Phase diagram calculation: past, present and future

Chang, Y. A.; Chen, Shuanglin; Zhang, Fan; Yan, Xinyan; Xie, Fanyou; Schmid–Fetzer, Rainer; Oates, W.A.

doi:10.1016/s0079-6425(03)00025-2

Cited by 285 publications

(111 citation statements)

References 67 publications

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“…Their differences can be appreciated in Paper C (Figure 4). Phase diagram calculation based on thermodynamics are also an alternative (Chang et al 2004) such as the calculated TTT-diagram used in . The principle is based on the computational thermodynamics known as the CALPHAD (CALculation of PHAse Diagrams) method (Saunders 1995;Saunders and Miodownik 1998).…”

Section: Transformation Kinetic Parameters For Diffusional To Phasesmentioning

confidence: 99%

A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes

Murgau

Pederson

Lindgren

2012

Modelling Simul. Mater. Sci. Eng.

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This thesis is devoted to microstructure modelling of Ti-6Al-4V. The microstructure and the mechanical properties of titanium alloys are highly dependent on the temperature history experienced by the material. The developed microstructure model accounts for thermal driving forces and is applicable for general temperature histories. It has been applied to study wire feed additive manufacturing processes that induce repetitive heating and cooling cycles. The microstructure model adopts internal state variables to represent the microstructure through microstructure constituents' fractions in finite element simulation. This makes it possible to apply the model efficiently for large computational models of general thermomechanical processes. The model is calibrated and validated versus literature data. It is applied to Gas Tungsten Arc Welding -also known as Tungsten Inert Gas welding-wire feed additive manufacturing process. Four quantities are calculated in the model: the volume fraction of phase, consisting of Widmanstätten , grain boundary , and martensite . The phase transformations during cooling are modelled based on diffusional theory described by a Johnson-Mehl-AvramiKolmogorov formulation, except for diffusionless martensite formation where the Koistinen-Marburger equation is used. A parabolic growth rate equation is used for the to transformation upon heating. An added variable, structure size indicator of Widmanstätten , has also been implemented and calibrated. It is written in a simple Arrhenius format. The microstructure model is applied to in finite element simulation of wire feed additive manufacturing. Finally, coupling with a physically based constitutive model enables a comprehensive and predictive model of the properties that evolve during processing.

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Section: Transformation Kinetic Parameters For Diffusional To Phasesmentioning

confidence: 99%

A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes

Murgau

Pederson

Lindgren

2012

Modelling Simul. Mater. Sci. Eng.

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“…[1][2][3] Phase diagrams depict the dominantly stable equilibrium metallic or intermetallic phase (in the solid or liquid state) as a function of temperature and constituent composition. 4 In high temperature/ dry oxidation, the Ellingham diagram maps the enthalpy of formation of an oxide comprised of metallic elements as a function of temperature for reactions between the metal and various gaseous phases (O 2 , CO 2 , H 2 O) at equilibrium. 5 The concentration of various types of defects in these oxides can be plotted as a function of the O 2 partial pressure with a Brouwer (or Kröger-Vink) diagram.…”

Section: Introductionmentioning

confidence: 99%

“…1). It is a graphical representation of the chemical stability of various metallic (or otherwise) compounds principally formed with OH − but possibly also with a host of aqueous species (Cl − , CO 3 2− , PO 4 3− , etc) as a function of pH and aqueous metal ion concentration, [M n+ ]. 6 The electrochemical behavior of a material is often governed by pH, metal ion concentration, formation of surface oxides and hydroxides, etc., all of which are schematically represented by and analyzed in the chemical stability diagram for specific material systems.…”

Section: Introductionmentioning

confidence: 99%

Utilization of chemical stability diagrams for improved understanding of electrochemical systems: evolution of solution chemistry towards equilibrium

2018

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Predicting the stability of chemical compounds as a function of solution chemistry is crucial towards understanding the electrochemical characteristics of materials in real-world applications. There are several commonly considered factors that affect the stability of a chemical compound, such as metal ion concentration, mixtures of ion concentrations, pH, buffering agents, complexation agents, and temperature. Chemical stability diagrams graphically describe the relative stabilities of chemical compounds, ions, and complexes of a single element as a function of bulk solution chemistry (pH and metal ion concentration) and also describe how solution chemistry changes upon the thermodynamically driven dissolution of a species into solution as the system progresses towards equilibrium. Herein, we set forth a framework for constructing chemical stability diagrams, as well as their application to Mg-based and Mg-Zn-based protective coatings and lightweight Mg-Li alloys. These systems are analyzed to demonstrate the effects of solution chemistry, alloy composition, and environmental conditions on the stability of chemical compounds pertinent to chemical protection. New expressions and procedures are developed for predicting the final thermodynamic equilibrium between dissolved metal ions, protons, hydroxyl ions and their oxides/hydroxides for metal-based aqueous systems, including those involving more than one element. The effect of initial solution chemistry, buffering agents, complexation agents, and binary alloy composition on the final equilibrium state of a dissolving system are described by mathematical expressions developed here. This work establishes a foundation for developing and using chemical stability diagrams for experimental design, data interpretation, and material development in corroding systems.

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“…Phase diagram calculation based on the CALPHAD approach [2][3][4], which is used to understand the effect of the alloy chemistry on the final microstructure, is certainly one of the key stones of the ICME suite. The essence of the CALPHAD approach is to obtain self-consistent thermodynamic descriptions of the lower order systems: binaries and ternaries, in terms of the known thermodynamic and phase equilibrium data.…”

Section: Introductionmentioning

confidence: 99%

Development of a computational tool for materials design

et al. 2013

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An integrated modeling tool coupling thermodynamic calculation and kinetic simulation of multicomponent alloys is developed under the framework of integrated computational materials engineering. On the basis of Pandat TM software for multicomponent phase diagram calculation, the new tool is designed in an integrated workspace and is targeted to understand the composition-processing-structure-property relationships of multicomponent systems. In particular, the phase diagram calculation module is used to understand the phase stability under the given conditions. The calculated phase equilibrium information, such as phase composition and chemical driving force, provides input for the kinetic simulation. In this paper, the design of the modeling tool will be presented and the calculation examples from the different modules will also be demonstrated.

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Phase diagram calculation: past, present and future

Cited by 285 publications

References 67 publications

A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes

A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes

Utilization of chemical stability diagrams for improved understanding of electrochemical systems: evolution of solution chemistry towards equilibrium

Development of a computational tool for materials design

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