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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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79 records · Page 5

Advancing Metasurfaces Towards New Frontiers: Nonvolatile Reconfigurable Optics

The applications of adaptive optics extend across multiple sectors, encompassing areas such as LiDAR, biological and chemical sensing, and free-space communications. In this study, we report on the design, fabrication, testing, and modeling of electrically reconfigurable metasurfaces using a low-loss high contrast phase change material, Ge2Sb2Se4Te integrated with an IR-transparent silicon microheater. Through this work, we introduce a reliable architecture for switching PCM-based metasurfaces within an integrated circuit configuration which is compatible with standard foundry fabrication processes. We demonstrate the capability of controlling the transmission of electromagnetic waves through the precise stimulation of PCM-based pixels, each spanning a few hundred microns, over numerous cycles. By leveraging PCM-based pixels, we unlock the potential to create metasurfaces encompassing a diverse range of functionalities such as dielectric filters, metalens, or beam steering devices, which is governed by the design of the meta-atoms. Further, we perform an in-depth investigation into the failure mechanism utilizing techniques such as Fourier transform IR spectroscopy (FTIR), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and thermal modeling. According to our results, due to a sharp temperature rise at the PCM/heater interface, we observe severe delamination of the PCM from the heater. More uniform PCM deposition, better adhesion at the PCM/heater interface, and a more uniform temperature distribution in the device could potentially mitigate the failure and lead to a longer life-time. By addressing these challenges, we aim to unlock the full potential of PCM-based devices and advance the field of adaptive optics.

Phase change material↗

Surface Hardness Testing of Mobile Launcher 1 (ML-1) Vehicle Support Posts (VSP) Following Artemis I Launch Exposure

Following the successful launch of Artemis I on November 16th, 2022 (Fig 1), a surface hardness assessment was performed on the eight primary VSPs (Figs. 2, 3) located on the Zero Deck of the ML. This assessment was performed as part of an instrument investigation for strain gauges installed on VSP interior surfaces that had a “strange reaction”. This report does not address the VSP strain gauge investigation, but rather VSP structural integrity for future service (Artemis II, III, …). Surface hardness measurements were taken to assess the strength of the ASTM A148 steel castings to confirm thermal exposure from launch had not reannealed the VSPs. However unlikely, it is possible high temperature may have heated and tempered (reannealed) the VSPs, resulting in a change of built-in stresses. This loss in built-in stress may explain the change in off-set measured by the strain gauges. Initial hardness measurements were made at two interior surfaces of VSPs near the strain gauges and the corresponding exterior surfaces (engine hole-facing). Field hardness measurements on the exterior, engine hole surface-facing surfaces for all eight VSPs ranged from 175 to 226 HB/P, well below the minimum hardness of 302 Brinell (HB). Opposing interior surface hardness measurements near strain gauges ranged from 264 to 358 HB/P. In all cases for flight VSPs, a drop in interior-to-exterior hardness ranging from 70 to 132 HB/P was measured. Surface hardness measurements were then made on the two spare VSPs not exposed to launch temperatures for baseline comparison. These two spare VSPs had a drop in Brinell hardness from interior to exterior surfaces ranging from 3 to 17 HB/P. The large interior-to-exterior delta hardness for eight flight VSPs but not for the two spare VSPs suggests launch exposure temperatures softened the exterior surfaces, raising two questions: 1) Are the VSPs compromised for future use, and 2) How deep is the exterior surface softening effect? To address concerns of low surface hardness values at non-critical exterior surfaces, additional field surface hardness measurements were taken at high-stress locations on VSP3: Both door jams, back radius, and internal left and right radius near the base. These values came in well above the required minimum hardness (317 to 365 HB/P). For a more representative pre-launch versus post-launch surface hardness comparison, VSP Acceptance Data Packages (ADPs) were reviewed, and hardness measurements were made at the same eight original locations on VSP3 where hardness measurements were made at the foundry. To determine the degree of softening, 1/8” of material was machined away at three exterior surfaces of engine hole-facing side (Fig. 4). A significant increase in surface hardness was measured ranging from 50 to 86 HB/P. Values at these three locations were still slightly below the required minimum hardness, so an additional 1/8” material was machined away, and hardness values were retaken. At the ¼” depth, hardness values increased to 321 to 324 HB/P. These values fall above the required minimum, concluding surface hardness testing. Rationale for VSP continued use was reached with no restrictions during a Chief Engineering Review based on hardness values exceeding minimum at critical locations and subsurface locations for VSP #3.

