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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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Modelling the spectral influence on photovoltaic device performance using the average photon energy and the depth of a water absorption band for improved forecasting
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Code-verification techniques for an arbitrary-depth electromagnetic slot model
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In-depth analysis on parallel processing patterns for high-performance Dataframes
The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.
Spatial distribution of aerosols burden and evaluation of changes in aerosol optical depth using multi-approach observations in tropical region
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GD-OES study of the influence of second phase particles on the deuterium depth distribution in dispersion-strengthened tungsten
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High energy X-ray characterization of the microstructure of PuGa alloy samples at macroscopic depths and non-ambient conditions
High energy (95 keV) X-rays were utilized to characterize the microstructure of eight PuGa alloy samples at room temperature and during cooling to ∼10 K. The samples had different Ga content (nominally 0-3.4 at.%), age, and history. A ninth sample, similarly characterized with neutron diffraction, was included to extend the Ga range to 7 at.%. The samples span the range from single phase α (monoclinic) to δ (face-centered cubic) PuGa, as well as a two-phase α′/δ sample. The crystallographic textures, phase fractions, lattice parameters and dislocation densities of each sample were evaluated through distinct analysis techniques. The textures of the samples were modest. In each case, the dislocation densities were relatively high, comparable to cold worked metals and metals exposed to similar radiation dose. At room temperature, the lattice parameters determined in the predominantly single-phase samples were larger than expected based on the nominal Ga concentration. The observed lattice thermal expansions of the single-phase δ samples to 10 K are self-consistent across the samples and consistent with previous measurements reported in the literature. Significantly larger thermal lattice strain is observed in the δ phase of the two-phase material due to mechanical constraint from the α′ phase, which has a three times larger thermal expansion and is much harder than the δ phase. In conclusion, the results demonstrate the unique value of high-energy X-rays for relatively routine microstructural characterization of Pu alloy samples.
Hydrolysis of poly(ester urethane): In-depth mechanistic pathway determination through thermal and chemical characterization
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Photon counting with intensified charge coupled device (ICCD) – I. In-depth detector characterization
While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.
De Facto Water Reuse: Bioassay suite approach delivers depth and breadth in endocrine active compound detection
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Modeling and testing of a highly sensitive surface acoustic wave pressure sensor for liquid depth measurements
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Bacterial community response to environmental change varies with depth in the surface soil
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Long-Term Cyclability of NCM-811 at High Voltages in Lithium-Ion Batteries: an In-Depth Diagnostic Study
High-nickel layered oxides, such as LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM-811), offer higher energy density than their low-nickel counterparts at a given voltage and are gaining major traction in automotive lithium-ion batteries for electric vehicles. Besides high-Ni content, higher charging voltages above 4.3 V vs Li + /Li boost the energy and represent another focus in battery development. Here, we investigate the long-term cyclability of NCM-811 in graphite pouch cells over 1000 deep cycles between 2.5–4.2, 2.5–4.4, and 2.5–4.5 V through a suite of sensitive characterization techniques. The NCM-811 full cells show severely deteriorated cyclability with higher charging voltages, from 78% at 4.2 V to 52 and 32% at 4.4 and 4.5 V, respectively. At 4.2 V, minor parasitic electrolyte oxidation as well as cathode Li/Ni mixing and cracking are revealed after cycling, while transition-metal dissolution and surface reconstruction into rock-salt NiO are virtually undetectable. At 4.4 and 4.5 V, transition-metal dissolution and crossover to the anode become much more pronounced and a primary contributor to the capacity fade, while significant surface NiO formation causes substantial voltage polarization, which is less noticeable at 4.2 V. Meanwhile, more severe electrolyte oxidation, Li/Ni mixing, and particle pulverization exacerbate the voltage and capacity fade. Finally, these results outline distinct challenges for stable high-Ni layered oxide cathodes in high-voltage Li-ion batteries.