Mechanical Properties and Stacking Fault Energies of NiFeCrCoMn High-Entropy Alloy

Zaddach, A.J.; Niu, Chunyao; Koch, Carl C.; Irving, Douglas L.

doi:10.1007/s11837-013-0771-4

Cited by 688 publications

(293 citation statements)

References 47 publications

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“…The main reasons are the slower recrystallization rate in regions with brass texture, and the absence of preferential nucleation of brass-textured grains from shear bands. [58] The low SFE in the CoCrFeMnNi alloy as suggested by Bhattacharjee et al [58] is indeed confirmed by Zaddach et al [59] They combined experiments with first-principle calculations and concluded that the SFE of CoCrFeMnNi is between 18.3 and 27.3 mJ/m 2 . This value is close to that of conventional low-SFE alloys such as AISI 304L and brass.…”

Section: Basic Concepts and Deformation Behaviorsmentioning

confidence: 73%

High-Entropy Alloys: A Critical Review

Tsai

Yeh

2014

Materials Research Letters

2,622

853

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High-entropy alloys (HEAs) are alloys with five or more principal elements. Due to the distinct design concept, these alloys often exhibit unusual properties. Thus, there has been significant interest in these materials, leading to an emerging yet exciting new field. This paper briefly reviews some critical aspects of HEAs, including core effects, phases and crystal structures, mechanical properties, high-temperature properties, structural stabilities, and corrosion behaviors. Current challenges and important future directions are also pointed out.

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Section: Basic Concepts and Deformation Behaviorsmentioning

confidence: 73%

High-Entropy Alloys: A Critical Review

Tsai

Yeh

2014

Materials Research Letters

2,622

853

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“…The line tension parameter α = 0.123 is obtained from the atomistically-measured edge dislocation line tension in the EAM FeNiCr effective matrix, and is close to the coefficient for elemental Al [82]. The dislocation cores in HEAs show large dissociation distances d > 10b, consistent their relatively low stacking fault energies γ SF (low ab initio estimates, and large stacking fault ribbons observed experimentally [100,101,102]). The minimized parameters of Eqs.…”

Section: Fcc High Entropy Alloysmentioning

confidence: 80%

“…Direct calculations of average properties, such as C ij , b, ∆V n , σ 2 ∆Vn , and γ SF are currently feasible (see Refs. [100,101]) and provide the inputs needed for application of the simplified elasticity model. The precise dislocation core structure, direct solute/dislocation core interactions U n (x i , y j , z k ), and dislocation line tension, are all far more challenging, and perhaps prohibitively expensive, to compute.…”

Section: Identification Of Promising Materialsmentioning

confidence: 99%

Solute strengthening in random alloys

et al. 2017

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Random solid solution alloys are a broad class of materials that are used across the entire spectrum of engineering metals, whether as stand-alone materials (e.g. Al-5xxx alloys) or as the matrix in precipitatestrengthening materials (e.g. Ni-based superalloys). As a result, the mechanisms of, and prediction of, strengthening in solid solutions has a long history. Many concepts have been developed and important trends identified but predictive capability has remained elusive. In recent years, a new theory has been developed that builds on one historical model, the Labusch model, in important ways that lead to a well-defined model valid for random solutions with arbitrary numbers of components and compositions. The new theory uses first-principles-computed solute/dislocation interaction energies as input, from which specific predictions emerge for the yield strength and activation volume as a function of alloy composition, temperature, and strain-rate. Being a general model for materials that otherwise have a low Peierls stress, it has broad application and has been successfully applied to Al-X alloys, Mg-Al, twinning in Mg alloys, and recently fcc High-Entropy Alloys. Here, the new theory is presented in a general and systematic manner. Approximations and limiting cases that reduce the complexity and facilitate understanding are introduced, and help relate the new model to various physical features present among the historical array of models. The quantitative predictions of the model in the various materials above is then demonstrated.

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“…[14] This computational method has been widely used for solid solution systems, for example, stainless steels [15] and NiFeCrCoMn. [16] The results of our mechanical alloying of the selected alloy, Al 20 Li 20 Mg 10 Sc 20 Ti 30, must be divided into two materials-one which contained mainly the five components intentionally added, and another, which besides these components had significant impurity content of nitrogen and oxygen.…”

mentioning

confidence: 99%