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

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At least 487 records · Page 27

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar↗

Integrating and Characterizing HPC Task Runtime Systems for hybrid AI-HPC workloads

Scientific workflows increasingly involve both HPC and machine-learning tasks, combining MPI-based simulations, training, and inference in a single execution. Launchers such as Slurm’s srun constrain concurrency and throughput, making them unsuitable for dynamic and heterogeneous workloads. We present a performance study of RADICAL-Pilot (RP) integrated with Flux and Dragon, two complementary runtime systems that enable hierarchical resource management and high-throughput function execution. Using synthetic and production-scale workloads on Frontier, we characterize the task execution properties of RP across runtime configurations. RP+Flux sustains up to 930 tasks/s, and RP+Flux+Dragon exceeds 1,500 tasks/s with over 99.6% utilization. In contrast, srun peaks at 152 tasks/s and degrades with scale, with utilization below 50%. For IMPECCABLE.v2 drug discovery campaign, RP+Flux reduces makespan by 30–60% relative to srun/Slurm and increases throughput more than four times on up to 1,024. These results demonstrate hybrid runtime integration in RP as a scalable approach for hybrid AI-HPC workloads.

HPC-AI↗

Remotely Controlled Mixers for Light Microscopy Module (LMM) Colloid Samples

Developed by NASA Glenn Research Center, the LMM aboard the International Space Station (ISS) is enabling multiple biomedical science experiments. Techshot, Inc., has developed a series of colloid specialty cell systems (C-SPECS) for use in the colloid science experiment module on the LMM. These low-volume mixing devices will enable uniform particle density and remotely controlled repetition of LMM colloid experiments. By automating the experiment process, C-SPECS allow colloid samples to be processed more quickly. In addition, C-SPECS will minimize the time the crew will need to spend on colloid experiments as well as eliminate the need for multiple and costly colloid samples, which are expended after a single examination. This high-throughput capability will lead to more efficient and productive use of the LMM. As commercial launch vehicles begin routine visits to the ISS, C-SPECS could become a significant means to process larger quantities of high-value materials for commercial customers.

Kurk, Michael A. (Andy)↗

A Flat Analyzer Polycapillary Spectrometer for X-ray Absorption Spectroscopy of Dilute Transition Metals at X-ray-Free Electron Lasers

X-ray absorption spectroscopy (XAS) coupled with highly intense pulses from an X-ray-free electron laser (XFEL) can be used to track ultrafast chemical dynamics. Nonetheless, measurements for dilute samples (≤1 mM) have been exceptionally challenging, as scattering background signals dominate over the sample’s X-ray fluorescence. We show that femtosecond time-resolved XAS measurements of sub-millimolar transition metal solutions are now possible at the Linac Coherent Light Source (LCLS) using a high-throughput polycapillary XAS spectrometer, designed, developed, and commissioned at LCLS and the Stanford Synchrotron Radiation Lightsource (SSRL). The instrument integrates three polycapillary optics that collect and collimate X-ray fluorescence emitted from the interaction point with a high solid angle. X-ray collimated fluorescence is then selectively diffracted by coupled graphite analyzer crystals. As a result, the contribution of scattered photons is suppressed. Experiments at the Pt L 3 -edge on 0.1 mM aqueous K 2 PtCl 6 (delivered via a 100 μm liquid jet) were successfully performed in the laser pump X-ray probe configuration at the LCLS XCS and XPP instruments. We report the transient spectra of hexachloroplatinate within the first 10 ps after a 266 nm photoexcitation. We observed a short-lived reduced intermediate (≈2 ps). The polycapillary X-ray spectrometer at LCLS now enables the efficient study of the dynamics of ultradilute transition metals in solution. This capability opens the door to investigating plasmonic systems, photocatalysts, enzymes, and other scarce and dilute samples.

