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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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Stoichiometric effects on grain growth in zirconium carbide coatings for high-temperature nuclear fuel

Interest in coated particle fuel for space nuclear propulsion (SNP) has expanded in recent years due to successful demonstrations of the resiliency of the coatings to extreme environments. For SNP applications, the coating layer for the particle design needs to be able to withstand exposure to high temperature hydrogen during operating conditions. ZrC has been proposed as a protective layer, however, it is important to understand the high temperature behavior to ensure adequate protection to this fuel. In this study, surrogate ZrC coated particles were heat treated at 1900 °C up to 300 min, to examine how the microstructure evolves when exposed to high temperature. Scanning electron microscopy and electron backscatter diffraction (EBSD) were conducted to determine grain size and grain boundary character and orientation to determine the degree of change in the ZrC layer post heat treatment. Raman spectroscopy provided insight to understand how the as-fabricated stoichiometry of each sample contributed to the differences in grain growth behavior. Despite the as-fabricated samples showing a similar initial grain size and grain boundary character, the samples with a higher amount of excess carbon exhibited smaller grain areas and slower growth rates when exposed to 1900 °C. In conclusion, this investigation details the as-fabricated microstructure of the ZrC layer, specifically grain size, evolved under high temperature as this can impact the performance of the fuel under operating conditions.

EBSD

NOx mediated formation of ε – UO 3 during thermal decomposition of uranyl nitrate hexahydrate under static air conditions

The thermal decomposition of uranyl nitrate hexahydrate in air at temperatures of 650 – 800 °C is expected to yield α – U 3 O 8 through intermediate UO 3 phases. Here, n this study, Raman spectroscopy complimented by powder X-ray diffraction revealed the unexpected formation of ε – UO 3 as an accompanying phase during thermal decomposition of UNH at 700 °C under static air conditions. Experiments demonstrated that ε – UO 3 does not form during the initial ramp up stage nor during the high temperature heating period; but instead forms during the cooling stage between 250 – 400 °C. Additional experiments revealed that UNH initially decomposes through an amorphous UO 3 intermediate prior to α – U 3 O 8 formation. Attempts to bypass the U 3 O 8 precursor in the formation of ε – UO 3 were unsuccessful, supporting the necessity of U 3 O 8 (α – U 3 O 8 in this study) in the formation of ε – UO 3 . The observed phase evolution is proposed to result from the NOx species generated during UNH thermal decomposition, which create localized oxidizing conditions within the furnace under static air conditions. Furthermore, a predominantly phase pure ε – UO 3 was synthesized under static air conditions through the addition of an extra plateau at 250 °C during the cooling step. These findings demonstrate the importance of gas-phase chemistry and cooling conditions in uranium oxide phase evolution and provide additional insight into ε – UO 3 formation pathways.

Epsilon uranium trioxide

Advanced Non-Intrusive Instrumentation for Propulsion Engines

Changes in engine technology such as higher temperatures, higher tip speeds, new metal/composite/ceramic materials together with radical changes in design philosophy will require amongst other prerequisites the ability to measure and to monitor key internal gas and structural characteristics. The symposium papers presented non-intrusive measurement and analysis technologies in the following categories: Laser Point Measurements (11); Absorption and Infrared Techniques (4); Paints - Surface Sensors (6); Laser Induced Fluorescence (6); Mechanical (7); Films (5); Laser Planar Measurement (9); and a Keynote Address.

Propulsion

MEAD In-situ Sampling and Testing at Haughton Crater

The Mars Exploration through Analog-site Drilling (MEAD) project is designed to demonstrate the feasibility and scientific value of robotic drilling missions to Mars in the search for evidence of past or extant life. MEAD conducts high-fidelity field simulations integrating drilling, autonomous operations, and in-situ life-detection and mineralogical instruments. The project tests the Signs of Life Detector (SOLID), proposed for the 2019 Discovery Mars Icebreaker mission, and ARIA (Astronaut Raman Instrument for ISRU and Astrobiology), which provides mineral identification and detects trace organics and volatiles, including indicators of organic thermal maturity. Because current and planned Mars drilling missions operate largely “blind,” MEAD also evaluates the use of drill-induced vibrations recorded by deployed geophones to enable local subsurface mapping for improved targeting of drilling and sampling. In August 2025, MEAD completed its first-year field deployment to Haughton Crater in the Canadian High Arctic, an established Mars impact-crater terrestrial analog site, bringing a Honeybee Robotics TRIDENT drill with applied automation, alongside ARIA, SOLID, and FleetSpace geophones.

Haughton Crater

Autonomous Detection and Classification of Lunar Minerals Using a Convolutional Neural Network Based Framework for the SUCR DALI Project

NASA’s long-term goal is to deploy humans to the Moon and, from there, advance human exploration to Mars, with Artemis missions as pivotal milestones. Raman spectroscopy can uniquely identify minerals, compounds, water states, and other materials, providing distinctive fingerprints for classification. A Raman instrument has been successfully deployed and utilized on the Mars surface via the Perseverance rover, but has not yet been utilized at the lunar surface The SUCR DALI project is working towards developing a Raman spectroscopy instrument to be applied in various lunar mission concepts, including within the Artemis program. The objective of my research is to assist in the maturation of the proposed SUCR DALI lunar Raman instrument through the development of an autonomous detection and classification model capable of identifying minerals and water states on the Moon’s surface.

Convolutional Neural Networks