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Boron, either uncombined or combined with nitrogen or carbon added to tungsten powder prior to processing, effectively inhibits grain growth. The tungsten material is stable up to 1800 degrees C.
Interstellar silicates are likely to be a part of all grains responsible for visual extinction (Av) in the diffuse interstellar medium (ISM) and dense clouds. A correlation between Av and the depth of the 9.7 micron silicate feature (measured as optical depth, tau(9.7)) is expected if the dust species are well 'mixed. In the di&se ISM, such a correlation is observed for lines of sight in the solar neighborhood. A previous study of the silicate absorption feature in the Taurus dark cloud showed a tendency for the correlation to break down at high Av (Whittet et al. 1988, MNRAS, 233,321), but the scatter was large. We have acquired Spitzer Infrared Spectrograph data of several lines of sight in the IC 5 146, Barnard 68, Chameleon I and Serpens dense clouds. Our data set spans an Av range between 2 and 35 magnitudes. All lines of sight show the 9.7 micron silicate feature. The Serpens data appear to follow the diffuse ISM correlation line whereas the data for the other clouds show a non-linear correlation between the depth of the silicate feature relative to Av, much like the trend observed in the Taurus data. In fact, it appears that for visual extinctions greater than about 10 mag, tau(9.7) begins to level off. This decrease in the growth of the depth of the 9.7 micron feature with increasing Av could indicate the effects of grain growth in dense clouds. In this poster, we explore the possibility that grain growth causes an increase in opacity (Av) without causing a corresponding increase in tau(9.7).
The primitive solar nebula was a violent and chaotic environment where high energy collisions, lightning, shocks and magnetic re-connection events rapidly vaporized some fraction of nebular dust, melted larger particles while leaving the largest grains virtually undisturbed. At the same time, some tiny grains containing very easily disturbed noble gas signatures (e.g., small, pre-solar graphite or SiC particles) never experienced this violence, yet can be found directly adjacent to much larger meteoritic components (chondrules or CAIs) that did. Additional components in the matrix of the most primitive carbonaceous chondrites and in some chondritic porous interplanetary dust particles include tiny nebular condensates, aggregates of condensates and partially annealed aggregates. Grains formed in violent transient events in the solar nebula did not come to equilibrium with their surroundings. To understand the formation and textures of these materials as well as their nebular abundances we must rely on Nucleation Theory and kinetic models of grain growth, coagulation and annealing. Such models have been very uncertain in the past: we will discuss the steps we are taking to increase their reliability.
Aluminide intermetallics, because of their strength, microstructural stability, and oxidation resistance at elevated temperatures, represent potential structural materials for use in advanced energy conversion systems. This inherent potential of the intermetallics can currently not be realized in connection with the general brittleness of the materials under ambient conditions. It is pointed out, however, that brittleness is not an inherent characteristic. Single crystals are ductile and polycrystals may be, too, if their grains are fine enough. The present investigation is concerned with an approach for reducing material brittleness, taking into account thermal-mechanically induced grain refinement in NiAl, a B2 aluminide which melts at 1638 C and which retains complete order to its melting point. Attention is given to the kinetics of recrystallization and grain growth of warm-worked, nickel-rich material.
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While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. Additionally, it is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.
A deep operator network (DeepONet) has been constructed that generates accurate representations of phase-field model simulations for evolving two dimensional metal grain morphology growing from melt. These representations serve as lower resolution, computationally efficient stand-ins for quick parameter space exploration of solutions to the the Allen-Cahn equations that dictate the phase-field model simulations. The experimental target for the phase-field model is a uranium casting system cooling a 434 g uranium charge from a maximum temperature of 1400° C at an average rate of 30° C / min , traversing the crystallographic phases of the pure metal. Experimental parameters inform the phase-field model, whose higher resolution computational model solutions are used to train the DeepONet in a given parameter space with the aim of developing a faster, more efficient method for predicting the solidifying metal's microstructure at different potential experimental values. The final DeepONet generates high accuracy, lower resolution predictions with cumulative relative approximation error over all timesteps of less than 0.5%, while ensuring solutions remain within physically feasible ranges. Further, these relative error values are comparable with other state-of-the-art DeepONet models for microstructure evolution, while significantly reducing the amount of training data required. Training a convolutional neural network simultaneously with the DeepONet, enforcing realistic values at the complex metal grain boundaries, and mathematically encoding boundary conditions into the structure of the DeepONet improved prediction accuracy and computational efficiency over a standard DeepONet model.
Understanding the formation mechanism of layered oxide cathodes via solid-state synthesis is imperative to achieving controllability over their materials properties and electrochemical behaviors. In this work, we investigate the phase and microstructure evolution during the synthesis of NaNi 1/3 Fe 1/3 Mn 1/3 O 2 , a model sodium-ion layered oxide cathode, using a combination of imaging, diffraction, and spectroscopic techniques. We unravel the synthetic mechanistic pathways involved in the high-temperature calcination reaction, as well as elaborate the synthesis-microstructure-performance relationship of this material. The formation of the final layered oxide phase involves a gradual transformation through a sodiated oxyhydroxide intermediate. During the reaction, the precursor dehydration reaction dominates at 250–550 °C, while the major sodiation reaction occurs at 550–850 °C. Alongside multiple stages of phase transformations, the final grain structure formation occurs through the continuous growth of the (003) and (104) facets. During the reaction, Mn acts as the charge-compensating element and exhibits depth-dependent characteristics. When the sodiation reaction dominates over dehydration, the reaction intermediates undergo gradual electronic structure changes with increasing temperature, as indicated by the spectral features of TM3d-O2p hybrid states. Calcination duration is also a critical parameter governing the microstructure, surface reactivity, phase fraction distribution and electrochemical performance of the material. The optimal calcination duration was determined to be 18 hours at 850 °C under the conditions evaluated here. Calcination beyond this duration was found to be detrimental to electrochemical performance due to Na and O loss and heterogeneous sodium distribution throughout the particles. Our work sheds light on the complex crystallographic-chemical-microstructural evolution of sodium ion layered oxide cathodes and provides insight into precisely tuning material properties which are intimately linked to battery performances.
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