LCLS↗

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗

Lunar UV-visible-IR mapping interferometric spectrometer

Ultraviolet-visible-infrared mapping digital array scanned interferometers for lunar compositional surveys was developed. The research has defined a no-moving-parts, low-weight and low-power, high-throughput, and electronically adaptable digital array scanned interferometer that achieves measurement objectives encompassing and improving upon all the requirements defined by the LEXSWIG for lunar mineralogical investigation. In addition, LUMIS provides a new, important, ultraviolet spectral mapping, high-spatial-resolution line scan camera, and multispectral camera capabilities. An instrument configuration optimized for spectral mapping and imaging of the lunar surface and provide spectral results in support of the instrument design are described.

Smith, W. Hayden↗

Variability in Galactic Cosmic Radiation- Induced DNA Damage Response in Inbred Mice Is Modulated by Genetics

In radiation biology, the ability to predict cancer risk associated with exposure to low doses of high-LET (Linear Energy Transfer) ionizing radiation remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual sensitivity. We have hypothesized that DNA repair capacity is the primary factor differentiating peoples radiation sensitivity. We previously showed in immortalized human cell lines that characterizing the dose and time dependence of p53-binding protein 1 (53BP1) foci formation in the nucleus following X-rays exposure is sufficient to predict DNA repair response to any other LET in the same cell line. We now tested this hypothesis across a population of mice with different genetic background. Fibroblast cells were extracted and cultivated from 76 individual mice from 15 different strains and exposed to HZE (high (H) atomic number (Z) and energy (E) galactic cosmic ray particles) particles and X-rays. Individual radiation sensitivities were investigated by high throughput measurement of DNA repair kinetics that evaluated 53bp1 foci numbers as a surrogate for DNA double-strand breaks at various times post-irradiation. Instead of just counting foci which can be hard to distinguish for high-LET or high doses, we also took into account the track structure of high-LET particles to compute the remaining number of unrepaired tracks as a function of time post-irradiation. As expected, the percentage of unrepaired track over a 48 hours follow-up period increased with LET. In addition, repair rate was modulated by genetics, with animals from the same strain showing small variance while large rate differences were observed between strains. Radiation strain sensitivity ranking was estimated based on repair rates from exposure to each LET evaluated in this work, and ranking for high-LET correlated better with ranking from high dose of X-ray, not low dose. At the in-vivo level, drops in T-cells and B-cells number measured 24 hours after 0.1 Gy (Gray) X-ray exposure, correlated with slower DNA repair kinetic in fibroblast cells of the same strains of mice. At the genomic level, mouse genome wide association (GWA) analysis identified seven significant genetic loci on chromosomes 2, 3, 7, 10, 11, 13 and 19 with different significance depending on the LET. Interestingly, for the two highest LET, a common locus on Chromosome 10 was identified with high enrichment for DNA repair associated genes.Overall, this work suggests that repair kinetics of primary skin fibroblasts is a good surrogate marker for in-vivo radiation sensitivities in other tissues and that this response is modulated by genetics. Our study also confirms that DNA repair kinetics following high doses of X-ray can be used to predict radiation sensitivity to high-LET.

High-LET Radiation↗

Neurovascular effects of simulated space radiation

A major health risk for human deep space exploration is central nervous system (CNS) damage by ionizing radiation. Simulated galactic cosmic rays or their components, especially high-linear energy transfer particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. Astrocytes are major cellular regulators of BBB permeability and also modulate neuroinflammation and neurodegeneration. However, BBB and astrocyte functions in regulating CNS responses to space radiation remain little investigated, especially in human organ analogs. Therefore, we developed and utilized a high-throughput 3D human neurovascular organ-on-a-chip model, seeded with induced pluripotent stem cell-derived cells. The effects of time course, ionizing radiation dose and dose rate were mapped by exposing the model to either acute, high dose rate radiation with simulated galactic cosmic rays or 600 MeV/n 56Fe particles, or protracted, low dose rate gamma radiation using a 57Co sealed source setup. We investigated BBB permeability, oxidative stress, cellular damage and secreted factors over the time period between 24 hours – 2 weeks after 0.1 – 0.8 Gy irradiation. We observed that ionizing radiation exposure increased BBB permeability, caused oxidative stress, damaged endothelial cells and altered expression of inflammatory cytokines with a subset of outcomes dependent on ionizing radiation dose rate. Furthermore, our results indicated that astrocyte functions were primarily deleterious at early time points and protective later after irradiation, resembling CNS responses to injury in vivo. Our findings in organ models were complemented by studies on true spaceflight using mouse spatial and single cell multi-omics, which similarly indicated spaceflight-mediated changes in astrocyte functions. In summary, our study evaluates the regulation of neurovascular responses to simulated space radiation, suggesting astrocytes as targets for countermeasures to mitigate CNS damage in deep space exploration.

