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At least 505 records · Page 28

Hf‐W chronology of a macrochondrule from the L5/6 chondrite Northwest Africa 8192

Abstract A large, igneous‐textured, and 2 cm‐sized spherical object from the L5/6 chondrite NWA 8192 was investigated for its chemical composition, petrography, O isotopic composition, and Hf‐W chronology. The petrography and chemical data indicate that this object closely resembles commonly found chondrules in ordinary chondrites and is therefore classified as a “macrochondrule.* As a result of metal loss during its formation, the macrochondrule exhibits elevated Hf/W, which makes it possible to date this object using the short‐lived 182 Hf‐ 182 W system. The Hf‐W data provide a two‐stage model age for metal–silicate fractionation of 1.4 ± 0.6 Ma after Ca‐Al‐rich inclusion (CAI) formation, indicating that the macrochondrule formed coevally to normal‐sized chondrules from ordinary chondrites. By contrast, Hf‐W data for metal from the host chondrite yield a younger model age of ~11 Ma after CAIs. This younger age agrees with Hf‐W ages of other type 5–6 ordinary chondrites, and corresponds to the time of cooling below the Hf‐W closure temperature during thermal metamorphism on the parent body. The Hf‐W model age difference between the macrochondrule and the host metal demonstrates that the Hf‐W systematics of the bulk macrochondrule were not disturbed during thermal metamorphism, and therefore, that the formation age of such objects can still be determined even in strongly metamorphosed samples. Collectively, this study illustrates that chondrule formation was not limited to mm‐size objects, implying that the rarity of macrochondrules reflects either that this process was very inefficient, that subsequent nebular size‐sorting decimated large chondrules, or that large precursors were rare.

58 GEOSCIENCES↗

Modeling of crack bridging in a unidirectional metal matrix composite

The effective fatigue crack driving force and crack opening profiles were determined analytically for fatigue tested unidirectional composite specimens exhibiting fiber bridging. The crack closure pressure due to bridging was modeled using two approaches: the fiber pressure model and the shear lag model. For both closure models, the Bueckner weight function method and the finite element method were used to calculate crack opening displacements and the crack driving force. The predicted near crack tip opening profile agreed well with the experimentally measured profiles for single edge notch SCS-6/Ti-15-3 metal matrix composite specimens. The numerically determined effective crack driving force, Delta K(eff), was calculated using both models to correlate the measure crack growth rate in the composite. The calculated Delta K(eff) from both models accounted for the crack bridging by showing a good agreement between the measured fatigue crack growth rates of the bridged composite and that of unreinforced, unbridged titanium matrix alloy specimens.

Ghosn, Louis J.↗

Modeling of crack bridging in a unidirectional metal matrix composite

The effective fatigue crack driving force and crack opening profiles were determined analytically for fatigue tested unidirectional composite specimens exhibiting fiber bridging. The crack closure pressure due to bridging was modeled using two approaches; the fiber pressure model and the shear lag model. For both closure models, the Bueckner weight function method and the finite element method were used to calculate crack opening displacements and the crack driving force. The predicted near crack tip opening profile agreed well with the experimentally measured profiles for single edge notch SCS-6/Ti-15-3 metal matrix composite specimens. The numerically determined effective crack driving force, Delta K(sup eff), was calculated using both models to correlate the measure crack growth rate in the composite. The calculated Delta K(sup eff) from both models accounted for the crack bridging by showing a good agreement between the measured fatigue crack growth rates of the bridged composite and that of unreinforced, unbridged titanium matrix alloy specimens.

Ghosn, Louis J.↗

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗

Helium bubble formation in aged plutonium metal at ambient conditions

A model of helium bubble formation is developed that assumes the initial nascent bubbles are generated when two diffusing helium atoms come within a distance of about the interatomic spacing of the plutonium atoms. These nascent bubbles are assumed to be locked in place and grow as additional helium atoms diffuse across their surfaces. Calculations of the helium-bubble number density and sizes as a function of age are compared to experiment. This leads to an inferred helium diffusion coefficient of-the-order of 10 -20 m 2 /s, supports the idea that most of the helium from alpha-decay end up in bubbles, and that previous transmission electron microscopy size estimates are biased low. The energy that helium can transfer to 40-year-old plutonium, upon expansion, is determined to be <0.1 Joules per gram of metal. The model predicts differences between the bubble properties in naturally and accelerated aged plutonium.

36 MATERIALS SCIENCE↗

Geomycology

Fungi have long been known to have capabilities for reduction and alkylation of arsenate and selenate but their general capabilities for solubilizing and accumulating metallic substances have been given serious attention only in recent years. Common members of the Aspergillaceae cultured on boron, copper, lead and other metals or oxides can solubilize and concentrate the elements or their compounds. To account for biosolubilization of the metals, we have set up a model study, incubating selected metals, e.g., mercury, in solutions of various metabolites including L-lysine and citric acid. Results of 100-300 days incubation showed that many metals can in fact be readily solubilized, and in some cases more effectively at pH 6-7 than at pH 1.5-2.

Puerner, N. J.↗

Documentation of the Benson Diesel Engine Simulation Program

This report documents the Benson Diesel Engine Simulation Program and explains how it can be used to predict the performance of diesel engines. The program was obtained from the Garrett Turbine Engine Company but has been extensively modified since. The program is a thermodynamic simulation of the diesel engine cycle which uses a single zone combustion model. It can be used to predict the effect of changes in engine design and operating parameters such as valve timing, speed and boost pressure. The most significan change made to this program is the addition of a more detailed heat transfer model to predict metal part temperatures. This report contains a description of the sub-models used in the Benson program, a description of the input parameters and sample program runs.

Vangerpen, Jon↗

Modelling of Surfaces. Part 1: Monatomic Metallic Surfaces Using Equivalent Crystal Theory

We present a detailed description of equivalent crystal theory focusing on its application to the study of surface structure. While the emphasis is in the structure of the algorithm and its computational aspects, we also present a comprehensive discussion on the calculation of surface energies of metallic systems with equivalent crystal theory and other approaches. Our results are compared to experiment and other semiempirical as well as first-principles calculations for a variety of fcc and bcc metals.

Bozzolo, Guillermo↗