Artemis I↗

Progress Towards SiC ASICs for Extreme Temperature and Radiation Environments

This presentation describes development and demonstrations of semiconductor integrated circuits (ICs) and ceramic packaging that are arguably the most environmentally durable transistor electronics ever demonstrated. Silicon carbide (SiC) junction field effect transistor-resistor (JFET-R) ICs fabricated by NASA Glenn Research Center with two-level interconnect have successfully operated for over 1 year in 500 °C air-ambient, 60 days in 460 °C and 9.3 MPa pressure caustic Venus surface environment test chamber, and radiation exposure through 7 Mrad(Si) total ionizing dose (TID) and 86 MeV-cm2/mg heavy ion strikes. Furthermore, these ICs have also demonstrated operation from -190 °C to +812 °C (over 1000 °C temperature span) without significant change in signal (input /output) or power supply voltages. While the operating frequency and functional complexity is far below silicon-based ICs, these SiC application specific ICs (ASICs) are nevertheless becoming capable of providing unique and advantageous harsh-environment circuit functionality without cooling/sheltering overhead. With modest adjustments, the SiC JFET-R fabrication process is compatible with semiconductor mass-production tools and materials. As an initial step towards manufacture, a majority of processing steps to realize the next SiC JFET-R IC prototype wafer run have been outsourced to commercial foundry. It is expected that further upscaling combined with technology transfer to commercial production will lower investment and risk barriers to useful application deployment.

high temperature↗

Increasing Data Discovery and Re-Use: The Space Life Sciences Ontology

Two of the most important goals of the adoption of the FAIR principles are increasing the ability of agents to find and re-use research data. Achieving these goals for space life sciences research is even more pressing, given the relatively expensive and scarce nature of these data. We have reported in the past on the progress made by exemplar life sciences data systems towards implementing FAIR, showing gaps particularly in the “interoperability area” of the principles; the lack of common conceptual models for space life science research is one reason for this gap. There were few available resources that define, annotate, categorize or otherwise relate various kinds of metadata describing the acquisition, nature, and intent of investigational space life sciences data. To address this gap, NASA is working with the Open Biological and Biomedical Ontology Foundry (https://obofoundry.org/) to develop the Space Life Science Ontology (SLSO) that is intended to support archival and other kinds of systems that operate using these data. The scope of the ontology includes concepts regarding those aspects of investigation design and execution specific or unique to space environments, such as types of specialized equipment, operating organizations, and documentation. The ontology is continually being developed and published to the life science community (https://github.com/nasa/LSDAO/); at the time of this publication, the SLSO newly and uniquely defines 30 types (classes), 90 properties, and 14 relations specific to space life sciences metadata. In addition, the SLSO reuses (imports) some 2,360 types (classes), 49 properties, and 393 relations from other ontologies that are relevant to these kinds of metadata. In addition to its role as a common conceptualization for space biomedical research activities, the SLSO can also be used to provide automated support for traditionally difficult and expensive activities such as data curation and cross-system data integration and analysis.

fair↗

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗

Proton Testing of AMD Ryzen 3 1200 Microprocessors

Single-Event Effects (SEE) testing was conducted on the AMD Ryzen 3 1200 microprocessor. Testing was conducted at Massachusetts General Hospital's (MGH) Francis H. Burr Proton Therapy Center on June 2nd, 2019.

single event functional interrupt (SEFI)↗