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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 NTRS2004

Ejecta Generation and Redistribution on 433 Eros: Modeling Ejecta Launch Conditions

The NEAR-Shoemaker mission to asteroid 433 Eros presents an unprecedented opportunity to gain fundamental new knowledge about the processes governing regolith formation and redistribution on small bodies. NEAR-Shoemaker’s high-resolution imaging of the surface of Eros makes the asteroid a valuable and heretofore unparalleled laboratory for the detailed study of impact ejecta reaccretion and regolith redistribution on low-gravity (of order 10 -3 g) objects. Regolith is produced on asteroids by impact cratering, and the existence of regolith on the smallest solar system bodies supports the view that some of the ejecta from impact events on such objects may be retained. Impact craters and retained ejecta on low-gravity objects like Eros represent valuable natural laboratories for evaluating various models of impact cratering processes, since they may present crater structures or ejecta features that either do not form or are hidden on higher-gravity bodies like the Moon. Further, quantifying the extent to which impact processes generate and redistribute regoliths on small body surfaces (excavation depths, retained fraction, turnover timescales, etc.) is pivotal to the issue of how to relate meteoritical samples to their asteroidal parent bodies when surficial processes ( i.e., “space weathering”) may disguise or cover up underlying material and confound the ability of remote sensing techniques to provide reliable mineralogical assays of the parent objects. The rich variety of data on Eros’ regolith properties and distribution returned by NEAR-Shoemaker now require detailed analysis in order to take full advantage of the clues these observations offer for elucidating details of the impact cratering process on small bodies. Complicating simple interpretations of crater and ejecta morphology are dynamical effects on ejecta emplacement resulting from Eros’ irregular shape, rapid (5.27 hr) rotation, and low gravity. Figure 1 shows the very different ejecta deposit morphology that can result if the effects of rotation alone are neglected. Considering the additional complicating factors of Eros’ irregular shape and complex gravitational field, simple calculations of the extent and thickness of ejecta blankets and the spatial distribution of ejecta blocks from basic crater scaling laws or numerical hydrocodes alone do not suffice. In order to fully interpret the suite of NEAR-Shoemaker observations of regolith features across the surface of Eros and to evaluate various impact models for specific craters on the asteroid, detailed dynamical modeling of the deposition of crater ejecta from those craters is required . Here, I describe some modifications and improvements to the dynamical model being used for these studies.

D D Durda↗
NASA NTRSDate not supplied

Using Open Innovation in Reducing Risk to Crews

In the exploration of destinations outside of Earth's neighborhood, specifically Mars, scientific and engineering inquiries have occurred by two means; observations from satellites and observations by landed spacecraft. Satellite observations (Mariner, MRO, Mars Odyssey, provide global-scale spatial and temporal data while landed spacecraft (Viking, Mars Pathfinder, Spirit, Opportunity, Phoenix Mars Lander) investigate highly localized areas of the surface of the planet. In preparation for human exploration, extensive knowledge of the surface and atmospheric environments should be known before the first human leaves Earth. The primary goal of performing reconnaissance on Mars on a sub-global scale is to know as much as possible about the environment to which crews will be subjected. At the current rate of launching and landing probes to Mars, it will take a very long time to understand the surface and atmospheric conditions associated with the regions where prospective crews may land. Meanwhile electronics and electrical systems are rapidly getting smaller. One can argue that to acquire the knowledge of the region, one must take hundreds, maybe thousands of measurements simultaneously. One means to perform such a task is to deploy a swarm of sensors. Such a swarm would perform an in-situ assessment of the region. Imagine a close flyby mission to Mars for example, where mini- to micro-sensors are deposited into the atmosphere over half an orbit or more. The sensors, captured by the atmospheric drag and Martian gravity slowly descend buffeted about by Martian winds and weather until they settle on the surface a great time later (think of how long dust takes to settle). As they descend they communicate a vast array of data; temperature, chemistry, pressure, radiation dose, electric or magnetic properties from a region of the planet and an individual sensor need not measure the same quantity as its neighbors. Initially, they could move at the whim of the environment but later versions could have locomotion or propulsion mechanisms. Humans wouldn't need to decide where the sensors go, the sensors do that for themselves. This is a key strength of a sensor swarm. The intelligence relies on the group not on a decision maker on earth. Real time sensor inputs direct what the swarm considers most interesting to investigate resulting in emergent behavior. We issued a $20,000 challenge to the global innovators to provide solutions as to how such a swarm could be initialized and by what protocols and methodologies by which they operate. Over 400 innovators from 49 countries took a look at the problem, with three receiving partial awards for solutions.

