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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Testing Seam Concepts for Advanced Multilayer Insulation

Multilayer insulation (MLI) is considered the state of the art insulation for cryogenic propellant tanks in the space environment. MLI traditionally consists of multiple layers of metalized films separated by low conductivity spacers. In order to better understand some of the details within MLI design and construction, GRC has been investigating the heat loads caused by multiple types of seams. To date testing has been completed with 20 layer and 50 layer blankets. Although a truly seamless blanket is not practical, a blanket lay-up where each individual layer was overlapped and tapped together was used as a baseline for the other seams tests. Other seams concepts tested included: an overlap where the complete blanket was overlapped on top of itself; a butt joint were the blankets were just trimmed and butted up against each other, and a staggered butt joint where the seam in the out layers is offset from the seam in the inner layers. Measured performance is based on a preliminary analysis of rod calibration tests conducted prior to the start of seams testing. Baseline performance for the 50 layer blanket showed a measured heat load of 0.46 Watts with a degradation to about 0.47 Watts in the seamed blankets. Baseline performance for the 20 layer blanket showed a measured heat load of 0.57 Watts. Heat loads for the seamed tests are still begin analyzed. So far analysis work has suggested the need for corrections due to heat loads from both the heater leads and the instrumentation wires. A careful re-examination of the calibration test results with these factors accounted for is also underway. This presentation will discuss the theory of seams in MLI, our test results to date, and the uncertainties in our measurements.

multilayer insulation↗
NASA NTRS2017

Using Advanced Mass Spectrometry Techniques to Fully Characterize Atmospheric Organic Carbon: Current Capabilities and Remaining Gaps

Organic compounds in the atmosphere vary widely in their molecular composition and chemical properties, so no single instrument can reasonably measure the entire range of ambient compounds. Over the past decade, a new generation of in-situ, field-deployable mass spectrometers has dramatically improved our ability to detect, identify, and quantify these organic compounds, but no systematic approach has been developed to assess the extent to which currently available tools capture the entire space of chemical identity and properties that is expected in the atmosphere. Reduced-parameter frameworks that have been developed to describe atmospheric mixtures are exploited here to characterize the range of chemical properties accessed by a suite of instruments. Multiple chemical spaces (e.g. oxidation state of carbon vs. volatility, and oxygen number vs. carbon number) were populated with ions measured by several mass spectrometers, with gas- and particle-phase α-pinene oxidation products serving as the test mixture of organic compounds. Few gaps are observed in the coverage of the parameter spaces by the instruments employed in this work, though the full extent to which comprehensive measurement was achieved is difficult to assess due to uncertainty in the composition of the mixture. Overlaps between individual ions and regions in parameter space were identified, both between gas- and particle-phase measurements, and within each phase. These overlaps were conservatively found to account for little (<10%) of the measured mass. However, challenges in identifying overlaps and in accurately converting molecular formulas into chemical properties (such as volatility or reactivity) highlight a continued need to incorporate structural information into atmospheric measurements.

G. Isaacman-VanWertz↗
NASA NTRS2019

Aerodynamic and Aerothermal Simulations of Mars Concept Vehicles Using Overset DPLR

NASA's Descent System Studies (DSS) Program is studying various concept vehicles to enable landing of heavy payloads on the surface of Mars. While it is desirable to run high-fidelity CFD simulations to accurately assess the aerodynamic and aerothermal effects of various design changes during EDL, it is usually difficult to quickly generate high-quality grids suitable for such analyses. One approach to address this bottleneck in mesh generation is through the use oversetting grids. Although the overset approach is efficient and powerful in solving partial differential equations on complex geometries, new users often find it challenging to apply overset concepts for their simulations. For example, generating hyperbolic grids with sufficient overlap; priority in hole-cutting on multiple overlapping grids; and fixes to assemble overlapping viscous grids at the body surface. The objective of this presentation is to introduce a simple process that combines the advantages of near-body, point-matched, structured grids with oversetting background grids suitable for grid alignment. This approach allows for grids that can be sequenced, reclustering of mesh spacing at the wall, and grid alignment with the bow shock. The current methodology is tested on a Mid-L/D configuration using the overset DPLR code.

