Current Projects

HRTEM image of two adjacent metastable phases in Al matrix

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HRTEM image of two adjacent metastable phases in Al matrix

Robert Kahlenberg, project start 01/2022

AlMgSi aluminum alloys (6xxx series) are among the most common light metal alloys in the automotive and aerospace industries. The microstructural processes during production are very complicated in many respects and some of them are still unexplained. The project therefore aims on the one hand to experimentally examine the production chain of semi-finished products of selected alloys and to identify key components for a better understanding of the development of the microstructure. On the other hand, the project deals with the extension and linking of existing mean-field models of the software MatCalc in order to depict several consecutive production steps and their interactions and ultimately to simulate process chains. Ultimately, material properties should be able to be calculated and optimized on the basis of process parameters.

Schematic representation of the rotary swaging process

Figure 1: Schematic representation of the rotary swaging process (Source: FELSS Group GmbH).

Robert Kahlenberg, Project start 08/2020

Al-Mg-Cu alloys (2xxx series) are well-established materials in aviation industries, due to their high strength to weight ratio in combination with a decent ductility (fatigue resistance). The main process of interest in this project is the forming of tubular parts via rotary swaging, by which high dimensional accuracy is accomplished. However, many of the process parameters used today are primarily based on experience and several gaps remain with respect to the detailed microstructural evolution during processing.

Therefore, the project focuses on the investigation and the simulation of 2024 during production, using SimpleMSE (MatCalc). Especially the influence of the deformation on precipitation kinetics as well as recrystallization phenomena and the resulting mechanical properties are key aspects.

Paul Estermann, project start: 07/2019

TU Wien / K1-Met / voestalpine Linz / Primetals

The problem of surface cracks developing on steel slabs has been a problem since the invention of continuous casting of steels more than 50 years ago. This problem is commonly referred to as second ductility minimum or intermediate temperature embrittlement. Several mechanisms are responsible for this embrittlement between 700 and 900 °C, including precipitation, ferrite formation and segregation. The aim of this project is to identify and characterize these influences both experimentally and simulatively.

The second ductility minimum and some of its causes

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Figure 1: The second ductility minimum and some of its causes

Testing is performed using a Gleeble thermal-mechanical testing machine and dilatometer, and samples are analyzed using light and electron microscopes. The simulations will use the material calculation program MatCalc and JMat Pro. By comparing the measurements with the predicted values, we can optimize the simulation parameters and find out where and at what temperatures the respective steel shows brittle behavior.

One of the mechanisms that will be of particular interest for this project is segregation. Of the two types of segregation, namely equilibrium and non-equilibrium segregation, only the second is relevant at the elevated temperatures and relatively short times present during the casting process. The process behind non-equilibrium segregation is the accumulation of solutes at grain boundaries via a flow of solute-vacancy complexes. These complexes form within the grains because it is energetically favorable for these defects to combine for some solutes. Once the material is quenched, excess vacancies at the grain boundaries are destroyed and the solute-vacancy complexes break down to compensate for this loss. As a result, a complex concentration gradient forms and the dissolved atoms that are brought along can accumulate at grain boundaries and other vacancy sinks. A similar effect can be seen when deforming the material, since certain microstructures can lead to defects during mechanical processing.

An example for grain boundary segregation

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Figure 2: An example of grain boundary segregation

Since the mechanism is based on a non-equilibrium effect, the grain boundary concentration can exceed the maximum equilibrium concentration. Once this threshold is reached, the solute atoms are desegregated again, but their movement is limited by the rate at which they can diffuse. As a result, the concentration increases sharply and then slowly decreases again over time. In some cases, this mechanism can lead to rapid embrittlement at short holding times and at elevated temperatures, which can be decisive for the ductility behavior of some steels.

 

 

[1] Caliskanoglu, O., 2016, Hot ductility investigations of continuously cast steels, dissertation, TU Wien, Vienna

[2] Li Y.J., Ponge D., Choi P. and Raabe D., 2015, Atomic scale investigation of non-equilibrium segregation of boron in a quenched Mo-free martensitic steel. Ultramicroscopy 159, 240-247. doi:10.1016/j.ultramic.2015.03.009mechanical processing can lead to defects.

Paul Estermann, Project Start: 07/2019

TU Wien / K1-Met / voestalpine Linz / Primetals

The problem of surface cracks originating on steels slabs has been a problem since the invention of continuous casting of steels more than 50 years ago. This problem is usually referred to as the second ductility minimum or intermediate temperature embrittlement. Several mechanisms are responsible for this embrittlement between 700 and 900 °C, including precipitates, ferrite formation and segregation. The aim of this project is to identify and characterize these influences using experimental techniques as well as simulations.

The second ductility minimum and some of its causes

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Figure 1: The second ductility minimum and some of its causes

The experiments are performed using a Gleeble thermal-mechanical testing machine as well as a Dilatometer and the samples are analyzed using optical and electron microscopes. The simulations will use the materials calculator program MatCalc as well as JMat Pro. Comparing the measurements and the predicted values allows us to optimize the simulation parameters and find out where the particular steel will show brittle behavior as well as at which temperatures.

