Microstructural Comparison of an Al-8.0Zn-1.8Mg-2.0Cu Alloy with Typical T6 and T76 Tempers

In order to analyze aging behavior of an Al-8.0Zn-1.8Mg-2.0Cu alloy, the microstructure of the alloy subjected to T6 and T76 states are investigated by transmission electron microscopy (TEM) and high-resolution electron microscopy (HREM). Based on the precipitate observations, precipitate size distributions and average precipitate size are extracted from bright-field TEM images projected along 〈110〉Alorientation with the aid of an imaging analysis. The results indicate that the main precipitates are GPI zone, GPII zone and η' phase in the T6 alloy while η' phase and η phase in the T76 alloy. The bright-field TEM observations reveal that the matrix precipitates for the T6 alloy have small size and dispersive distribution while that for the T76 alloy has big size and sparse distribution. Both have discontinuously distributed grain boundary precipitates. Quantitative structural information including precipitate size distribution and average precipitate size has been calculated by an image analysis based on the bright-field TEM images projected along 〈110〉Alorientation. The results show that the T6 alloy has a narrower precipitate size range than the T76 alloy and thus the T6 alloy possesses a smaller average precipitate size than the T76 alloy.

Anin situUSAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

Intermetallic γ′ precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure duringin situheat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoidinga prioridefinition of a functional form of the PSD. However, strong low-qscattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. This work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-qpower law slopes and demonstrates their use in anin situstudy of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.

In Situ Investigation with Neutrons on the Evolution of γ ' Precipitates at High Temperatures in a Single Crystal Ni-Base Superalloy

Single crystal Ni-base superalloys based on the  /  system are widely used in gas turbine applications. To understand the formation of  precipitates, including size distribution and growth, we performed in situ small-angle neutron scattering (SANS) measurements at elevated temperatures and - together with TEM as well as , SEM imaging - studied changes in the precipitates in short and long time scale. In the early stages, a bimodal precipitate size distribution of precipitate is observed, which (depending on the annealing temperature) changes to a cuboidal or nearly spherical morphology with almostmore or less uniform ( unimodal?) size distribution. [Note: The term "more or less" is several times repeated in the text. I cannot imagine what it in fact means. Could you change it or explain in a more clear way?]

Comparison of Compositional and Morphological Atom-Probe Tomography Analyses for a Multicomponent Fe-Cu Steel

A multicomponent Fe-Cu based steel is studied using atom-probe tomography. The precipitates are identified using two different methodologies and subsequent morphological and compositional results are compared. The precipitates are first identified using a maximum separation distance algorithm, the envelope method, and then by a concentration threshold method, an isoconcentration surface. We discuss in detail the proper selection of the parameters needed to delineate precipitates utilizing both methods. The results of the two methods exhibit a difference of 44 identified precipitates, which can be attributed to differences in the basis of both methods and the sensitivity of our results to user-prescribed parameters. The morphology of the precipitates, characterized by four different precipitate radii and precipitate size distribution functions (PSDs), are compared and evaluated. A variation of less than ∼8% is found between the different radii. Two types of concentration profiles are compared, giving qualitatively similar results. Both profiles show Cu-rich precipitates containing Fe with elevated concentrations of Ni, Al, and Mn near the heterophase interfaces. There are, however, quantitative disagreements due to differences in the basic foundations of the two analysis methods.

Cluster Dynamics Modelling of the Precipitation Kinetics in Al(ZrSc) Alloys

The precipitation kinetics path in multi-component alloys may involve a competition between atomic mobilities and precipitates thermodynamic stability. Cluster dynamics modelling (CDM) is a simulation method that allows to describe this competition without introducing any heuristic assumptions as, for example, in the classical theory of nucleation. CDM consists in solving numerically, for each time increment, the master equations expressing the balance of solute exchanges (absorption and emission) between clusters/precipitates. A key issue is the energetics of the nano-clusters in the nucleation range. The computation of the precipitate size distribution function allows the complete description of the precipitates kinetic evolution, in chemical composition and in size. The method is applied to the precipitation of the Al3(Zr,Sc) L12 phase in Al solid solutions. The model predicts fairly well in the precipitation path some observed coupling effects between the two solutes, particularly during the nucleation stage.

Development of a New 7xxx Ageing Model

A kinetic model has been developed to simulate the precipitate size distribution and the resulting yield strength during ageing of 7xxx alloys. The η phase is the only one considered. The kinetic model is mean field: precipitates of different sizes see each other through the average solid solution. Precipitates are assumed to be homogeneous in concentration and are allowed to change chemistry. Local equilibrium is assumed at the matrix-precipitate interface; the equilibrium concentrations are corrected by the curvature effect. Values of the equilibrium concentrations at the matrix-precipitate interface are solved by an iterative method: the resulting flux for each element must be compatible with equilibrium conditions and with the changing stoechiometry of the considered precipitate while maximizing the energy gained. The yield strength is derived from the precipitate size distribution through a mixture law combining the effect of each individual precipitate. The model can take into account non-isothermal treatments and can therefore simulate complicated multi-stage ageing treatment as well as a FSW weld. Results of the model are discussed and compared measurements.