Ingots of the bulk metallic glass (BMG), Zr64.13Cu15.75Ni10.12Al10 in atomic percent (at. %), are compressed at slow strain rates. The deformation behavior is characterized by discrete, jerky stress-drop bursts (serrations). Here we present a quantitative theory for the serration behavior of BMGs, which is a critical issue for the understanding of the deformation characteristics of BMGs. The mean-field interaction model predicts the scaling behavior of the distribution, D(S), of avalanche sizes, S, in the experiments. D(S) follows a power law multiplied by an exponentially-decaying scaling function. The size of the largest observed avalanche depends on experimental tuning-parameters, such as either imposed strain rate or stress. Similar to crystalline materials, the plasticity of BMGs reflects tuned criticality showing remarkable quantitative agreement with the slip statistics of slowly-compressed nanocrystals. The results imply that material-evaluation methods based on slip statistics apply to both crystalline and BMG materials.

Slowly compressed microcrystals deform via intermittent slip events, observed as displacement jumps or stress drops. Experiments often use one of two loading modes: an increasing applied stress (stress driven, soft), or a constant strain rate (strain driven, hard). In this work we experimentally test the influence of the deformation loading conditions on the scaling behavior of slip events. It is found that these common deformation modes strongly affect time series properties, but not the scaling behavior of the slip statistics when analyzed with a mean-field model. With increasing plastic strain, the slip events are found to be smaller and more frequent when strain driven, and the slip-size distributions obtained for both drives collapse onto the same scaling function with the same exponents. The experimental results agree with the predictions of the used mean-field model, linking the slip behavior under different loading modes.

One considerable concern in metallic glass is enhancing ductility by suppressing catastrophic failure by the instantaneous propagation of shear bands. Compressed nanopillars with alternating CuZr metallic glass and polyisoprene nanolaminates exhibit >30% enhancement in plastic flow, as compared with monolithic glass, without sacrifice of strength. A suppression of stochastic strain burst signature in these metallic glass‐polymer composites is reported, which is an undesirable characteristic ubiquitously present in monolithic metallic glass and in metallic glass‐metal composites. The intermittent stochastic signature is quantified in each metallic glass‐containing nanolaminate system by constructing histograms of burst size distributions and provide theoretical foundation for each behavior. The exceptional mechanical properties emergent in these MG‐polymer nanolaminate composites are attributed to the combination of nanometer size‐induced shear band suppression in metallic glasses and the damping capability of the polyisoprene layers.

In this paper, Laser Sintering (LS) of 90%W-7%Ni-3%Fe (wt.%) powders have been investigated, with the goal to understand the influence of final density by laser power, scanning speed, laser trace width, and the number of scanning passes. The results suggest that the laser power and scanning speed are the most important factors influencing density; the influence of trace width and number of scanning passes are not significant. With the in crease of laser power and decrease of scanning speed, higher density can be achieved. The microstructure anal ysis indicated that the porosity changed from open porosity to closed porosity with higher laser energy input. Energy-Dispersive X-ray Spectroscopy (EDX) analysis shows that during the sintering process, W was not melted but dissolved into the Ni-Fe matrix. Contact flattening and grain accommodation of W grains have been ob served. It suggests that both rearrangement and solution-reprecipitation mechanisms are responsible for the densification. The sintered density with respect to laser power and scanning speed was modeled by continuum modeling theory and compared with experimental results.

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