Search

Alumina has been liquid state bonded with pure Al and Al-4 wt% Mg and the mechanical behavior of the bonds has been characterized. It has been shown that failure never occurs by interface cracking. Instead, when the bond layer is thick, the bond strength is limited either by plastic flow or by ductile fracture in the metal. Conversely, when the bond layer is thin, failure occurs in the ceramic, limited by the strength of the ceramic. The Al alloy bond has also been shown capable of arresting cracks by plastic blunting.

A study has been made of the effect of solute (Mn, Al, Ni) additions on microstructure refinement due to large strain deformation in single phase, copper solid solutions. The solutes were specifically selected for their influence on stacking fault energy (SFE) of copper, and the large strain deformation was imposed by chip formation in machining. The microstructure of Cu- 0.7at%Ni chip consists of elongated, sub-micrometer sized grains while Cu-7at%Al chip is made up of long, thin microbands with twins. The microstructure of the chip changes as the SFE of the material varies. With all of the solid solutions studied, the hardness of the chips is found to be significantly greater than that of the bulk material. Recrystallization temperature of solid solution chips is found to be higher than those of pure copper chips.

The single-edge V-notched-beam fracture testing method was used to measure the short-crack R-curve behavior of a 90-vol%-alumina–10-vol%-ceria-doped zirconia multilayered composite. The initiation and extension of short cracks from the V-notch tip were observed in situ via optical microscopy. Initial crack lengths of 15–50 μm were obtained repeatedly. The resulting R-curve was similar to the R-curve that was measured using the surface-crack-in-flexure testing method. The ability to control the position of the V-notch tip within a material permits study of the influence of specific microscopic features on the fracture behavior.

Microstructural length scales, such as dendritic spacings in cast metallic alloys, play an essential role in the properties of structural components. Therefore, quantitative prediction of such length scales through simulations is important to design novel alloys and optimize processing conditions through integrated computational materials engineering (ICME). Thus far, quantitative comparisons between experiments and simulations of primary dendrite arms spacings (PDAS) selection in metallic alloys have been mainly limited to directional solidification of thin samples and quantitative phase-field simulations of dilute alloys. In this article, we combine casting experiments and quantitative simulations to present a novel multiscale modeling approach to predict local primary dendritic spacings in metallic alloys solidified in conditions relevant to industrial casting processes. To this end, primary dendritic spacings were measured in instrumented casting experiments in Al–Cu alloys containing 1 wt.% and 4 wt.% of Cu, and they were compared to spacing stability ranges and average spacings in dendritic arrays simulated using phase-field (PF) and dendritic needle network (DNN) models. It is first shown that PF and DNN lead to similar results for the Al-1 wt.%Cu alloy, using a dendrite tip selection constant calculated with PF in the DNN simulations. PF simulations cannot achieve quantitative predictions for the Al-4 wt.%Cu alloy because they are too computationally demanding due to the large separation of scale between tip radius and diffusion length, a characteristic feature of non-dilute alloys. Nevertheless, the results of DNN simulations for non-dilute Al–Cu alloys are in overall good agreement with our experimental results as well as with those of an extensive literature review. Simulations consistently suggest a widening of the PDAS stability range with a decrease of the temperature gradient as the microstructure goes from cellular-dendrites to well-developed hierarchical dendrites.