Thermodynamic modeling of ordered phases in the NiAl system

Ansara, I.; Sundman, Bo; Willemin, P.

doi:10.1016/0001-6160(88)90152-6

Cited by 194 publications

(60 citation statements)

References 6 publications

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“…For the more complex case of RR1000 nickel-based superalloy, the chemistry of the γ phase is generally given as (Ni, Co, Cr, Mo) 3 (Al, Ti, Ta, Hf. The elements Al, Ti, Ta and Hf, are generally assumed to substitute into the β-sublattice, while Ni, Co, Cr, and Mo occupy the α-sublattice as predicted by first principle calculations [20][21][22][23][24][25]. Herein Hf is not found to be present at measurable levels in the precipitate size range considered in this work.…”

Section: Experimental Approachesmentioning

confidence: 78%

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

Chen

Francis

Preuss

et al. 2014

MATEC Web of Conferences

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Abstract. Size dependent compositional variations for the ordered L1 2 -structure gamma prime (γ ) precipitates in the commercial Ni-based superalloy RR1000 have been investigated using scanning transmission electron microscope (STEM) imaging combined with energy-dispersive X-ray (EDX) spectroscopy. To address the problem of quantitative compositional determination for nanoscale particles within a metal matrix we have applied a novel electrochemical method to extract individual precipitates. The use of a high-efficiency EDX detector enabled compositional measurements to be obtained for particles with diameters as small as 20 nm with acquisition times of the order of a few minutes. We have studied compositional variations across the different size families of γ precipitates within a microstructure generated by slow cooling. Our results demonstrate the importance of kinetic factors for determining the precipitates compositions. In particular, we provide new evidence for the role of aluminium antisite atoms on the low-temperature growth kinetics of fine scale γ precipitates. Our findings provide valuable structural data towards improving the accuracy of predicting the microstructural evolution in Ni-based superalloys.

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Section: Experimental Approachesmentioning

confidence: 78%

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

Chen

Francis

Preuss

et al. 2014

MATEC Web of Conferences

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“…It includes support for multi-component Redlich-Kister polynomials using the Muggianu ternary extension [10], the Inden-Hillert-Jarl magnetic model [11,12], and the order-disorder model for atomic ordering [13,14] For parametric model contributions, users can use the param_search argument defined in the function signature of every energetic contribution to query a Database for parameters satisfying some criteria. The Model class defines a redlich_kister_sum() convenience function to allow users to easily build multicomponent Redlich-Kister polynomials using parameters defined in a Database.…”

Section: Modelmentioning

confidence: 99%

pycalphad: CALPHAD-based Computational Thermodynamics in Python

Otis

Liu

2017

JORS

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The pycalphad software package is a free and open-source Python library for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria using the CALPHAD method. It provides routines for reading thermodynamic databases and solving the multi-component, multi-phase Gibbs energy minimization problem. The pycalphad software project advances the state of thermodynamic modeling by providing a flexible yet powerful interface for manipulating CALPHAD data and models. The key feature of the software is that the thermodynamic models of individual phases and their associated databases can be programmatically manipulated and overridden at run-time without modifying any internal solver or calculation code. Because the models are internally decoupled from the equilibrium solver and the models themselves are represented symbolically, pycalphad is an ideal tool for CALPHAD database development and model prototyping.

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“…The description for the thermodynamic modeling of an order-disorder transition was introduced by Ansara et al, 16) and allows the Gibbs energy of the disordered phase and the ordering energy contribution to be evaluated independently. 17,18) However, no identification with neutron diffraction is available for this phase.…”

Section: The 1 and 2 Phasesmentioning

confidence: 99%

Thermodynamic Analysis of the V–H Binary Phase Diagram

2008

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A thermodynamic analysis of the V-H binary system has been performed by combining first-principles calculations with the CALPHAD approach. In order to represent the order-disorder transition between the monoclinic 1 and body-centered tetragonal 2 phases arising from the ordering of H atoms located at the octahedral interstitial sites, a (V) 1=2 (H,Va) 1=4 (H,Va) 1=4 -type three-sublattice model was applied. The formation energies of the -VH 2 hydride phase and solid solution phases were calculated in the ground state using the Full-potential Linearized Augmented Plane Wave method, and the estimated values were introduced into a CALPHAD-type thermodynamic analysis, along with some experimental information on the phase boundaries and the hydrogen isotherms. The calculated phase diagram and hydrogen isotherms were in good agreement with these experimental results.

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Thermodynamic modeling of ordered phases in the NiAl system

Cited by 194 publications

References 6 publications

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

pycalphad: CALPHAD-based Computational Thermodynamics in Python

Thermodynamic Analysis of the V–H Binary Phase Diagram

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Thermodynamic modeling of ordered phases in the NiAl system

Cited by 194 publications

References 6 publications

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

On the diffusion mechanisms of fine-scaleγ′ in an advanced Ni-based superalloy

pycalphad: CALPHAD-based Computational Thermodynamics in Python

Thermodynamic Analysis of the V&ndash;H Binary Phase Diagram

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Product

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Thermodynamic Analysis of the V–H Binary Phase Diagram