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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhancing and Extinguishing the Different Emission Features of 2D (EA(1-)(x)FA(x))(4)Pb3Br10 Perovskite Films

2D hybrid perovskites are attractive for optoelectronic devices. In thin films, the color of optical emission and the texture of crystalline domains are often difficult to control. Here, a method for extinguishing or enhancing different emission features is demonstrated for the family of 2D Ruddlesden-Popper perovskites (EA(1-)(x)FA(x))(4)Pb3Br10 (EA = ethylammonium, FA = formamidinium). When grown from aqueous hydrobromic acid, crystals of (EA(1-)(x)FA(x))(4)Pb3Br10 retain all the emission features of their parent compound, (EA)(4)Pb3Br10. Surprisingly, when grown from dimethylformamide (DMF), an emission feature, likely self-trapped exciton (STE), near 2.7 eV is missing. Extinction of this feature is correlated with DMF being incorporated between the 2D Pb-Br sheets, forming (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y). Without FA, films grown from DMF form (EA)(4)Pb3Br10, retain little solvent, and have strong emission near 2.7 eV. Slowing the kinetics of film growth strengthens a different emission feature, likely a different type of STE, which is much broader and present in all compositions. Films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) have large, micron-sized domains and homogeneous orientation of the semiconducting sheets, resulting in low electronic disorder near the absorption edge. The ability to selectively strengthen or extinguish different emission features in films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) reveals a pathway to tune the emission color in these compounds.

2D halide perovskites↗
DOE OSTI2024

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of weave path parameters on the geometry of wire arc additive manufactured features

Here, the present work investigates the effect of process parameters on the geometry of wire arc additive manufactured parts. The geometric accuracy of features produced with a weaving strategy is compared to what can be accomplished with a typical overlapping bead strategy. In this work, single-layer and multi-layer geometries were deposited under varying process and path parameters. The wavelength, amplitude, and torch speed of the weaving path were varied, while the power, wire feed speed, and contact tip to work distance remained constant. The geometric deposition efficiencies of several samples produced with a weave strategy are directly compared to samples generated with two parallel overlapping beads with torch speeds defined to match the deposition rate of the weave samples. Feature geometries were characterized using optical microscopy and laser scanning data. The results indicate that implementing a weave path strategy can improve the geometric accuracy of wire arc additive features, thus increasing the effective volumetric deposition rate of the process. It is shown that the most consistent improvements resulted from the combination of low wavelength and high amplitude, which correlate to wider and taller printed layers.

GMAW↗
DOE OSTI2021

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗
DOE OSTI2020

HAZARD ANALYSIS OF DIGITAL ENGINEERED SAFETY FEATURES ACTUATION SYSTEM IN ADVANCED NUCLEAR POWER PLANTS USING A REDUNDANCY-GUIDED APPROACH

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The role of ambient gas confinement, plasma chemistry, and focusing conditions on emission features of femtosecond laser-produced plasmas

Ultrafast laser ablation coupled with optical emission spectroscopy is currently under development for standoff detection of elements and their isotopes for a wide range of application areas. In this work, we explore the role of ambient air pressure during the interaction of an ultrafast laser beam with two metallic targets (brass and uranium) with significantly different oxygen gas-phase reactivity. Plasma plumes were generated by focusing ~800 nm, ~35 fs pulses from an ultrafast laser system using a long focal length lens with f = 1 m. Two-dimensional spectral imaging was performed over the pressure range of 30 mTorr-700 Torr air to evaluate emission dynamics, plasma chemistry, signal-to-background ratio, and characteristic parameters (i.e. excitation temperature, electron density). An increase in ambient air pressure during ultrafast laser ablation leads to plume confinement and subsequent changes in the emission dynamics due to plasma chemistry as well as changes in plasma generation conditions (i.e. focused fs laser ablation versus filament ablation). Ablation crater morphologies were also investigated via scanning electron microscopy. Results indicate atomic emission intensity and signal-to-background ratios peak at moderate pressure levels (~50-100 Torr air) for both targets studied, although plasma chemistry influences uranium emission signatures. The emission features of the uranium plasma at pressures = 10 Torr showed the presence of atoms and oxide molecules which are co-located within the plume. We also find filament ablation leads to wider, more shallow craters compared to focused laser ablation. Our study provides unique insight into the interplay between plume dynamics, confinement, and oxygen chemistry of fs laser-produced plasmas and how these phenomena evolve with changing ambient air pressure.

Laser-produced plasma↗
DOE OSTI2021

Where’s Swimmy?: Mining unique color features buried in galaxies by deep anomaly detection using Subaru Hyper Suprime-Cam data

Abstract We present the Swimmy (Subaru WIde-field Machine-learning anoMalY) survey program, a deep-learning-based search for unique sources using multicolored (grizy) imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). This program aims to detect unexpected, novel, and rare populations and phenomena, by utilizing the deep imaging data acquired from the wide-field coverage of the HSC-SSP. This article, as the first paper in the Swimmy series, describes an anomaly detection technique to select unique populations as “outliers” from the data-set. The model was tested with known extreme emission-line galaxies (XELGs) and quasars, which consequently confirmed that the proposed method successfully selected $\sim\!\! 60\%$–$70\%$ of the quasars and $60\%$ of the XELGs without labeled training data. In reference to the spectral information of local galaxies at z = 0.05–0.2 obtained from the Sloan Digital Sky Survey, we investigated the physical properties of the selected anomalies and compared them based on the significance of their outlier values. The results revealed that XELGs constitute notable fractions of the most anomalous galaxies, and certain galaxies manifest unique morphological features. In summary, deep anomaly detection is an effective tool that can search rare objects, and, ultimately, unknown unknowns with large data-sets. Further development of the proposed model and selection process can promote the practical applications required to achieve specific scientific goals.

Astronomy & Astrophysics↗
DOE OSTI2022

Photocatalytic Biocidal Coatings Featuring Zr 6 Ti 4 -Based Metal–Organic Frameworks

The world is currently suffering socially, economically, and politically from the recent pandemic outbreak due to the Coronavirus Disease 2019 (COVID-19), and those in hospitals, schools, and elderly nursing homes face enhanced threats. Healthcare textiles, such as masks and medical staff gowns, are susceptible to contamination of various pathogenic microorganisms, including bacteria and viruses. Here, metal–organic frameworks (MOFs) can potentially address these challenges due to their tunable reactivity and ability to be incorporated as porous coatings on textile materials. Here, we report how incorporating titanium into the zirconium-pyrene-based MOF NU-1000, denoted as NU-1012, generates a highly reactive biocidal photocatalyst. This MOF features a rare ligand migration phenomenon, and both the Ti/Zr center and the pyrene linker act synergistically as dual active centers and widen the absorption band for this material that results in enhanced reactive oxygen species (ROS) generation upon visible light irradiation. Additionally, we found the ligand migration process is generally applicable to other csq topology Zr-MOFs. Importantly, NU-1012 can be easily incorporated onto cotton textile cloths as a coating, and the resulting composite material demonstrates fast and potent biocidal activity against Gram-negative bacteria (E. coli), Gram-positive bacteria (S. epidermidis), and T7 bacteriophage virus with up to a 7-log (99.99999%) reduction within one hour under simulated daylight.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