Radiation↗

Potential for improved silicon ribbon growth through thermal environment control

The Ribbon-to-Ribbon (RTR) process for growth of silicon ribbon is described. This process involves the fabrication of a microcrystalline ribbon of silicon and subsequent grain size enhancement through a laser recrystallization process. The microribbon is obtained from a Thermal Expansion Shear Separation (TESS) process which allows a CVD layer of silicon to be separated from a temporary molybdenum substrate. Efforts to achieve increased solar cell efficiencies and higher area production rates have been problematical. Furnaces, which are necessary for thermal stress control, have been shown to contribute contamination to substrates resulting in degraded efficiencies. Recent results with a new furnace design indicate efficiencies in excess of 9% will be routine. Limitations to area throughput arise due to fundamental linear velocity limitations and width limitations necessary to prevent the occurrence of thermal buckling. Calculations are reported which show the influence of thermal profile on buckling tendencies, and a proposed electron beam technique is considered which promises high throughput with minimal buckling.

Gurtler, R. W.↗

GeneLab for High Schools – Bioinformatic Training For Students And Educators

Modern biological sciences are increasingly based on high-throughput molecular techniques, including genomics, transcriptomics, and proteomics. NASA’s GeneLab program has collected extensive data from ‘omics’ studies, curated them into an accessible platform and provided data analysis/visualization tools to facilitate the generation of new hypotheses and research directions. GeneLab for High Schools (GL4HS), launched in 2017, has endeavored to utilize this database and provide tools for students to understand and analyze omics datasets whilst also learning about spaceflight research. The GL4HS program ran in person at Ames from 2017-2019 and has run virtually since 2020. Each year fifteen high school students are trained to analyze and interpret GeneLab transcriptomic data. Additionally, in the last several years we have expanded our “teacher training program” to include 10 teachers total in an effort to enable this program to be utilized in classrooms across the USA. Teachers also join the NASA GeneLab Education Working Group (EWG) enabling support as they implement custom GL4HS modules into their classrooms. The GL4HS program consists of three main components – (1) core learning modules, (2) networking and teamwork, and (3) an independent learning project. Students are also taught critical networking and science communication skills facilitating their ability to ‘sell their science’ in innovative and creative ways. This program has enabled students to learn about biology in space and to have a glimpse into the world of research for the first time. Many of the students in this program shared that the course was transformative to their perception about biological sciences and how it linked to other areas of STEM. The ultimate and long-term goal of GL4HS is to expand the program to multiple locations thereby facilitating the reach of NASA Space Biology beyond NASA-centric regions.

GeneLab↗

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗

High entropy oxides prediction and discovery by the Mixed Enthalpy-Entropy Descriptor

The vast, high-dimensional composition space of high-entropy oxides (HEOs) offers exceptional opportunities for functional materials discovery, yet it also poses a fundamental challenge: the rational and efficient prediction of stable, synthesizable compositions and the corresponding structure–property relationships. Despite growing interest, the field still lacks broadly applicable, physically grounded descriptors capable of navigating various large chemical spaces. Here, we introduce a Mixed Enthalpy–Entropy Descriptor (MEED) that enables rapid, first-principles–based prediction of HEOs synthesizability across diverse chemistries. Using MEED, we perform high-throughput screening of two distinct HEO families: rocksalt oxides and perovskite oxides. The predicted top candidates in each family were experimentally validated. MEED reveals unifying thermodynamic and structural principles governing stability across both chemical compositions and polymorphs, providing mechanistic insight into the formation of high-entropy phases. This work significantly broadens the accessible chemical design space for HEOs and establishes a data-efficient framework for accelerating the discovery of next-generation functional materials.

