Revisit the VEC rule in high entropy alloys (HEAs) with high-throughput CALPHAD approach and its applications for material design-A case study with Al–Co–Cr–Fe–Ni system

Yang, Songge; Lü, Jun; Xing, Fangzhou; Zhang, Lijun; Zhong, Yu

doi:10.1016/j.actamat.2020.03.039

Cited by 110 publications

(29 citation statements)

References 44 publications

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“…The boxplot shown in Supplementary Figure S5 also captures the uniqueness of the mean_MeltingT variable for the MPEAs forming in the single-phase BCC crystal structure. This result agrees with literature data 54 , 55 . A similar consistency between the importance variables cannot be reached for compositions that form in the single-phase FCC or AM structures using the BD and SHAP results.…”

Section: Discussionsupporting

confidence: 94%

A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys

Lee

Ayyasamy

et al. 2022

Sci Rep

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We demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative relationship between chemical composition and multi-principal element alloys (MPEA) phase formation. We trained an ensemble of support vector machines using a dataset with 1,821 instances, 12 features with low pair-wise correlation, and seven phase labels. Feature contributions to the model prediction are computed by BD and SHAP for each composition. The resulting BD and SHAP transformed data are then used as inputs to identify similar composition groups using k-means clustering. Explanation-of-clusters by features reveal that the results from SHAP agree more closely with the literature. Visualization of compositions within a cluster using Ceteris-Paribus (CP) profile plots show the functional dependencies between the feature values and predicted response. Despite the differences between BD and SHAP in variable attribution, only minor changes were observed in the CP profile plots. Explanation-of-clusters by examples show that the clusters that share a common phase label contain similar compositions, which clarifies the similar-looking CP profile trends. Two plausible reasons are identified to describe this observation: (1) In the limits of a dataset with independent and non-interacting features, BD and SHAP show promise in recognizing MPEA composition clusters with similar phase labels. (2) There is more than one explanation for the MPEA phase formation rules with respect to the set of features considered in this work.

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Section: Discussionsupporting

confidence: 94%

A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys

Lee

Ayyasamy

et al. 2022

Sci Rep

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“…Thus, by adding aluminum as an alloying element into the system, the BCC phase tends to form. As an example, in the Al x CoCrFeNi alloy, when the Al concentration increases from 0 to around 53 mol.%, phase transition gradually occurs from FCC to BCC [84]. For Al concentration between 20 and 53 mol.%, BCC is a stable phase in the system.…”

Section: Heals With Bcc Matrixmentioning

confidence: 99%

“…Symbols show the experimental validation. Reproduced from [84] with permission from Acta Materialia.…”

Section: Heals With Bcc Matrixmentioning

confidence: 99%

A review of the design of high-entropy aluminum alloys: a pathway for novel Al alloys

et al. 2021

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Aluminum (Al) alloys are of great importance and interest because of their extensive applications in various engineering fields. Lightweighting of our infrastructure has been a driver for more than the last two decades as our need to reduce carbon footprint on a global scale has become an inevitable reality. As a result, we have witnessed much progress in alloy development in Al alloys, especially with the advent of Integrated Computational Materials Engineering (ICME) and other computational tools. However, the limitations of the properties one may attain through alloy development to date have relied on the traditional solvent/solute model, where the matrix is Al with additions of elements (solute) to the matrix. Despite making much progress, we are still lockedin to the strength-ductility curve without any appreciable increase in modulus (stiffness) of the alloy. High Entropy Alloys (HEAs) provide a new paradigm as they differ from conventional alloys in entropy-based mixing logic of various elements, which is different from the solvent/solute model. HEAs offer the opportunity to move out of the strength-ductility curve as well as the opportunity to increase the alloy's modulus. In this paper, we present a retrospective view of Al alloys, followed with an understanding of the principles of HEAs, and lastly, with the idea of applying high entropy concept to conventional Al alloys to develop a novel Al alloy category, which we have coined HEAl. Preliminary results with a commentary on potential future opportunities are also given.

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“…Our predictions match perfectly well with the VEC empirical rules, which implies that the fcc phase is stable at VEC C 8. [6,49] In the CALPHAD community, the mechanically unstable phase is defined as the thermodynamically unstable phase. Meanwhile, a thermodynamic metastable phase should be mechanically stable even though they are not thermodynamically stable.…”

Section: Shape Distortion Rate (S)mentioning

confidence: 99%

“…Thus, each atom in the multi-principal-element matrix is surrounded by different kinds of atoms and suffers lattice strain and stress, which causes four core effects (e.g., high entropy, severe lattice distortion, sluggish diffusion, and cocktail effects). [6,7] Generally, the four core effects on microstructure and mechanical properties are positive and encouraging. [8] Alloy designs utilizing these positive effects become very promising to develop the next-generation HEAs.…”

Section: Introductionmentioning

confidence: 99%

Ab Initio Modeling of fcc Fe-Co-Cr-Ni High Entropy Alloys with Full Composition Range

Yang

Zhong

2021

J. Phase Equilib. Diffus.

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The Fe-Co-Cr-Ni quaternary system has been studied extensively in the past decade, not only because of the superior properties achieved like high tensile ductility and fracture toughness, but also it is the foundation for the development of FeCrCoNi-based HEAs. However, most of the investigations are mainly focusing on the equiatomic and semi-equiatomic compositions. The physical properties of non-equiatomic compositions are barely explored. In the current work, the ab initio approach is adopted to predict the lattice parameter, structure stabilities, elastic properties, and enthalpy of formations of fcc Fe-Cr-Co-Ni HEA single crystals with the special quasirandom structure (SQS) method. To expand the design of Fe-Co-Cr-Ni HEAs into a full composition range, the current simulations cover all the binaries, ternaries, and the whole quaternary system. The 2-D composition-property contour diagrams are created to show the physical properties in the ternary and quaternary systems. Our investigation shows that the fcc alloys' lattice parameter increases with the addition of Fe and Cr and decreases with Ni and Co. In addition to the enthalpy of formation at 0 K, the shape distortion rate is proposed to be another essential parameter to evaluate the crystal stability. The results show the addition of Cr would destabilize the fcc lattice and cause symmetry breaking. Finally, the result of Pugh's ratio shows that most of the fcc alloys show ductile behavior (P[ 1.75), especially for the alloys around Fe 3 Ni, FeCo, and Fe 2 NiCo (P[ 2.5). The brittle behavior (P\ 1.75) is located around Fe 3 Cr and Fe 2 CoCr. Meanwhile, Cr 2 NiCo and Cr 2 FeNiCo are considered promising compositions to be tried and verified experimentally because of the higher bulk modulus and moderate shear modulus.

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Revisit the VEC rule in high entropy alloys (HEAs) with high-throughput CALPHAD approach and its applications for material design-A case study with Al–Co–Cr–Fe–Ni system

Cited by 110 publications

References 44 publications

A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys

A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys

A review of the design of high-entropy aluminum alloys: a pathway for novel Al alloys

Ab Initio Modeling of fcc Fe-Co-Cr-Ni High Entropy Alloys with Full Composition Range

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