Ostwald Ripening of a Narrow Precipitate Size Distribution

1971 ◽  
Vol 75 (6) ◽  
pp. 533-535 ◽  
Author(s):  
Alan J. Markworth
2011 ◽  
Vol 278 ◽  
pp. 42-47 ◽  
Author(s):  
Ralph Gilles ◽  
Debashis Mukherji ◽  
H. Eckerlebe ◽  
Pavel Strunz ◽  
Joachim Rösler

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?]


1989 ◽  
Vol 157 ◽  
Author(s):  
R. C. Birtcher ◽  
J. Rest ◽  
D. S. Bergstrom

ABSTRACTAfter implantation into Ni at room temperature, Kr condenses under high pressure as an fee solid aligned with the Ni lattice. Evolution of these precipitates during subsequent thermal annealing to a temperature of 650 C has been followed with transmission electron microscopy and modeled with rate theory.Room temperature implantation results in a monomodal size distribution of small solid Kr precipitates. When Kr is implanted into Ni at 500 C, some precipitates grow to larger sizes, and the precipitate size distribution becomes bimodal. Annealing to temperatures below 600 C after room temperature implantation produces a bimodal size distribution consisting of small solid Kr precipitates and large Kr bubbles. Annealing above 600 C leads to more complete precipitate motion and coalescence that eliminates all small precipitates and results in a monomodal size distribution of large faceted bubbles.Rate-theory modelling of Kr implantation into Ni at 500 C suggests that small solid Kr precipitates are immobile and that Kr melting is required for precipitate mobility. Similar calculations for thermal annealing experiments show that the bubble size distribution becomes bimodal when only a small fraction of the small precipitates melt and become mobile during annealing, while the size distribution remains monomodal when all precipitates become mobile after Kr melting at higher temperatures.


2017 ◽  
Vol 50 (3) ◽  
pp. 734-740 ◽  
Author(s):  
Ross N. Andrews ◽  
Joseph Serio ◽  
Govindarajan Muralidharan ◽  
Jan Ilavsky

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.


2006 ◽  
Vol 519-521 ◽  
pp. 321-326 ◽  
Author(s):  
Christophe Sigli

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.


2021 ◽  
Author(s):  
Istvan Geresdi ◽  
Lulin Xue ◽  
Sisi Chen ◽  
Youssef Wehbe ◽  
Roelof Bruintjes ◽  
...  

Abstract. A hybrid bin microphysical scheme is developed in a parcel model framework to study how natural aerosol particles and different types of hygroscopic seeding materials affect the precipitation formation. A novel parameter is introduced to describe the impact of different seeding particles on the evolution of the drop size distribution. The results of more than 100 numerical experiments using the hybrid bin parcel model show that: (a) The Ostwald-ripening effect has a substantial contribution to the broadening of the drop size distribution near the cloud base. The efficiency of this effect increases as the updraft velocity decreases. (b) The efficiency of hygroscopic seeding is significant only if the size of the seeding particles is in the coarse particle size range. The presence of the water-soluble background coarse particles reduces the efficiency of the seeding. (c) The efficient broadening of the size distribution due to the seeding depends on the width of the size distribution of water drops in the control cases, but the relation is not as straightforward as in the case of the glaciogenic seeding.


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