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Results for “Ba(GaP)2”

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
NASA NTRS1995

Electronic properties of Y-Ba-Cu-O superconductors as seen by Cu and O NMR/NQR

Nuclear Magnetic Resonance (NMR) and Nuclear Quadrupole Resonance (NQR) allow the investigation of electronic properties at the atomic level. We will report on such studies of typical members of the the Y-Ba-Cu-O family such as YBa2Cu30(6 + x) (1-2-3-(6 + x)), YBa2Cu4O8 (1-2-4) and Y2Ba4Cu7015 (2-4-7) with many examples of recent work performed in our laboratory. In particular, we will deal with Knight shift and relaxation studies of copper and oxygen. We will discuss important issues of current studies such as: (1) Existence of a common electronic spin-susceptibility in the planes (and perhaps in the chains) of 1-2-4; (2) Strong evidence for the existence of a pseudo spin-gap of the antiferromagnetic fluctuations in 1-2-4 and 2-4-7; (3) Evidence for d-wave pairing in 1-2-4; (4) Strong coupling of inequivalent Cu-O planes in 2-4-7 and possible origin for the high Tc value of this compound; and (5) The possibility to describe NMR data in the framework of a charge-excitation picture.

Brinkmann, D.↗
NASA NTRS2018

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV) and a structure from motion (SfM) approach. At 20 Forest Inventory and Analysis (FIA) subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue) point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD), basal area (BA), and aboveground biomass (AGB). We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r(sup 2) = 0.91), BA (r(sup 2) = 0.79), and AGB (r(sup 2) = 0.92), using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1%) and aspen BA (−2%) to misallocation of aspen AGB (+118%) and white spruce AGB (−50%). These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

aboveground biomass↗