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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
DOE OSTI2026

Demonstration and analysis of volumetric additive manufacturing via sub-orbital spaceflight testing

Computed Axial Lithography (CAL) represents a significant advancement in the emerging field of Volumetric Additive Manufacturing (VAM). CAL addresses key limitations of traditional photopolymer additive manufacturing technologies, by eliminating the need for layering and support structures. Unlike conventional methods, CAL prints components by illuminating all points within a desired geometry simultaneously, using tomographic reconstruction to form the object in a single step. This unique approach eliminates the relative motion between the object and the precursor material, enabling faster printing speeds and reducing the waste associated with support structures. However, CAL parts require post-processing steps before they can be utilized. CAL's core attributes make it particularly suited for In-Space Manufacturing (ISM), due to its fast fabrication times, wide breadth of materials it can use, and minimized footprint. CAL has been successfully demonstrated in microgravity during parabolic flight experiments. However to fully validate and understand CAL's behaviour in microgravity, all manufacturing and post-processing steps must be integrated. In June 2024, we conducted SpaceCAL Mission 3, testing this entire workflow on a suborbital flight aboard Virgin Galactic's SpaceShipTwo. During ~140 s of microgravity, the system autonomously manufactured and post-processed four parts using PEGDA700 resin. Post-flight analysis showed that 2/4 parts were recognisable, while others were distorted due to bubble formation from residual water droplets, off-axis optical aberrations, and non-uniform solvent rinsing. Despite these limitations, this study represents the first integrated CAL workflow in space, providing an initial experimental demonstration and analysis for closed-loop in-space manufacturing.

Waddell, Taylor [Department of Mechanical Engineer↗
DOE OSTI2022

Emerging Role of Exosomal Long Non-coding RNAs in Spaceflight-Associated Risks in Astronauts

During spaceflight, astronauts are exposed to multiple unique environmental factors, particularly microgravity and ionizing radiation, that can cause a range of harmful health consequences. Over the past decades, increasing evidence demonstrates that the space environment can induce changes in gene expression and RNA processing. Long non-coding RNA (lncRNA) represent an emerging area of focus in molecular biology as they modulate chromatin structure and function, the transcription of neighboring genes, and affect RNA splicing, stability, and translation. They have been implicated in cancer development and associated with diverse cardiovascular conditions and associated risk factors. However, their role on astronauts’ health after spaceflight remains poorly understood. In this perspective article, we provide new insights into the potential role of exosomal lncRNA after spaceflight. We analyzed the transcriptional profile of exosomes isolated from peripheral blood plasma of three astronauts who flew on various Shuttle missions between 1998–2001 by RNA-sequencing. Computational analysis of the transcriptome of these exosomes identified 27 differentially expressed lncRNAs with a Log 2 fold change, with molecular, cellular, and clinical implications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Radioisotope Power System Dose Estimation Tool (RPS-DET) User Manual

Radioisotope power systems (RPSs) convert decay heat from radioactive materials to electrical power. The National Aeronautics and Space Administration (NASA) uses RPSs for certain orbiters, landers, rovers, and probes that cannot rely on solar or chemical power. Most of the emitted charged particles in RPS fuels are locally absorbed, and the particles’ kinetic energy is converted into thermal energy as they slow down in the surrounding materials. This heat is subsequently converted into electricity through some form of energy conversion process (e.g., thermoelectric, heat engine, thermionic). While nearly all the charged particles are stopped locally, a non-trivial portion of the emitted neutral particles (neutrons and photons) escape the fuel and are free to interact with surrounding materials. This escaping radiation field can be operationally problematic for certain instruments, materials, electronics, etc., and can cause problems during terrestrial shipping, integration, testing for personnel, instrumentation, etc. Furthermore, the fuel’s emission spectrum evolves over time as the parent isotopes decay away and daughter products accumulate. This changing fuel composition alters characteristics of the ambient radiation field over time, which is further affected by RPS orientation and the surrounding environment. Tools that can rapidly estimate the radiation characteristics of RPSs with various fuel compositions, fuel ages, various RPS orientations, and in/on different spaceflight and planetary scenarios provide researchers with an opportunity to quickly estimate the radiation implications of a given RPS scenario. The RPS dose estimation tool (RPS-DET) provides engineers, scientists and analysts who are not trained in the art of particle transport software with a solution for quickly building, simulating, and analyzing the radiation impacts of various RPS designs in relevant spaceflight and terrestrial environments.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Methods for Estimating Dose from Galactic Cosmic Rays and Jovian Radiation Belts on Reduced-Order Monte Carlo Geometries

This document outlines the methods and tools developed to estimate dose rates from galactic cosmic rays and the trapped radiation belts surrounding Jupiter using Monte Carlo particle transport software. Furthermore, the techniques described here are specific for translating high-resolution MAVRIC models to analogous but lower resolution Monte Carlo N-Particle Transport (MCNP) code models to estimate charged particle effects on models originally developed to study neutral particles only. This capability was initially developed to predict doses to various components of dynamic radioisotope power systems for spaceflight applications, but the tools and methods can be easily applied to other problem geometries and expanded to other space radiation environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Ionospheric Disturbances in GNSS TEC Data: SpaceX Falcon 9 Deorbit Maneuvers Over CONUS in April–May 2024

Traveling ionospheric disturbances (TIDs) driven by a large number of internal and external sources are detectable with dense networks of ground‐based Global Navigation Satellite System (GNSS) receivers' measurements of total electron content (TEC). We present the newly developed System for Rapid Analysis of Ionospheric Dynamics (S‐RAID), providing data and visual GNSS TEC products of TIDs of periods ~2–120 min and horizontal resolution up to tens of kilometers for years 2017–2024. The S‐RAID data reveal myriad natural and anthropogenic TIDs from meteorology and space weather, and from human spaceflight activities. In this report, we focus on new prominent disturbances found during SpaceX second stage deorbit maneuvers in April–May 2024. Signatures include waves emanating from the Falcon's trajectory above California and depletions following its deorbit and passage over Arizona. These findings suggest further opportunities to detect and quantify small‐scale events in the ionosphere as well as to understand the responses of the atmosphere‐ionosphere system to known inputs.

58 GEOSCIENCES↗
DOE OSTI2020

Magnetic Navigation for GPS-Denied Airborne Applications

Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