Potential TRIP/TWIP coupled effects in equiatomic CrCoNi medium-entropy alloy

Ding, Lipeng; Hilhorst, Antoine; Idrissi, Hosni; Jacques, Pascal

doi:10.1016/j.actamat.2022.118049

Cited by 46 publications

(7 citation statements)

References 46 publications

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“…It is well reported that the local atomic configuration plays an important role in SFE in MEA (importance of local effect) [39]. Most of the MEAs are developed mainly from d-transition elements.…”

Section: Modulus Of Elasticitymentioning

confidence: 99%

Accelerated prediction of stacking fault energy in FCC medium entropy alloys using multilayer perceptron neural networks: correlation and feature analysis

Mahato,

Gurao,

Biswas

2024

Modelling Simul. Mater. Sci. Eng.

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A multilayer perceptron neural networks (MLPNN) model is developed for robust and quick prediction of stacking fault energy (SFE) to overcome the challenges faced in the calculation of SFE via experimentation and atomistic calculations in FCC medium entropy alloys (MEA). The present investigation employs a three-step hybrid feature selection approach to obtain a comprehensive understanding of the prominent features that influence the SFE, as well as the interrelationships among these features. The feature space encompasses various features related to composition, lattice stability, and elemental properties, of medium entropy alloys (MEAs). The findings indicate that the estimation of SFE relies on five crucial factors: temperature, lattice stability, specific heat, ionization energy, and Allen electronegativities. Furthermore, a mathematical relationship for the estimation of the SFE is derived, considering the various influencing and prominent factors. Consequently, the MLPNN model for robust SFE prediction in MEAs is developed and the performance is evaluated using R2 scores, with values of 0.87 and 0.85 obtained for the training and testing datasets, respectively. This efficient strategy introduces a novel opportunity for the engineering of SFE in the extensive range of alloy chemistry of MEAs, enabling the quick prediction of SFE, and facilitating the systematic exploration of new alloys for the development of mechanisms that may accommodate deformation through octahedral/partial slip, twinning, and/or transformation.

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Section: Modulus Of Elasticitymentioning

confidence: 99%

Accelerated prediction of stacking fault energy in FCC medium entropy alloys using multilayer perceptron neural networks: correlation and feature analysis

Mahato,

Gurao,

Biswas

2024

Modelling Simul. Mater. Sci. Eng.

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“…This potential has been carefully benchmarked and successfully applied to predict the thermodynamics and mechanical properties of HEAs in previous studies [11,36,52,59,60]. SFE plays an important role in deformation behaviors, including dislocation gliding, deformation twinning and phase transformation [16,48,61]. Using standard methods, the generalized stacking fault energies based on this potential are determined as shown in figures 1(c) and (d).…”

Section: Model and Simulationsmentioning

confidence: 99%

Effect of loading orientation on plasticity in nano-laminated CoNiCrFeMn dual-phase high-entropy alloy: a molecular dynamics study

Shuang¹,

Liang²,

Yu³

et al. 2022

Modelling Simul. Mater. Sci. Eng.

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Dual-phase high-entropy alloys (DP-HEAs) have been proved to be a kind of promising materials that exhibit a combination of excellent strength and ductility. Previous studies have emphasized the effect of interface and phase volume fraction on mechanical performance in DP-HEAs. However, the deformation mechanisms such as interplays between dislocations and the constituent phases have not been fully understood. Particularly, the research concerning plastic anisotropy in DP-HEAs is still lacking. Here, molecular dynamics simulations are performed to probe the effect of loading orientation on plasticity in the nano-laminated face-centered cubic (FCC)/hexagonal close-packed (HCP) CoNiCrFeMn DP-HEA. Results reveal that a switch from strengthening to softening and back to strengthening is closely related to the activation of different slip systems when tailoring the inclination angles of the nanolaminates with respect to the tensile direction from 0° to 90°. Slip transfer across phase boundaries, phase transformation and the nucleation of shear bands dominate the plasticity in the samples with low, medium and high inclination angles, respectively. Furthermore, the evolution of microstructures, such as dislocations, stacking faults, and FCC/HCP phase are analyzed to study the underlying deformation mechanisms. These results can help understand the plastic anisotropy of DP-HEAs and design alloys with excellent mechanical properties for engineering applications.

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“…Phase transformation-assisted alloys have motivated investigations due to their exceptional mechanical properties and excellent application potential in advanced technologies [1][2][3][4][5][6] . However, a key bottleneck that hinders their widespread applications is the traditional strength-ductility trade-off [7] .…”

Section: Introductionmentioning

confidence: 99%

Detwinning/twin growth-induced phase transformation in a metastable compositionally complex alloy

Lu¹,

An²,

Liebscher³

2022

Microstructures

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Extensive experiments have shown that the transformation from the face-centered cubic to hexagonal close-packed ε phase usually occurs around coherent Σ3 boundaries. However, in this letter, we reveal a different transformation mechanism in a metastable dual-phase compositionally complex alloy via a systematic high-resolution scanning transmission electron microscopy analysis. The face-centered cubic γ matrix can be transformed to the hexagonal close-packed ɛ phase (as small as one unit) around an incoherent Σ3 boundary (~30 nm), i.e., the facet of the coherent Σ3 boundary. This transformation is assisted by the detwinning/twin growth of a coherent Σ3 boundary during annealing treatment (900 °C for 60 min).

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Potential TRIP/TWIP coupled effects in equiatomic CrCoNi medium-entropy alloy

Cited by 46 publications

References 46 publications

Accelerated prediction of stacking fault energy in FCC medium entropy alloys using multilayer perceptron neural networks: correlation and feature analysis

Accelerated prediction of stacking fault energy in FCC medium entropy alloys using multilayer perceptron neural networks: correlation and feature analysis

Effect of loading orientation on plasticity in nano-laminated CoNiCrFeMn dual-phase high-entropy alloy: a molecular dynamics study

Detwinning/twin growth-induced phase transformation in a metastable compositionally complex alloy

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