Quantitative prediction of Suzuki segregation at stacking faults of the γ’ phase in Ni-base superalloys

Feng, Longsheng; Rao, You; Ghazisaeidi, Maryam; Mills, Michael J.

doi:10.1016/j.actamat.2020.08.056

Cited by 31 publications

(2 citation statements)

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“…The kinetics of precipitate coarsening influence the strength of alloys such that this area continues to attract the interests of many researchers. Techniques like solute segregation at precipitate interfaces in Al alloys [2][3][4][5][6], formation of stacking fault ribbons in Ni alloys [7][8][9], introduction of slow diffusing elements in superalloys [10][11][12][13][14], and application of external compressive stresses [15,16] were proposed as measures to retard the precipitate coarsening process. The mechanisms responsible for precipitate coarsening resistance are thermodynamic and kinetic in nature and involve interfacial energy reduction, solute drag against precipitate growth, development of strain fields around growing precipitates, slowing down of solute diffusion [17], etc.…”

Section: Introductionmentioning

confidence: 99%

Modification of Precipitate Coarsening Kinetics by Intragranular Nanoparticles—A Phase Field Study

Fashu

Huang

Wang

2022

Metals

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Precipitate coarsening is a major mechanism responsible for the degradation in mechanical properties of many precipitation-hardened alloys at high temperatures. With recent developments in processing of nanocomposite materials, a substantial volume fraction of inert second phase ceramic nanoparticles can be introduced into the grain interiors of polycrystalline materials. These intragranular nanoparticles can have synergistic effects of impeding dislocation motion and interacting with coarsening precipitates to modify the coarsening rate. In this work, the precipitate coarsening behavior of an alloy in the presence of intragranular inert nanoparticles was studied using the phase field method. Two key measurements of coarsening kinetics, precipitate size distribution and coarsening rate, were found to be affected by the volume fraction and the size of nanoparticles. Two novel mechanisms related to geometric constraints imposed by inter-nanoparticle distance and the blockage of solute diffusion path by nanoparticle–matrix interfaces were proposed to explain the observed changes in precipitate coarsening kinetics. The simulation results in general suggest that the use of small nanoparticles with large number density is effective in slowing down the coarsening kinetics.

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Section: Introductionmentioning

confidence: 99%

Modification of Precipitate Coarsening Kinetics by Intragranular Nanoparticles—A Phase Field Study

Fashu

Huang

Wang

2022

Metals

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“…For example, superlattice intrinsic stacking faults (SISFs) in the L1 2 phase of (Co x , N i 1−x ) 3 Al can be easily formed during high-temperature creep [32], breaking the symmetry by changing the (111) plane stacking sequence from (...ABC...) to (...ABCABABCA...), see Figure 11(a). Understanding the elemental segregations to SISFs in Ni-and Co-based superalloys is important to improve high temperature creep performance [6,33,34,35,36,7]. Cluster expansion surrogate models based on DFT calculations can facilitate the alloy design through calculating the temperature-and composition-dependent segregation profiles and stacking fault energies [6,7,7].…”

Section: Ni-al-cr Ternary Systemmentioning

confidence: 99%

Bayesian Optimization Acquisition Functions for Accelerated Search of Energy Convex Hull of Multi-Component Alloys

Wen,

Tucker,

Titus

2023

Preprint

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Atomistic simulations such as density functional theory and embedded-atom method calculations are essential for predicting many materials properties in the integrated computational materials engineering framework. For many thermodynamic properties, searching the convex hull is necessary to obtain phase stability information for materials selection, synthesis, and characterization in simulations/experiments. With increasingly complicated structures and compositions of materials, the computational cost of the expensive density functional theory calculations has become a barrier to materials design. Thus, there is a need to maximize information gained from each calculation while simultaneously identifying subsequent high-value calculations. In this work, we show that new data acquisition strategies can consider the geometry of the convex hull to maximize the yield of batch experiments done with limited computational resources. Based on Bayesian-Gaussian optimization, we developed uncertainty-based acquisition functions for weighing the conﬁgurations of multi-component alloys to learn the ground-state line. The proposed acquisition methods were validated by learning the formation energy convex hulls of the Co-Ni metallic system, the Zr-O ionic compound system, the Ni-Al-Cr ternary alloys, and the intermetallic (Ni 1−x ,Co x ) 3 Al planar defect system. By comparing to the conventional acquisition scheme using the genetic algorithm models, we demonstrated that the proposed strategies have the advantages of reducing training parameters and user interactions for selecting candidate batch experiments. We show that new acquisition functions can reduce the number of experiments required to obtain the ground-state line error by more than 30%. The new strategies can be extended to multicomponent systems and coupled with cost functions.

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Effects of Alloying Elements on Twinning in Ni-Based Superalloys

Borovikov,

Mendelev,

Smith

et al. 2024

The Minerals, Metals &Amp; Materials Series

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Quantitative prediction of Suzuki segregation at stacking faults of the γ’ phase in Ni-base superalloys

Cited by 31 publications

References 50 publications

Modification of Precipitate Coarsening Kinetics by Intragranular Nanoparticles—A Phase Field Study

Modification of Precipitate Coarsening Kinetics by Intragranular Nanoparticles—A Phase Field Study

Bayesian Optimization Acquisition Functions for Accelerated Search of Energy Convex Hull of Multi-Component Alloys

Effects of Alloying Elements on Twinning in Ni-Based Superalloys

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