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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Impact of surface growth method and surface treatment in niobium-based superconducting devices

We explore the comparison between two growth methods for niobium film - sputtering and electron-cyclotron resonance growth - for niobium-based superconducting resonators. We discuss some of the key properties of the films, including surface characterization and residual resistance measurements metrics. We present our design of various devices used in this study including superconducting resonators and qubits, both in planar configurations and integrated in 3D cavities, as well as experimental characterization of coherence metrics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗
NASA NTRS1972

Magnetic hysteresis classification of the lunar surface and the interpretation of permanent remanence in lunar surface samples

A magnetic hysteresis classification of the lunar surface is presented. It was found that there is a distinct correlation between natural remanence (NRM), saturation magnetization, and the hysteresis ratios for the rock samples. The hysteresis classification is able to explain some aspects of time dependent magnetization in the lunar samples and relates the initial susceptibility to NRM, viscous remanence, and to other aspects of magnetization in lunar samples. It is also considered that since up to 60% of the iron in the lunar soil may be super paramagnetic at 400 K, and only 10% at 100 K, the 50% which becomes ferromagnetic over the cycle has the characteristics of thermoremanence and may provide for an enhancement in measurable field on the dark side during a subsatellite magnetometer circuit.

Wasilewski, P.↗
NASA NTRS1972

TRW vortex-lattice method subsonic aerodynamic analysis for multiple-lifting-surfaces (N. surface) TRW program number HA010B

The program was designed to provide solutions of engineering accuracy for determining the aerodynamic loads on single- or multiple-lifting-surface configurations that represent vehicles in subsonic flight, e.g., wings, wing-tail, wing-canard, lifting bodies, etc. The preparation is described of the input data, associated input arrangement, and the output format for the program data, including specification of the various operational details of the program such as array sizes, tape numbers utilized, and program dumps. A full description of the underlying theory used in the program development and a review of the program qualification tests are included.

Gomez, A. V.↗