Yu, Liping [University of Central Florida]↗

Fabricating Silver Nanowire–IZO Composite Transparent Conducting Electrodes at Roll-to-Roll Speed for Perovskite Solar Cells

This study addresses the challenges of efficient, large-scale production of flexible transparent conducting electrodes (TCEs). We fabricate TCEs on polyethylene terephthalate (PET) substrates using a high-speed roll-to-roll (R2R) compatible method that combines gravure printing and photonic curing. The hybrid TCEs consist of Ag metal bus lines (Ag MBLs) coated with silver nanowires (AgNWs) and indium zinc oxide (IZO) layers. All materials are solutions deposited at speeds exceeding 10 m/min using gravure printing. We conduct a systematic study to optimize coating parameters and tune solvent composition to achieve a uniform AgNW network. The entire stack undergoes photonic curing, a low-energy annealing method that can be completed at high speeds and will not damage the plastic substrates. The resulting hybrid TCEs exhibit a transmittance of 92% averaged from 400 nm to 1100 nm and a sheet resistance of 11 Ω/sq. Mechanical durability is tested by bending the hybrid TCEs to a strain of 1% for 2000 cycles. The results show a minimal increase (<5%) in resistance. The high-throughput potential is established by showing that each hybrid TCE fabrication step can be completed at 30 m/min. We further fabricate methylammonium lead iodide solar cells to demonstrate the practical use of these TCEs, achieving an average power conversion efficiency (PCE) of 13%. The high-performance hybrid TCEs produced using R2R-compatible processes show potential as a viable choice for replacing vacuum-deposited indium tin oxide films on PET.

14 SOLAR ENERGY↗

Space Biotech: Hindsight, Insight, Foresight

Over the past forty years, microgravity has inspired and enabled applications in a wide range of sectors including medicine, materials, computers, communications, and national defense. Trends show that demand for high-tech solutions is increasing in these sectors, solutions that require higher resolution, greater precision, novel materials, innovative processes, and more sophisticated tools. These are areas where microgravity can offer unique capabilities for innovation. The Emerging Space Office (ESO) has engaged in multiple studies over the past year that have found that microgravity RD is one of the most promising technology areas for contributing to economic growth and to NASAs mission. The focus of these studies was on terrestrial markets rather than NASA applications, applied research rather than basic research, and commercial rather than academic investigators. There have been more success stories than are generally appreciated and there are significant areas of promising future potential. Many of the problems that have limited commercial microgravity development in the past are being solved. Microgravity research and development (RD) requires iteration and learning, as rapidly as possible. New technologies enable high throughput and rapid data collection in increasingly small payloads. The International Space Station is in orbit and provides a laboratory that is available 247 at least until 2024. Frequent flights by commercial space providers to and from the ISS now enable the fast learning cycles needed by high-tech industries. Launch costs are decreasing and the ability to return payloads to Earth is increasing. New commercial space laboratories, such as those being developed by SpaceX and Bigelow Aerospace, are in the final stages of development and testing. This ecosystem for microgravity RD has never been available before. These are game-changer conditions for attracting high-tech industries to space for terrestrial, as well as NASA, applications. However, few know that these capabilities are available or how to use them. In aggregate, the potential value for new applications from microgravity RD over the next ten years could add billions of dollars per year in terrestrial applications to the future economy, create new jobs, and generate a wide range of public benefits in medical advances, while broadening the customer base for the emerging space industry.

biotech↗

Modular, Fast, Two-Dimensional Cyclic Convolver

Proposed high-throughput, real-time synthetic-aperture-radar (SAR) processor built using new, modular, two-dimensional cyclic convolver architecture based on polynomial factorization and designed for very-large-scale integrated (VLSI) circuitry. New architecture reduces cost, size, and power dissipation of SAR processor in comparison to high-speed array-processor approach. Processor also used for other image-and data-processing applications involving two-dimensional Fourier transforms.

