Thermoelastic properties and γ’-solvus temperatures of single-crystal Ni-base superalloys

Horst, Oliver Martin; Schmitz, D.; Schreuer, J.; Git, P.; Wang, Hongcai; Körner, Carolin; Eggeler, Gunther

doi:10.1007/s10853-020-05628-w

Cited by 18 publications

(8 citation statements)

References 60 publications

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“…From VF100 to VF0, that is, with decreasing content of the c¢ stabilizing elements, the peak temperature decreases and the thermal expansion anomaly becomes less pronounced (Figure 7(c) and Table VI). Similar thermal expansion anomalies have been reported in the literature [11,52] for a series of CMSX-4 type Ni-and Co-base superalloys. The authors demonstrated that the temperature of the thermal expansion peak coincides with the c¢ solvus temperature and suggested dilatometry as a highly sensitive probe for the determination of T c¢ .…”

Section: E Thermal Expansionsupporting

confidence: 88%

“…In the alloys investigated here, the dissolution or precipitation of the c¢ phase is always associated with a significant positive contribution to the thermal expansion (Figure 7), which was also observed in other Coand Ni-based superalloys. [11,40,52] Surprisingly, such an effect, even though a weaker one, also occurs in VF0, which indicates that at low temperatures, VF0 does not have a single-phase microstructure in equilibrium. During slow heating in the dilatometer, precipitation of c¢ starts at about 700°C in VF0 samples, before the precipitates have dissolved again at the c¢ solvus temperature of 881°C.…”

Section: Anomalies Of the Thermal Expansion Behaviormentioning

confidence: 97%

“…Based on their studies on CMSX-4 type alloys, Horst et al [52] suggested two major contributions to the thermal expansion anomaly as a consequence of temperature-induced variations of the c/c¢ volume ratio: The relative c¢ area and volume fractions refer to the fraction within the local c/c¢ regions. Numbers in parentheses indicate uncertainties derived from the covariance matrix of the corresponding fully converged fit.…”

Section: Anomalies Of the Thermal Expansion Behaviormentioning

confidence: 99%

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Design of a Co–Al–W–Ta Alloy Series with Varying γ′ Volume Fraction and Their Thermophysical Properties

Volz

Xue

Bezold

et al. 2021

Metall Mater Trans A

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The γ′ volume fraction is a key parameter in precipitation-strengthened Co- and Ni-base superalloys and mainly determines the alloys’ properties. However, systematic studies with varying γ′ volume fractions are rare and the influence on thermal expansion has not been studied in detail. Therefore, a series of six Ta-containing Co-based alloys was designed with compositions on a γ–γ′ tie-line, where the γ′ volume fraction changes systematically. During solidification, Laves (C14-type) and µ (D85-type) phases formed in alloys with high levels of W and Ta. Single-phase γ or two-phase γ/γ′ microstructures were obtained in four experimental alloys after heat treatment as designed, whereas secondary precipitates, such as χ (D019-type), Laves, and μ, existed in alloys containing high levels of γ′-forming elements. However, long-term heat treatments for 1000 hours revealed the formation of the χ phase also in the former χ-free alloys. The investigation of the thermal expansion behavior revealed a significant anomaly related to the dissolution of γ′, which can be used to determine the γ′ solvus temperature with high accuracy. Compared to thermodynamic calculations, differential scanning calorimetry (DSC) and thermal expansion analysis revealed a larger increase of the γ′ solvus temperatures and a lesser decline of the solidus temperatures when the alloy composition approached the composition of the pure γ′ phase.

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Section: E Thermal Expansionsupporting

confidence: 88%

Section: Anomalies Of the Thermal Expansion Behaviormentioning

confidence: 97%

Section: Anomalies Of the Thermal Expansion Behaviormentioning

confidence: 99%

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Design of a Co–Al–W–Ta Alloy Series with Varying γ′ Volume Fraction and Their Thermophysical Properties

Volz

Xue

Bezold

et al. 2021

Metall Mater Trans A

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“…Despite its simplicity, this model has proved an adequate descriptor of high-temperature creep performance. [26] 3.…”

Section: ½2mentioning

confidence: 99%

Numerical Design of CoNi-Base Superalloys With Improved Casting Structure

Wahlmann

Bandorf

Volz

et al. 2022

Metall Mater Trans A

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Numerical methods can accelerate the design of alloys with improved material properties. One approach is the coupling of multi-criteria optimization with CALPHAD-based models of alloy properties. While this technique has already yielded promising new Nickel-base superalloys, the applicability to CoNi-base alloys has not yet been investigated. These alloys show promising properties for application as wrought high-temperature materials. We designed three CoNi-base superalloys, which were optimized for either high strength or high chemical homogeneity. The alloys were cast, and mechanical and thermophysical properties were characterized. The alloy optimized for strength showed creep performance inferior to a conventionally designed CoNi-alloy but had a much lower density. For developing highly homogeneous alloys, Scheil calculations were implemented in the optimization routine to quantify the severity of segregation. Non-equilibrium phases could be predicted successfully, resulting in a degree of homogeneity that rivaled that of a low-segregation ternary Co-base alloy. A comparison of elemental partitioning behavior and phase transition temperatures with CALPHAD calculations showed that trends are well represented for the most part. Finally, the applicability of the alloy design approach for Co-rich superalloys is evaluated, and possible applications for the optimized alloys are discussed.

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“…The γ′ solvus temperature is a critical parameter when evaluating the stability of Ni-based superalloys under high-temperature working environments and designing alloy heat treatment schedules [40] . ML has also been applied for predicting the γ′ solvus temperature of Ni-based superalloys [41][42][43][44] .…”

Section: Alloy Optimization and Design Of Ni-based Superalloysmentioning

confidence: 99%

Machine learning-guided design and development of metallic structural materials

Yu¹,

Xi²,

Pan³

et al. 2021

JMI

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In recent years, the advent of machine learning (ML) in materials science has provided a new tool for accelerating the design and discovery of new materials with a superior combination of mechanical properties for structural applications. In this review, we provide a brief overview of the current status of the ML-aided design and development of metallic alloys for structural applications, including high-performance copper alloys, nickel- and cobalt-based superalloys, titanium alloys for biomedical applications and high strength steel. We also present our perspectives regarding the further acceleration of data-driven discovery, development, design and deployment of metallic structural materials and the adoption of ML-based techniques in this endeavor.

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Thermoelastic properties and γ’-solvus temperatures of single-crystal Ni-base superalloys

Cited by 18 publications

References 60 publications

Design of a Co–Al–W–Ta Alloy Series with Varying γ′ Volume Fraction and Their Thermophysical Properties

Design of a Co–Al–W–Ta Alloy Series with Varying γ′ Volume Fraction and Their Thermophysical Properties

Numerical Design of CoNi-Base Superalloys With Improved Casting Structure

Machine learning-guided design and development of metallic structural materials

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