Mel Ferebee↗
NASA NTRS1993

Radio Metric Errors Due to Mismatch and Offset Between a DSN Antenna Beam and the Beam of a Troposphere Calibration Instrument

Two components of the error of a troposphere calibration measurement were quantified by theoretical calculations. The first component is a beam mismatch error, which occurs when the calibration instrument senses a conical volume different from the cylindrical volume sampled by a Deep Space Network (DSN) antenna. The second component is a beam offset error, which occurs if the calibration instrument is not mounted on the axis of the DSN antenna. These two error sources were calculated for both delay (e.g., VLBI) and delay rate (e.g., Doppler) measurements. The beam mismatch error for both delay and delay rate drops rapidly as the beamwidth of the troposphere calibration instrument (e.g., a water vapor radiometer or an infrared Fourier transform spectrometer) is reduced. At a 10-deg elevation angle, the instantaneous beam mismatch error is 1.0 mm for a 6-deg beamwidth and 0.09 mm for a 0.5-deg beam (these are the full angular widths of a circular beam with uniform gain out to a sharp cutoff). Time averaging for 60-100 sec will reduce these errors by factors of 1.2-2.2. At a 20-deg elevation angle, the lower limit for current Doppler observations, the beam-mismatch delay rate error is an Allan standard deviation over 100 sec of 1.1 x 10 -14 with a 4-deg beam and 1.3 x 10 -15 for a 0.5-deg beam. A 50-m beam offset would result in a fairly modest (compared to other expected error sources) delay error (less than or equal to 0.3 mm for 60-sec integrations at any elevation angle is greater than or equal to 6 deg). However, the same offset would cause a large error in delay rate measurements (e.g., an Allan standard deviation of 1.2 x 10 -14 over 100 sec at a 20-deg elevation angle), which would dominate over other known error sources if the beamwidth is 2 deg or smaller. An on-axis location is essential for accurate troposphere calibration of delay rate measurements. A half-power beamwidth (for a beam with a tapered gain profile) of 1.2 deg or smaller is desired for calibration of all types of radio metrics. A water-vapor radiometer calibration beam of this size with very low sidelobes would require a clear aperture antenna with a diameter of at least 1.5 m if the primary water vapor sensing channel were in the 20-22 GHz range.

R P Linfield↗
DOE OSTI2025

Generalized geometric speed limits for quantum observables

Leveraging quantum information geometry, we derive generalized quantum speed limits on the rate of change of the expectation values of observables. These bounds subsume and, for Hilbert space dimension ≥3, tighten existing bounds—in some cases by an arbitrarily large multiplicative constant. Our theoretical results are supported by illustrative examples and an experimental demonstration using a superconducting qutrit. We also derive two upper bounds on the generalized quantum Fisher information in terms of the condition number of the density matrix. One of these bounds applies only to coherent dynamics and depends also on the variance of the Hamiltonian. The other bound depends also on the so-called Wigner-Yanase skew information. These bounds generalize well-known bounds on the symmetric logarithmic derivative quantum Fisher information and are tighter than the existing bounds for sufficiently mixed states (e.g., for sufficiently high temperature thermal states).

open quantum systems & decoherence↗
DOE OSTI2023

Thermal Disorder‐Induced Strain and Carrier Localization Activate Reverse Halide Segregation