Overset Grids↗
NASA NTRS2019

No Pixel Left Behind: Interactively Visualizing ''Everything'' from NASA's Earth Observations

The problem: satellite swath overlaps. Polar orbiting satellites like Terra, Aqua, and the joint NASA/NOAA Suomi-NPP satellite circle the globe from pole to pole, collecting data daily, swath by swath. Having this density of data is great for building a comprehensive mosaic of the planet, but sometimes there is something interesting occurring in one swath but is covered by a subsequent swath when the satellite passes over 90 minutes later. With our new prototype based on Worldview and the Global Imagery Browse Services (GIBS), we combine the best of both worlds to interactively visualize the entire globe as a mosaic and allow the user to _peel away the overlaps_ to see every pixel that was observed by the satellite. This ability to look at every pixel - and to know when they were captured - is especially important near the poles where swath overlaps are most common.

Boller, R.↗
NASA NTRS2012

TPSAS-NF1676L-13555-DND

A sub-scale advanced composite shell design is evaluated to determine its potential for use on a future aircraft fuselage. Two composite shells with the same nominal 8-ply [?45/?]s layup are evaluated, where ? indicates a tow-steered ply. To build this shell, a fiber placement machine is used to steer unidirectional prepreg tows as they are placed around the circumference of a 17-inch diameter right circular cylinder. The fiber orientation angle varies continuously from 10 degrees (with respect to the shell axis of revolution) at the crown, to 45 degrees on the side, and back to 10 degrees on the keel. All 24 tows are placed at each point on every fiber path in one structure designated as the shell with overlaps. The resulting pattern of tow overlaps causes the laminate thickness to vary between 8 and 16 plies. The second shell without tow overlaps uses the capability of the fiber placement machine to cut and add tows at any point along the fiber paths to fabricate a shell with a nearly uniform 8-ply laminate thickness. Static stiffness and buckling loads of shells with tow-steered layups are compared with the performance of a baseline quasi-isotropic shell using both finite element analyses and classical strength of materials theory. These tailored, tow-steered shells were then were designed and built at the National Center for Advanced Manufacturing - Louisiana Partnership under a joint NASA-industry collaborative effort. The shells were fabricated from unidirectional IM7/8552 graphite-epoxy pre-preg slit tape material placed on a constant-diameter mandrel. An overview of the detailed design and manufacturing processes for these shells is presented, and issues encountered during their design, analysis, fabrication and post-cure evaluation are presented and discussed. Future plans for structural testing and analyses of the shells are also discussed.

K Chauncey Wu↗
NASA NTRS2021

Goldstone Orbital Debris Radar: A Historical Review from a Decade of Observations (2007 – 2017)

The NASA Orbital Debris Program Office (ODPO) has utilized the Goldstone bistatic radar since the early1990’s to statistically characterize the low Earth orbit(LEO) sub-centimeter population. The radar provides a unique capability to detect orbital debris population sizes down to an approximate size of 3 mm for altitudes less than 1000 km, and even smaller sizes at lower altitudes. Due to the limited number of hours that are available from this radar each year, it is often used to validate measurements obtained by other radar data sources in the range of orbital debris sizes where the radar systems have an overlap. Additionally, the Goldstone radar provides significantly improved sensitivity than is available from other ground-based radar data sources, which enables it to observe orbital debris populations that, although smaller, still represent a significant risk to both robotic and human missions in LEO. Over the decade of observations from 2007 to2017, a number of significant on-orbit events have occurred including the anti-satellite test againstFengyun-1C, and the accidental collision between Cosmos 2251 and Iridium 33. The orbital debris flux as measured by the Goldstone radar over this important time period is reviewed in this paper, as well as the evolution of the environment over the ensuing years since these events. In addition, the measurements provided by this radar in the years prior to the deployment of large constellations into the environment, as well as the significant increase in missions and mission participants in recent years, is of interest since it provides a baseline for monitoring the effects of these and other changes in the coming years. In 2018, the Goldstone bistatic orbital debris radar pointing geometry changed due to the decommissioning of the nearby receiver antenna, Deep Space Station (DSS) 15, located approximately 500 m from the transmitter antenna. The historical combination of the DSS-14 transmitter and DSS-15receiver enabled all of LEO to be observed using a single pointing due to the close proximity of the two antenna stations and the resulting beam overlap of the bistatic radar geometry. The updated bistatic Goldstone geometry, following the decommissioning of DSS-15,utilizes one of the pair of DSS-25 or DSS-26 antennas that are located approximately 10 km from the transmitter station. The resulting beam overlap with this pointing is such that in LEO, only a small fraction of LEO altitude coverage is observable at one time. Given the operational change of the radar, it is of interest to review the data collected by the original Goldstone bistatic radar over the final decade preceding this change.

