continuous tracking and precise positioning. To satisfy the increasing requirements of DSN in Lunar applications, spacecrafts are also required to improve their onboard antenna power and efficiency of the transmission. However, there is an important aggregate cost trade between adding capabilities to every spacecraft and adding to a capacity on the ground that serves multiple spacecraft [6]. A weak GPS system can provide PNT service while the user spacecraft is bound to the Moon, leveraging a single, steerable high gain antenna with the relatively narrow beam which includes all the sources in its field of view [7]. However, the higher the altitude the receiver is above the GPS constellations, the poorer and the weaker are the relative geometry and the received signal powers, respectively, leading to a significant navigation accuracy reduction [8]. The transmitted power becomes weaker with increasing distance from the Earth as well as signals tracked from one of the side lobes of the GPS antenna pattern. As a results, the number of visible satellites and relative geometric condition of the GPS satellites at very high altitude drops dramatically and reduces the navigation solution accuracy. Therefore, the weak GPS system is also not an ideal way to provide PNT service to upcoming Lunar missions when considering its limited geometric condition and the recued navigation accuracy. Another navigation approach on the Moon is being developed, similar to the Global Navigation Satellite System (GNSS) on Earth, aiming to offer navigation service with continuous 24/7 coverage across the entire Lunar surface. For example, lunar communications relay and navigation systems (LCRNS) by NASA and Lunar navigation satellite systems (LNSS) by JAXA are designed to serve as dedicated Position, Navigation, and Timing (PNT) systems for the Moon. However, designing a dedicated LNSS and PNT service involves additional challenges, which are unique to the lunar environment, including limited payload capacity for the CubeSat platform, i.e., the size, weight, and power (SWaP) of the onboard clock, limited lunar ground monitoring stations, and limited financial investment as compared to the legacy Earth-GPS [9]. NASA’s focus on utilizing CubeSat platforms on the Moon leads to an alternative Lunar navigation platform that leverages the existing Lunar science and exploration assets. The small satellites used in Lunar missions can be used to create a low-cost, autonomous, ad-hoc, and on-demand mission-centric Lunar PNT swarm capable of providing PNT services to these low-cost lunar missions [10]. As upcoming Lunar missions will often operate at low-altitude about 30 km to 100 km for scientific observations and mapping purposes, the low-altitude orbital constellations could be employed to create an ad-hoc Lunar PNT system. However, several issues must be addressed, such as the instability of these orbits, which often require maintenance or are only suitable for short-duration missions, operating for fewer than 90 days. Additionally, at an altitude of 100 km, the satellites have a limited period during which they are above the horizon and capable of providing PNT service to users. The implementation of a non-dedicated, ad-hoc Lunar navigation constellation facilitates on-demand PNT services. A preliminary study of ad-hoc Lunar PNT system was conducted using 21 spacecraft in 5,5000 km altitude frozen orbits to test its feasibility and a basic performance of orbital asset localization among ad-hoc Lunar constellations in small satellites format [10]. These swarm assets are designed for autonomous localization with minimal Earth interaction, reducing dependency on bandwidth and ground resources. The design in [10] demonstrated the feasibility of a decentralized PNT approach, specifically employing a DEKF approach for state estimation, which helps minimize onboard operating costs. The DEKF method distributes computation across individual satellites, which lightens the computational load while maintaining accuracy in orbit ephemeris and clock offsets, similar to centralized systems [11]. In a follow-on study [12], each spacecraft was limited to 2 communications antennae, forcing the selection of measurements and scheduling spacecraft activities to perform the measurements. A matching algorithm is implemented to select the best measurements and schedule position estimation updates. The decentralized localization performance is also investigated with increasing levels of network degradation for swarm assets considering the impact of intermittent and permanent communication failure, to demonstrate the robustness and fidelity of the decentralized Lunar PNT service [13]. This study confirmed that the ad-hoc PNT constellations in frozen orbit are highly robust and resilient to communication failures. However, unlike frozen orbit swarm assets, the low-altitude satellites have a limited ground view at an altitude of 100 km, where the ad-hoc Lunar constellation consists of 98 low-altitude satellites, evenly distributed across seven circular polar orbital planes, alongside two satellites in a frozen orbit at an altitude of 5,500 km (Figure 1). Therefore, the number of satellites visible to ground users is significantly limited in low-altitude orbit constellations. As each visibility of a spacecraft remains intact for only a few ticks before it moves out of the field of view, the ground user encounters challenges in maintaining continuous navigation service, resulting in sparse availability and provision of Lunar PNT system. Consequently, service availability is primarily restricted to the Lunar South Pole region (Figure 2). Given these limitations and concerns, the localization performance of low-altitude swarm assets will be assessed in this study. We focus on the investigation of the localization performance of low-altitude swarm assets and ground users near the Lunar South Pole. The overall flow of the Lunar PNT simulation incorporates the DEKF approach of asset localization and the weighted least-squares approach in user localization (Figure 3). The autonomous Lunar PNT simulation is primarily implemented in MATLAB, where the DEKF based on the matching scheduler is implemented with Google’s OR-tools as a model builder and Gurobi optimization tool as a backend solver. The General Mission Analysis Tool (GMAT) is utilized to generate ephemeris data for swarm assets, and accounts for satellite orbital details, mass, and perturbations like solar radiation pressure and drag coefficients. Each ephemeris dataset is produced in the Moon International Celestial Reference Frame (ICRF) inertial coordinate system. For state estimation, the distributed swarm assets rely on two-way Inter-Satellite Link (ISL) measurements, which involve tracking pseudoranges and relative velocities between visible satellites and anchor nodes during each observation. Numerical evaluations of the decentralized localization process are conducted to demonstrate the feasibility of the low-altitude PNT system in providing reliable navigation services. The main approach involves using DEKF and CEKF to localize 100 satellites in low-altitude constellations, where the CEKF is implemented to serve as a baseline for comparing the performance of distributed algorithms. In both cases, we evaluate ‘fully sampled’ measurements from all available assets, and ‘two ISL’ measurements when spacecraft are constrained to have only two antennas. We test four estimation techniques: CEKF fully sampled, CEKF two ISL, DEKF fully sampled, and DEKF two ISL filters. As the DEKF update cycle is comprised of network setup, communication, and computations, a global broadcast network and 2-way ISL network setup will take from 4 to 6 minutes as maximum [12]. In this simulation, the DEKF update cycle is set to 10 minutes, including a 4-minute latency for obtaining and computing the actual measurement updates. We experiment an increased update cycle to demonstrate the feasibility and evaluate the impact on localization performance using various tuning values for measurement noise covariances (Figures 4 and 5). By comparing centralized and decentralized approaches using a matching algorithm, we analyze the influence of cross-correlation factors in the covariance matrix, assuming 100% reliability of all assets and measurements. The increased frequency and the adjustments of tuning parameters reveal distinct error patterns between the two scenarios. The localization accuracy of the swarm assets and ground users is assessed by taking the median error across 100 assets and one ground user (84.9°S, 137.5°E) over 7-day simulation period (Table 1). Since the user localization accuracy is significantly affected by the performance of the swarm assets, it is crucial to maintain high localization accuracy within the swarm. This study will continue to explore decentralized filtering for autonomous LPNT operations, with further investigation of an 'iterative' matching approach which enumerates every valid matching pair, planned for the following month.

Yeji Kim↗

Studying Aerosol, Clouds, and Air Quality in the Coastal Urban Environment of Southeastern Texas

A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.

54 ENVIRONMENTAL SCIENCES↗