The reversal of halide ions is studied under various conditions. However, the underlying mechanism of heat-induced reversal remains unclear. This work finds that dynamic disorder-induced localization of self-trapped polarons and thermal disorder-induced strain (TDIS) can be co-acting drivers of reverse segregation. Localization of polarons results in an order of magnitude decrease in excess carrier density (polaron population), causing a reduced impact of the light-induced strain (LIS – responsible for segregation) on the perovskite framework. Meanwhile, exposing the lattice to TDIS exceeding the LIS can eliminate the photoexcitation-induced strain gradient, as thermal fluctuations of the lattice can mask the LIS strain. Under continuous 0.1 W cm -2 illumination (upon segregation), the strain disorder is estimated to be 0.14%, while at 80 °C under dark conditions, the strain is 0.23%. However, in situ heating of the segregated film to 80 °C under continuous illumination (upon reversal) increases the total strain disorder to 0.25%, where TDIS is likely to have a dominant contribution. Therefore, the contribution of entropy to the system's free energy is likely to dominate, respectively. Various temperature-dependent in situ measurements and simulations further support the results. These findings highlight the importance of strain homogenization for designing stable perovskites under real-world operating conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Postanaerobic Digestion Manure Fibers as a Renewable Source of Lignin-Derived Aromatic Compounds for Microbial Upgrading

Abstract Postanaerobic digestion manure fibers are an abundant solid residue that remains underutilized. The substantial lignocellulosic content of digested manure opens the possibility of using it as a renewable resource for producing valuable products. In this study, we performed compositional and nuclear magnetic resonance analyses to determine lignin content and aromatic composition of these fibers. Additionally, alkaline-based treatment and reductive catalytic fractionation were evaluated as two different processes to produce aromatic-rich streams. The liquor from the alkaline treatment was subsequently utilized for microbial upgrading to produce 2-pyrone-4,6-dicarboxylic acid (PDC). The results showed that lignin in manure fibers represents 30% of the biomass (dry weight basis), with a ∼26% abundance of β-ether-linked aromatics and ∼13% p-coumarate moieties, indicating that the amount of lignin in the postanaerobic biomass is comparable to a moderately pretreated plant biomass. The alkaline treatment released 5.6 g aromatics/kg fibers, while reductive catalytic fractionation produced 14.0 g aromatics/kg fibers. A bioreactor operated in fed-batch mode produced a yield of ∼1 mol of PDC/mol measured aromatics at a rate of 0.2 g PDC/L·h and a titer of 2.6 g PDC/L. This study demonstrates how postanaerobic digestion manure fibers could be used in a circular bioeconomy by harnessing their lignocellulosic content to extract aromatic compounds and use them for obtaining valuable chemicals via microbial upgrading.

Riascos, Brayan D. [University of Wisconsin-Madiso↗
NASA NTRS2025

Airports as Energy Nodes Activity Summary

Advanced aircraft concepts that use non-traditional aviation energy storage methods such as batteries or cryogenic hydrogen are in development and expected to enter regular service at airports worldwide within the next decade. The energy needs for these aircraft may quickly overwhelm the existing energy infrastructure at airports, particularly at smaller and more remote facilities. Without energy upgrades, these airports will not be able to host these advanced vehicles, but without the advanced vehicle traffic, these airports will not have the rationale or funding to build up their energy infrastructure. The Airports as Energy Nodes (ÆNodes) activity, a collaboration between the National Aeronautics and Space Administration (NASA) and the National Renewable Energy Laboratory (NREL), was executed to understand and model the energy needs that advanced aircraft concepts may levy on these smaller airports, determine cost-effective approaches to enhance the airport energy infrastructure, and demonstrate the enhanced resilience of these energy infrastructure upgrades to the airport and surrounding community via “digital twin” simulation at relevant energy and dynamic time scales. The ÆNodes team also investigated future reference aircraft designs and materials to enable cryogenic hydrogen storage for aircraft. The ÆNodes team conducted analysis at two U.S. airport partner sites — Winchester Regional Airport in Winchester, Virginia, and Tweed/New Haven Airport in New Haven, Connecticut. The goal of this partnership was to develop data and reference infrastructure designs that could accommodate advanced aircraft in the future at these airports while also enhancing the resiliency of the energy supply to the surrounding airport community, which could be used to capture funding to enable the infrastructure upgrades. Over the course of the study, a method was developed to estimate air traffic requiring advanced energy services over the course of a year using a mix of historical data and companion studies on advanced aircraft transportation networks. The study has concluded at NASA but continues at NREL, who will develop a final report discussing the energy infrastructure upgrades and digital twin results. Preliminary results indicate that unrestricted adoption of advanced battery-electric aircraft may double traffic at these airports and increase peak daily power usage by an order of magnitude, while increase electricity energy needs by a factor of two to four. The infrastructure upgrades necessary to accommodate these increased energy needs could be used to provide enhanced energy services to the airport community to offset the cost and increase the utility of the upgrades, which will be described in the NREL final report.