Rossina Miller↗
NASA NTRS2021

GEWEX (Global Energy and Water Exchanges Project): Surface Radiation Budget (SRB) Release 4 Integrated Product (IP4) - Algorithm Theoretical Basis Document and Evaluation

The World Climate Research Programme’s (WCRP) Global Energy and Water Exchanges (GEWEX) program is an integrated program of research, observations, and science activities with the mission to “Observe, understand and model the hydrological cycle and energy fluxes in the Earth’s atmosphere and at the surface.” Since the public release in 2010 of SRB Release 3, GEWEX reorganized to formulate the Data and Assessments Panel (GDAP) aimed at performing community assessments of the long-term global data products with focus on integrating various data products to address issues in the closing of the global energy and water cycles. SRB Release 4 Intergrated Product (Rel4-IP) integrates data products from the cloud, aerosol, atmosphere, ocean surface, and land surface projects within GDAP to produce a long-term time series of Top-of-Atmosphere (TOA) and surface radiative estimates. This Algorithm Theoretical Basis Document (ATBD) describes the various inputs, algorithms and resulting top-of-atmosphere and surface flux products that span from July 1983 through June 2017. Comparisons of the TOA flux products are made to overlapping CERES data products when possible. The surface radiative flux products are assessed relative to the globally distribution Baseline Surface Radiation Network measurements sites. Variability of the various products are compared to ERBE and CERES during overlapping time periods. The variability of the product show excellent correspondent to CERES during overlap years and improved statistical agreement with surface measurements. This document also discusses known issues with the data products to help the user understand the uncertainty and known issues.

Surface radiation budget↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.

Machine Learning↗
DOE OSTI2026

A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations

We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8

Sanders, N. [Ohio U., Athens] (ORCID:0009000800202↗
DOE OSTI2025

A Fundamentally New Coupled Approach to Contact Mechanics via the Dirichlet‐Neumann Schwarz Alternating Method

Contact phenomena are crucial for understanding the behavior of mechanical systems. However, existing computational approaches for simulating mechanical contact often face numerical challenges, such as inaccurate physical predictions, energy conservation errors, and unwanted oscillations. Here, we introduce an alternative technique for simulating dynamic contact based on the non‐overlapping Schwarz alternating method, originally developed for domain decomposition. In multibody contact scenarios, this method treats each body as a separate, non‐overlapping domain and prevents interpenetration using an alternating Dirichlet–Neumann iterative process. This approach has a strong theoretical foundation, eliminates the need for contact constraints, and offers flexibility, making it ideal for multiscale and multiphysics applications. We conducted a numerical comparison between the Schwarz method and traditional methods, such as the Lagrange multiplier and penalty methods, focusing on a benchmark impact problem. Our results indicate that the Schwarz alternating method outperforms traditional methods in several key areas: it provides more accurate predictions for various measurable quantities and demonstrates exceptional energy conservation capabilities. To address unwanted oscillations in contact velocities and forces, we explored various algorithms and stabilization techniques, ultimately opting for the naïve‐stabilized Newmark scheme for its simplicity and effectiveness. Additionally, we validated the efficiency of the Schwarz method in a three‐dimensional impact problem, highlighting its inherent capacity to accommodate different mesh topologies, time‐integration schemes, and time steps for each interacting body.

Schwarz alternating method↗
DOE OSTI2025

Human IgE monoclonal antibodies define two unusual epitopes trapping dog allergen Can f 1 in different conformations

Abstract Molecular analysis of interactions between IgE antibody and allergen allows the structural basis of IgE recognition to be defined. Human IgE (hIgE) epitopes of respiratory lipocalin allergens, including Can f 1, remain elusive due to a lack of IgE‐allergen complexes. This study aims to map the structure of allergenic epitopes on Can f 1. The fragment antigen‐binding (Fab) regions of Can f 1 specific human IgE monoclonal antibodies (hIgE mAb) were used to determine the structures of IgE epitopes. Epitope mutants were designed to target Can f 1 epitopes. Immunoassays and a human FcεRIαtransgenic mouse model of passive anaphylaxis in vivo were used to assess the functional activity of epitope mutants. Crystal structures of natural or recombinant Can f 1 complexed with two hIgE mAb 1J11 and 12F3 Fabs, respectively, were determined. The hIgE mAb bound to two partially overlapping epitopes and recognized two different Can f 1 conformations. The hIgE mAb 12F3 showed an unusual mode of binding by protruding its heavy chain CDR3 inside the Can f 1 calyx. Epitope mutants generated based on the structural analyses displayed a 64%–89% reduction in IgE antibody binding and failed to induce passive anaphylaxis in a human FcεRIαtransgenic mouse model. In summary, the structures of Can f 1‐hIgE Fab complexes revealed two unique and partially overlapping epitopes on Can f 1. The modification of the identified IgE epitopes provides a pathway for the design of hypoallergens to treat dog allergies.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗
DOE OSTI2025