Liu, K. Y.↗

Predicting the High-Temperature Oxidation Response of Nickel Superalloys Using CALPHAD-Enhanced Machine Learning

Structural materials such as Ni-based superalloys used in high-temperature power cycles are routinely exposed to toxic environments including high temperature and pressure, aqueous and gas corrosion, etc. Here, we present a physics-informed machine learning approach to predict the oxidation response of diverse Ni-superalloys. First, a high-fidelity experimental dataset is curated from typical oxidation mass-change experiments in air, covering 25+ elements and different physical behavior such as parabolic growth, non-parabolic growth, and oxide spallation. Second, the dataset is featurized using thermophysical, chemical, and mechanical properties obtained from high-throughput CALPHAD calculations. Third, several machine learning models are developed to identify key features related to mass-change characteristics and model the mass-change curve for various alloys. Finally, the model is deployed to rapidly screen over a new composition space and down-select candidate alloys with high oxidation resistance for experimental validation.

CALPHAD↗

3D nanolithography with metalens arrays and spatially adaptive illumination

The growing demand for advanced materials, miniaturized devices and integrated microsystems calls for the reliable fabrication of complex, multiscale, three-dimensional (3D) architectures, a need increasingly addressed through light-based and laser-based processes. However, owing to the field-of-view (FOV) limitations of conventional imaging optics, existing 3D laser nanofabrication techniques face fundamental challenges in throughput, proximity error and stitching defects on the path to scaling. Here, in this study, we present a scalable 3D nanofabrication platform that uses a metalens-generated focal spot array to parallelize two-photon lithography (TPL) beyond centimetre-scale write field areas. Metalenses are ideally suited for producing submicron-scale focal spots for high-throughput nanolithography, as they uniquely feature large numerical apertures (NAs), immersion media compatibility and large-scale manufacturability. We experimentally demonstrate a printing system that uses a 12-cm 2 metalens array to produce more than 120,000 cooperative focal spots, corresponding to a throughput exceeding 10 8 voxels s −1 . By programmatically patterning the focal spot array using a spatial light modulator (SLM), an adaptive parallel printing strategy is developed for precise greyscale linewidth modulation and choreographed printing of semiperiodic and fully aperiodic 3D geometries. We demonstrate parallel printing of replicated microstructures (>50 M microparticles per day), centimetre-scale 3D architectures with feature sizes down to 113 nm, and photonic and mechanical metamaterials. This work demonstrates the potential of 3D nanolithography towards wafer-scale production, showing how TPL could be used at scale for applications in microelectronics, biomedicine, quantum technology and high-energy laser targets.

Materials science↗

An accelerated framework for predicting creep rupture lifetimes in engineering alloys

Confidently predicting high-temperature deformation, including creep and creep rupture, is paramount for the design and commercialization of candidate materials for advanced nuclear energy systems. To accelerate creep quantification, we introduce a framework that enables rapid, cost-effective, and reliable prediction of creep rupture lifetimes, minimizing reliance on time-intensive bulk creep testing. Unlike conventional creep analysis, which requires extensive time and resources, our method leverages a maximum of four short-term bulk creep tests as training data for prediction. This framework combines high-throughput nanoindentation up to 700 °C with these targeted bulk tests to inform our creep rupture model in order to predict rupture lifetimes. The strong agreement between our predictions and conventional experimental data demonstrates the effectiveness of our approach for accelerated creep analysis and lifetime prediction of structural components in high-temperature applications. Our multi-pronged approach motivates further integration of computational tools and advanced instrumentation to establish a universal framework for understanding high-temperature material responses.

36 MATERIALS SCIENCE↗