Airports↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

International Commission on Radiological Protectio↗
DOE OSTI2026

Elimination of detrimental grain boundary segregation in garnets

Garnet Li 7 La 3 Zr 2 O 12 electrolyte is considered a key enabler of solid-state batteries with Li metal electrodes, but the grain boundaries impair its performance. To date, the understanding of grain boundary structures and its impact on performance remains elusive. Here, we show that element segregation at Li 7 La 3 Zr 2 O 12 grain boundaries critically governs Li transport and nucleation. During conventional sintering, Al, Ta, and La segregate at grain boundaries, locally depleting Li and creating space-charge layers that lower total ionic conductivity. Simultaneously, this segregation leads to higher electronic conductivity along grain boundaries, which promotes Li nucleation at grain boundary edges with increased risk of dendrite formation. The underlying mechanism of segregation is governed by both thermodynamic driving forces and diffusion kinetics. Building on this understanding, we develop a strategy to achieve segregation-free grain boundaries through a rapid sintering protocol that utilizes the onset of solid-state softening. This approach yields transparent, polycrystalline Li 7 La 3 Zr 2 O 12 with negligible grain boundary impedance and enhanced dendrite tolerance. By elucidating the structural origins and electrochemical consequences of grain boundary segregation, this work provides a guidance for the rational optimization of solid electrolytes.

Energy - Storage↗
DOE OSTI2026

Radiative divertor detachment and impurity transport with nitrogen and neon seeding in KSTAR H-mode plasmas

Achieving core-edge compatible divertor detachment is a critical requirement for stable operation in future fusion devices. This study compares nitrogen and neon seeding in KSTAR H-mode plasmas with carbon walls, combining experiments and SOLPS-ITER modelling to evaluate their radiative dissipation and core-edge compatibility. Experimentally, N seeding achieved stronger divertor detachment, with larger reductions in target particle and heat fluxes, a higher divertor radiation fraction, and a lower core radiation fraction than Ne. In contrast, Ne seeding triggered a significant rise in core radiation followed by H–L back transitions, limiting the maximum total radiated power fraction to roughly half that of N. SOLPS-ITER simulations reproduced the experimental trends and revealed that the better core-edge compatibility of N arises from its higher divertor retention in addition to its higher cooling factor. The relative positions of the stagnation points of impurity poloidal velocity and ionization sources did not explain the different divertor compression. Instead, in the present modelling, the higher impurity parallel particle flux, resulting from the higher parallel impurity velocity, explains the stronger nitrogen impurity compression in the divertor region. The parallel temperature distribution with N was more favourable for achieving higher impurity parallel velocity than with Ne, because the impurity velocity is governed by modifications of the main ion flow due to friction and thermal forces, both of which strongly depend on the temperature. Ultimately, this behaviour is attributed to the strongly divertor-localized radiation of N. These results demonstrate that N is more effective than Ne in achieving radiative divertor detachment while maintaining low core contamination in KSTAR, consistent with observations in other present tokamaks.

KSTAR↗
DOE OSTI2026

DESI Strong Lens Foundry. III. Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using residual neural networks and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between z s = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with nondetections by NIRES were observed for a considerably shorter 600 s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology.