Coupling Approaches with Non-matching Grids for Classical Linear Elasticity and Bond-based Peridynamic Models in 1D

Local-nonlocal coupling approaches provide a means to combine the computational efficiency of local models and the accuracy of nonlocal models. To facilitate the coupling of the two models, non-matching grids are often desirable as nonlocal grids usually require a finer resolution than local grids. In that case, it is often convenient to resort to interpolation operators so that models can exchange information in the overlap regions when nodes from the two grids do not coincide. This paper studies three existing coupling approaches, namely 1) a method that enforces matching displacements in an overlap region, 2) a variant that enforces a constraint on the stresses instead, and 3) a method that considers a variable horizon in the vicinity of the interfaces. Further, the effect of the interpolation order and of the grid ratio on the performance of the three coupling methods with non-matching grids is carefully studied on one-dimensional examples using polynomial manufactured solutions. The numerical results show that the degree of the interpolants should be chosen with care to avoid introducing additional modeling errors, or simply minimize these errors, in the coupling approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unraveling Hydrogen Induced Geochemical Reaction Mechanisms through Coupled Geochemical Modeling and Machine Learning

Underground hydrogen storage (UHS) provides a promising large-scale, long-term energy storage solution. A reasonable recovery of stored hydrogen is critical for a successful storage scheme. However, in subsurface reservoirs hydrogen is subject to active geochemical reactions that might result in hydrogen loss. In this study, we implemented a geochemical modeling approach coupled with an unsupervised machine learning technique called non-negative matrix factorization (NMF) to unravel the complex brine-rock-H 2 geochemical processes responsible for hydrogen losses, with particular focus on sulfate reduction reactions. NMF is applied to modeled mineral evolution and fluid component profiles to retrieve profiles that can be interpreted to more easily assess competing processes. NMF decouples simulated competing equilibrium reactions. This facilitates separation of overlapping reaction profiles from redox processes, dissolution fronts, and secondary precipitation while considering the effects of simulation parameters such as salinity, temperature, and total H 2 pressure. NMF successfully discriminates these competing effects in nonlinear ways, allowing robust interpretation. In addition, NMF reveals subtle coupled mineral associations and reaction fronts that are invisible to conventional model analysis. This integrated approach strengthens the conceptual understanding of complex nonlinear hydrogen-brine-rock interactions and advances geochemical research on UHS systems to resolve complexities in modeled geochemical systems without the need for direct experiments or prior knowledge. Furthermore, this study highlights the efficacy of combining geochemical modeling with machine learning techniques to enhance the interpretability of the intricate geochemical simulation output through deciphering the overlapping reaction path that cannot be achieved only using conventional analysis of geochemical models alone.

08 HYDROGEN↗
DOE OSTI2026

Localization and functional exploration of leiomodin-2’s C-terminal binding sites

Striated muscle contraction occurs through interactions between overlapping myosin-based thick and actin-based thin filaments within the sarcomere. For effective contraction to occur, the length of the thin filament must be maintained to allow for sufficient overlap with the thick filament. The proteins leiomodin and tropomodulin compete for binding at the pointed end of thin filaments to regulate their length, utilizing their homologous N-terminal actin and tropomyosin binding sites. Leiomodin also has a region called the C-terminal extension, absent in tropomodulin. In this region, the cardiac isoform (leiomodin-2) contains additional actin-binding sites that enable it to bind along the sides of thin filaments in a Ca2+-dependent manner. Here, using nuclear magnetic resonance spectroscopy, we localize the regions of the C-terminal extension that contain residues involved in thin filament side-binding. Using co-sedimentation assays, we reveal that these regions can independently bind thin filaments and discover that the poly-proline region plays a role as a linker, maintaining an adequate distance between two of the regions required for effective interaction to occur. In addition to its role in side-binding, we provide direct evidence that the poly-proline region interacts with profilin and propose a new mechanism by which leiomodin-2 may assist in the polymerization of profilin-bound actin at thin filament pointed ends.

