Quantitative characterization of nanosized precipitate distributions in glassy alloys

Many material properties of alloys are strongly influenced by the precipitation of secondary phases in the bulk material. Traditional alloys have been polycrystalline, but over the years many types of advanced alloys have been obtained by precise tailoring of microstructure. One of these advanced alloys is the metallic glass, which is obtained by rapid quenching of a liquid into a metastable amorphous solid. The lack of long-range ordering in this phase has been shown to yield remarkable material properties such as extremely high yield strength and high corrosion resistance. One drawback of the amorphous phase is that it is very brittle and critical failure caused by a heterogeneous dislocation density is common. At the frontier of research on glassy-type alloys are the nanocrystalline composite alloys, where a controlled dispersion of nanosized crystallites is allowed to form by controlled heat treatment of the alloy system, yielding even more refined material properties. For example, alloys with high ductility and high strength, tunable corrosion resistance, or excellent soft-magnetic properties have been obtained. Regardless of whether the alloy is glassy, nanocrystalline, or polycrystalline, engineering of the microstructure is key, but far from trivial. A theoretical method well suited for simulating distributions of precipitates on a continuum scale is the classical nucleation and growth theory (CNGT), where the statistical precipitate population within a unit volume can be simulated. To quantitatively study colloid distributions of precipitates experimentally, small-angle scattering (SAS) is an advantageous method.This licentiate thesis is based on two research papers on precipitation in glassy alloys. Paper I is about oxygen-induced, unwanted, crystallization in the commercially available glassy alloy AMLOY-ZR01 (Zr Cu Al Nb ). Using X-ray characterization tech- niques and CNGT, the impact on phase transformations of this hard, ductility-deteriorating phase was investigated at various oxygen concentrations during rapid heating. The oxygen concentration is shown to be strongly correlated with the phase-formation hierarchy. This study thoroughly elucidates how oxygen impurities affect the devitrification of Zr-based bulk metallic glass (BMG), which is one of the main obstacles in overcoming the pro- cessing of BMG with additive manufacturing (AM). Paper II focuses on the analysis of SAS data from X-rays (SAXS) using the indirect Fourier-based model fitting approach. A method for separating model parameters is implemented and thoroughly benchmarked toward the standard method. A reduced computational wall time is obtained while the parameter precision is maintained. The Fourier-based model is found to inherently suffer from parameter correlations, and large discrepancies to the true values are observed when the intensity peak in the signal is not well defined. Based on the obtained results, a program called pySASA, which is built with parallelization using message passing interface to rapidly fit large batches of data, is presented. The solution structure around which this program is built can be one of the keys to keeping the full model analysis of SAS datarelevant in the future.