Agarwal, Shrihan [University of Chicago, IL (Unite↗
DOE OSTI2025

Rethinking 𝛼−RuCl 3 : Parameters, models, and phase diagram

RuCl 3 was likely the first ever deliberately synthesized ruthenium compound, following the discovery of the 44 Ru element in 1844. For a long time it was known as an oxidation catalyst, with its physical properties being discrepant and confusing, until a decade ago when its allotropic form 𝛼−RuCl 3 rose to exceptional prominence. This “rediscovery” of 𝛼−RuCl 3 has not only reshaped the hunt for a material manifestation of the Kitaev spin liquid, but it has opened the floodgates of theoretical and experimental research in the many unusual phases and excitations that the anisotropic-exchange magnets as a class of compounds have to offer. Given its importance for the field of Kitaev materials, it is astonishing that the low-energy spin model that describes this compound and its possible proximity to the much-desired spin-liquid state is still a subject of significant debate ten years later. In the present study, we argue that the existing key phenomenological observations put strong natural constraints on the effective microscopic spin model of 𝛼−RuCl 3 , and specifically on its spin-orbit-induced anisotropic-exchange parameters that are responsible for the nontrivial physical properties of this material. These constraints allow one to focus on the relevant region of the multidimensional phase diagram of the 𝛼−RuCl 3 model, suggest an intuitive description of it via a different parametrization of the exchange matrix, offer a unifying view on the earlier assessments of its parameters, and bring closer together several approaches to the derivation of anisotropic-exchange models. We explore extended phase diagrams relevant to the 𝛼−RuCl 3 parameter space using quasiclassical, Luttinger-Tisza, exact diagonalization, and density-matrix renormalization-group methods, demonstrating a remarkably close quantitative accord between them on the general structure and hierarchy of the phases, with the zigzag, ferromagnetic, and incommensurate phases that are proximate to each other. As a result, one of the highlights is the detailed agreement on the nature of the incommensurate phases that realize two distinct counterrotating helical states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Impact of anion-exchange membrane degradation on long-term CO 2 electrolysis to ethylene

Electrochemical CO 2 reduction (eCO2R) to ethylene offers a unique opportunity to diversify domestic supply chains for chemical manufacturing. Large-scale deployment of eCO2R to ethylene reactors is currently limited by low energy efficiencies and poor durability. Herein, we demonstrate >100 h of continuous electrolysis at an industrially relevant current density of 200 mA cm −2 in a 25 cm 2 geometric area zero-gap reactor with a full-cell voltage <3.1 V and ethylene Faradaic efficiency >30%. Incorporating expanded polytetrafluoroethylene (PTFE)-supported electrodes into zero-gap reactors allows for durable electrode catalysts that are resistant to flooding, and this enables wider ranges of operating parameters not typically accessible in CO 2 electrolysis. Finally, we identify membrane degradation, evidenced by a loss of membrane ion-exchange capacity, as the leading cause of performance loss over 144 h of electrolysis.

Energy - Conversion↗
NASA NTRS2026

A Summary of Test and Analysis Results from a Second Lift+Cruise Full-Scale Drop Test

The realization of advanced air mobility markets is enabling new forms of transportation to take shape in the United States and around the world. Though currently in development, as these markets mature, new types of vertical take-off and landing (VTOL) vehicles have been undergoing development for use. There are many factors which must be addressed prior to these types of vehicles becoming viable alternative forms of transportation in these markets. These factors include incorporation into the existing airspaces, the logistics of operating in urban environments, along with numerous factors associated with safety and reliability. To address some of the safety aspects associated with the development of these new types of vehicles, NASA has been conducting research into the performance of an example electric VTOL (eVTOL) aircraft as a part of the Revolutionary Vertical Lift Technology (RVLT) project. Over the course of this research, many aspects including the development of energy absorbing components, the evaluation of seating systems, the development of advanced finite element material model systems and the acquisition of full-scale vehicle impact data were investigated. The report will discuss aspects related to the acquisition of full-scale vehicle data which occurred in the form of a full-scale impact test conducted in the Summer of 2025. This test was on a NASA designed Lift+Cruise composite cabin test article and represented a partial capstone in the entirety of previous eVTOL research conducted for the project. In this test, a variety of experiments were included in order to investigate the effect of a full-scale environment on the experiment results. In parallel, the development of a computational impact model to simulate the full-scale test will be discussed in this report. A model of the Lift+Cruise test article was developed utilizing data collected from previous sub- and full-scale test data and then simulated in the current test environment. The model development, its use in pre-test predictions, and its use in post-test correlation will all be presented. This report will present the test data acquired from the Lift+Cruise test and document several of the results obtained. One intended result is to determine the effect of a complex full-scale crash impact on the identification of occupant injury risk within seat and vehicle designs. A second intended result is to determine whether high-fidelity models can be used with some confidence in the prediction of test events and can allow for additional test cases to be simulated without the need of having to conduct additional tests. The overall goal of the test is to provide the community with data that can be used for design, development or certification efforts, along with providing data on what an example eVTOL crash incident could entail.