ACTIN-BINDING PROTEINS↗
DOE OSTI2025

General field evaluation in high-order meshes on GPUs

Robust and scalable function evaluation at any arbitrary point in the finite/spectral element mesh is required for querying the partial differential equation solution at points of interest, comparison of solution between different meshes, and Lagrangian particle tracking. This is a challenging problem, particularly for high-order unstructured meshes partitioned in parallel with MPI, as it requires identifying the element that overlaps a given point and computing the corresponding reference space coordinates. Here, we present a robust and efficient technique for general field evaluation in large-scale high-order meshes with quadrilaterals and hexahedra. In the proposed method, a combination of globally partitioned and processor-local maps are used to first determine a list of candidate MPI ranks, and then locally candidate elements that could contain a given point. Next, element-wise bounding boxes further reduce the list of candidate elements. Finally, Newton’s method with trust region is used to determine the overlapping element and corresponding reference space coordinates. Since GPU-based architectures have become popular for accelerating computational analyses using meshes with tensor-product elements, specialized kernels have been developed to utilize the proposed methodology on GPUs. The method is also extended to enable general field evaluation on surface meshes. The paper concludes by demonstrating the use of the proposed method in various applications ranging from mesh-to-mesh transfer during r-adaptivity to Lagrangian particle tracking.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hurricanes and turbulent floods threaten arsenic-contaminated coastal soils and vulnerable communities

Coastal environments, particularly those adjacent to Superfund sites, are at increased risk of contaminant release during natural disasters, posing serious threats to nearby communities. To investigate this issue, we employed an advanced laboratory flood simulator to impose arsenic-contaminated sediments to turbulent flooding events. We further monitored changes in arsenic collocation and solid-phase speciation using advanced synchrotron radiation-based techniques to understand the impacts of flooding on arsenic mobility. Our results demonstrate that turbulent conditions significantly enhance the resuspension of arsenic-rich sediments, resulting in increased arsenic release into the water. This mobilization is driven by the erosion of the reduced sediments and the redox-mediated transformation and dissolution of Fe and Mn (oxyhydr) oxides, which promote the release of As(III). We found that arsenic speciation on resuspended particles is closely tied to shear stress, with As(V) prevailing at low stress and the more toxic As(III) dominating at higher stress levels. In the post-erosion phase, solid-phase As(III) decreased while dissolved As(III) increased, indicating ongoing desorption. The persistence of multiple arsenic species on resuspended particles marks them as potential long-range transport vectors. Thus, the environmental impact of flooding and sediment resuspension extends beyond the event itself, raising longer-term concerns for arsenic mobility. Our comprehensive geospatial analysis revealed substantial overlap between arsenic-contaminated soils and regions at high risk of flooding and hurricanes across the conterminous United States. This overlap disproportionately impacts economically disadvantaged and marginalized communities. Approximately 40 million Americans reside within 10 kilometers of these high-risk contaminated zones, with nearly 28 million exposed to hurricane threats and around 18 million vulnerable to flooding risks. Alarmingly, over 40% of those affected by hurricanes and 33% of those impacted by flooding belong to underrepresented minority and low-income populations. These findings highlight the urgent need for targeted mitigation strategies to protect public health and address environmental justice concerns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A collective trigger for widespread planetesimal formation revealed by accretion ages

The formation of planetesimals was an integral part of the cascading series of processes that built the terrestrial planets. To illuminate planetesimal formation, here we develop a refined thermal evolution model to calculate the formation ages of meteorite parent planetesimals. This model includes chemical reactions and phase changes during heating, as well as natural variations in the proportions of the constituent phases of these planetesimals. We find that the parent bodies of non-carbonaceous (NC) and carbonaceous (CC) iron meteorites start forming at very similar times ( ∼ 0.95 Myr after calcium-aluminium-rich inclusion [CAI] formation) and occupy overlapping time windows. NC and CC chondrite parent bodies formed later during non-overlapping periods. We combine these ages with proportions of isotopic end-members we recover from mixing models to construct records of motion throughout the protoplanetary disk. These records argue that NC and CC material traversed the barrier in the disk after ∼ 0.95 Myr after CAI formation. The onset of this motion coincided with planetesimal formation, indicating that the phenomenon that drove motion also triggered planetesimal formation. We argue that this feature also served as the semi-permeable barrier in the disk. Although its identity is uncertain, the effects this phenomenon had on the timing of planetesimal formation and motion through the disk can now serve as constraints on models of disk evolution. Models that reproduce these effects would elucidate the nature and implications of this phenomenon, which is key to unlocking a holistic model of terrestrial planet building.

Astronomy and AstroPhysics↗