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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Control of Shell Morphology in p-n Heterostructured Water-Processable Semiconductor Colloids: Toward Extremely Efficient Charge Separation

This article describes p-n heterostructured water-borne semiconductor naonoparticles (NPs) with unique surface structures via control of shell morphology. The shell particles, comprising PC60-PC61BM composite, having n-type semiconductor characteristic, notably influence the charge carrier behavior in the core-shell NPs. A one- or two-phase methodology based on a PC60 surfactant-water phase and PC61BM n-type semiconductor-organic phase provided highly specific control over the shell structure of the NPs, which promoted their superior charge separation ability when combined with poly-3-hexyl-thiophene (P3HT). Moreover, the resulting water-borne NPs exhibit shell morphology-dependent carrier quenching and stability, which was characterized via luminescence studies paired with structural analysis. Corresponding to the results, outstanding performances of photovoltaic cells with over 5 % efficiency were achieved. The results suggest that the surrounding shell environments, such as the shell structure, and its electronic charge density, were crucial in determining the overall activity of the core-shell p-n heterostructured NPs. Thus, this work provides a new protocol in the current fields of water-based organic semiconductor colloids.

charge separation↗
DOE OSTI2022

Oxidation Resistance in 1200°C Steam of a FeCrAl Alloy Fabricated by Three Metallurgical Processes

Abstract FeCrAl alloys are a leading candidate material for accident tolerant fuel cladding due to their good performance in both normal light-water reactor operating conditions as well as their resilience to high-temperature accident scenarios. For commercial-scale production, new fabrication techniques need to be investigated. In this study, the effects of fabrication methods on the high-temperature steam oxidation performance of C26M (Fe12Cr6Al2Mo in wt.%) were investigated. Three variants of C26M were manufactured: wrought (cast and forged) (WC26M), powder metallurgy hot isostatic pressing (PMC26M), and laser powder bed fusion additive manufacturing (AMC26M). All three variants were exposed to steam at 1200°C for 2 h. Results showed no significant variation in mass change between the variants after steam exposure. All three variants effectively formed stable protective alumina films with ~0.6–1.3 µ m thickness. This study suggests FeCrAl alloys have excellent resilience to high-temperature steam in nuclear reactor accident scenarios regardless of the fabrication method.

Materials Science↗
DOE OSTI2021

Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization

Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.

Renganathan, S. Ashwin↗
DOE OSTI2014

The impact of updated Zr neutron-capture cross sections and new asymptotic giant branch models on our understanding of the S process and the origin of stardust

We present model predictions for the Zr isotopic ratios produced by slow neutron captures in C-rich asymptotic giant branch (AGB) stars of masses 1.25-4 M {sub ☉} and metallicities Z = 0.01-0.03, and compare them to data from single meteoritic stardust silicon carbide (SiC) and high-density graphite grains that condensed in the outflows of these stars. We compare predictions produced using the Zr neutron-capture cross sections from Bao et al. and from n{sub T}OF experiments at CERN, and present a new evaluation for the neutron-capture cross section of the unstable isotope {sup 95}Zr, the branching point leading to the production of {sup 96}Zr. The new cross sections generally present an improved match with the observational data, except for the {sup 92}Zr/{sup 94}Zr ratios, which are on average still substantially higher than predicted. The {sup 96}Zr/{sup 94}Zr ratios can be explained using our range of initial stellar masses, with the most {sup 96}Zr-depleted grains originating from AGB stars of masses 1.8-3 M {sub ☉} and the others from either lower or higher masses. The {sup 90,} {sup 91}Zr/{sup 94}Zr variations measured in the grains are well reproduced by the range of stellar metallicities considered here, which is the same needed to cover the Si composition of the grains produced by the chemical evolution of the Galaxy. The {sup 92}Zr/{sup 94}Zr versus {sup 29}Si/{sup 28}Si positive correlation observed in the available data suggests that stellar metallicity rather than rotation plays the major role in covering the {sup 90,} {sup 91,} {sup 92}Zr/{sup 94}Zr spread.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

r -process nucleosynthesis from matter ejected in binary neutron star mergers [On r -process nucleosynthesis from matter ejected in binary neutron star mergers]

Here, when binary systems of neutron stars merge, a very small fraction of their rest mass is ejected, either dynamically or secularly. This material is neutron-rich and its nucleosynthesis provides the astrophysical site for the production of heavy elements in the Universe, together with a kilonova signal confirming neutron-star mergers as the origin of short gamma-ray bursts. We perform full general-relativistic simulations of binary neutron-star mergers employing three different nuclear-physics equations of state (EOSs), considering both equal- and unequal-mass configurations, and adopting a leakage scheme to account for neutrino radiative losses. Using a combination of techniques, we carry out an extensive and systematic study of the hydrodynamical, thermodynamical, and geometrical properties of the matter ejected dynamically, employing the WinNet nuclear-reaction network to recover the relative abundances of heavy elements produced by each configurations. Among the results obtained, three are particularly important. First, we find that, within the sample considered here, both the properties of the dynamical ejecta and the nucleosynthesis yields are robust against variations of the EOS and masses. Second, using a conservative but robust criterion for unbound matter, we find that the amount of ejected mass is ≲10 –3 M⊙, hence at least one order of magnitude smaller than what normally assumed in modelling kilonova signals. Finally, using a simplified and gray-opacity model we assess the observability of the infrared kilonova emission finding, that for all binaries the luminosity peaks around ~1/2 day in the H-band, reaching a maximum magnitude of –13, and decreasing rapidly after one day.

79 ASTRONOMY AND ASTROPHYSICS↗