energy storage systems↗
NASA NTRSDate not supplied

In-Situ Scanning Electron Microscope Experiments for Microscale Mechanical Testing and Validated Modeling of Fiber Reinforced Thermoplastics

A novel, in-situ, scanning electron microscope (SEM) mechanical testing capability for materials at the microscale which provides experimental validation to a machine learning (ML) toolset for full-field validation of physics-based micromechanics models is being developed by researchers at NASA Glenn Research Center. These are enabling technologies for the integration of multiscale digital twins for materials into system level models which will result in the improved performance, material discovery, reduced production cost and time, rapid characterization, and prognostic structural health monitoring (SHM) for materials and structures for extreme environments in support of NASA space exploration missions. In order to bridge the material structure-to-system gap for digital twins, physics-based models must be experimentally validated at multiple length scales. Seminal microscale experiments, conducted at the Air Force Research Laboratory (AFRL), were limited to transverse compression of single-layer, unidirectional thermoset polymer matrix composite (PMC) micropillar specimens [1]. The early phases of the current project followed those initial results and setup to reproduce the compression testing of PMC material on the custom-built piezoelectric actuated micromechanical testing rig built by MicroTesting Solutions LLC. In this work, samples of thermoplastic PMC material were first machined into 3 mm cubes, and then further machining and final milling was done using a Focused Ion Beam (FIB). The initial experiment was done on a pillar roughly 20 µm x 20 µm x 40 µm tall. Additional pillars were milled with final sizes ranging from 20 µm x 20 µm x 40 µm tall to 40 µm x 40 µm x 65 µm tall. A speckle pattern for in-situ full-field measurements using Digital Image Correlation (DIC) was applied with platinum, which was coated on the surface, and then the FIB was used to mill away some of the coating to produce an irregular pattern of Pt on the pillar surface. The samples were loaded into the custom testing rig and placed into the SEM and loaded under compression until failure. Images were collected in the SEM during testing. Post-processing of the images was conducted using DIC to obtain full-field displacement and strain measurements elucidating the role of the matrix as well as fiber-fiber interaction at the microscale within the composite subjected to compression loading well into the non-linear regime of the material. Moreover, the evolution of fiber-matrix debonding and matrix cracking is observed in-situ at the microscale. This data, along with images segmented with a newly developed ML toolset [2], was used to create and validate physics-based micromechanics models. An image of the failed micropillar is shown in Figure 1. The techniques developed in the initial compression experiment was tailored to the validation needs of the models and expanded to include different sized samples as well as possibly tension and fatigue.

Laura Wilson↗
DOE OSTI2024

Three-dimensional dispersion in the type-II Dirac semimetals PtTe 2 and PdTe 2 revealed through circular dichroism in angle-resolved photoemission spectroscopy

PtTe 2 and PdTe 2 are among the first transition metal dichalcogenides that were predicted to host type-II Dirac fermions, exotic particles prohibited in free space. These materials are layered and air stable, which makes them top candidates for technological applications that take advantage of their anisotropic magnetotransport properties. Here, in this work, we provide a detailed characterization of the electronic structure of PtTe 2 and PdTe 2 using angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations, offering an alternative interpretation for one of the Dirac-like dispersions in these materials. Through the use of circularly polarized light, we report a different behavior of such dispersion in PdTe 2 compared to PtTe 2 , that we relate to a symmetry analysis of the dipole matrix element. Such analysis reveals a link between the observed circular dichroism and the different momentum-dependent terms in the dispersion of these two compounds, despite their close similarity in crystal structure. Additionally, our data show a clear difference in the circular dichroic signal for the type-II Dirac cones characteristic of these materials, compared to their topologically protected surface states. Our paper provides a useful reference for the ARPES characterization of other transition metal dichalcogenides with topological properties and illustrates the use of circular dichroism as a guide to identify the topological character and attributes of two otherwise equivalent band dispersions.

angle-resolved photoemission spectroscopy↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