One of the mechanisms which will be of particular interest for this project is segregation. Of the two types of segregation, namely equilibrium and non-equilibrium segregation, only the second is relevant at the elevated temperatures and relatively short times present during the casting process. The process behind non-equilibrium segregation is the enrichment of solutes at grain boundaries via a flux of solute-vacancy complexes. These complexes form inside the grains because it is energetically favorable for these defects to combine for some solutes. Once the material is quenched, excess vacancies are annihilated at the grain boundaries and the solute-vacancy complexes break up to compensate this loss. As a consequence, a complex concentration gradient forms and the brought-along solute atoms can become enriched at grain boundaries and other vacancy sinks. A similar effect appears when the material is deformed, because certain microstructural structures can create vacancies during mechanical working.

An example for grain boundary segregation

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Figure 2: An example for grain boundary segregation

Since the mechanism is based on a non-equilibrium effect, the grain boundary concentration can surpass the maximum equilibrium concentration. As soon as this threshold is reached, the solute atoms desegregate again, but their movement is limited by the speed at which they can diffuse. Consequently, the concentration increases sharply and then decreases slowly again over time. This mechanism can in some cases lead to rapid embrittlement at short holding times and at elevated temperatures, which may be a deciding factor for the ductility behavior of some steels.

 

[1] Caliskanoglu, O., 2016, Hot ductility investigations of continuously cast steels, Dissertation, TU Wien, Vienna

[2] Li Y.J., Ponge D., Choi P. and Raabe D., 2015, Atomic scale investigation of non-equilibrium segregation of boron in a quenched Mo-free martensitic steel. Ultramicroscopy 159, 240–247. doi:10.1016/j.ultramic.2015.03.009

Yao Shan, Project start 01/2017

With increasing efficiency of computational resources, the possibility to solve complex processes in material science via simulations becomes more and more relevant.

Evolution of various precipitates considering local coarsening

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Figure 1: Evolution of various precipitates considering local coarsening [1]

Figure 1 shows an example for various coarsening processes, in which larger precipitates grow in favor of smaller ones. In the study the local arrangement of precipitates is emphasized, which gives insight to population sizes in specific areas.

 Mechanical stress relaxation between precipitate and hole in matrix during growth

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Figure 2: Mechanical stress relaxation between precipitate and hole in matrix during growth [2]

Growth of precipitates is driven by chemical driving forces, which are dependent on the chemical composition. However, there are mechanical stresses which are slowing down the process. Figure 2 shows a study, where the hole for the precipitate in the matrix grows via creep, but has to be adapted for the precipitate to grow further.

Bake-Hardening modeling in dual-phase steel

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Figure 3: Bake-Hardening modeling in dual-phase steel [3]

Bake-Hardening is  a process used in automotive industry to harden car body panels during the painting process. Figure 3 shows the strength increase due to carbon segregation into dislocations and carbide precipitation.

Austenite grain growth influenced by solute drag

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Figure 4: Austenite grain growth influenced by solute drag [4,5]

Besides of precipitates, the grain size in the matrix is also of importance. Solutes in the matrix can segregate into grain boundaries and slow down the process of grain growth. Figure 4 shows the grain growth halted due to solute drag.

[1] J. Svoboda, Y.V. Shan, G.A. Zickler, E. Kozeschnik, F.D. Fischer, Local approach for coarsening of precipitates, Scripta Materialia 178 (2020) 232-235.
[2] J. Svoboda, Y.V. Shan, E. Kozeschnik, F.D. Fischer, Influence ofmisfit stress relaxation by power-law creep and plasticity on kinetics of coarsening of precipitates, Scripta Materialia 168 (2019) 81-85.
[3] Y.V. Shan, M. Soliman, H. Palkowski, E. Kozeschnik, Modeling of Bake Hardening Kinetics and Carbon Redistribution in Dual‐Phase Steels, Steel Research International (2020) 2000307.
[4] N. Fuchs, P. Krajewski, C. Bernhard, In-situ Observation of Austenite Grain Growth in Plain Carbon Steels by Means of High-temperature Laser Scanning Confocal Microscopy, BHM Berg- und Hüttenmännische Monatshefte 160 (2015) 214-220.
[5] J. Svoboda, F.D. Fischer, E. Gamsjaeger, Influence of solute segregation and drag on properties of migrating interfaces, Acta Materialia 50 (2002) 967-977.

Completed Projects

Figure 1: Flow curve simulations at various temperatures   Figure 2: Simulation of Mises stresses after a quenching process

Bernhard Viernstein, Start 01/2018

For the construction of automotive components, rather complex temperature- and deformation steps are necessary. To understand the material’s behavior, microstructural simulations are used beside experimental techniques, such as mechanical tests or microscopical characterizations. The aim of this work is to develop a physically based model, which is able to calculate internal stress responses of complex components in any material state. Therefore, strengthening mechanisms, such as solid solution strengthening, precipitation strengthening and work hardening need to be included. Compression tests at different temperatures are used to calibrate the model. Figure 1 shows exemplary flow curve simulations at various temperatures.

A new Abaqus user hardening (UHARD) subroutine is developed and used to calculate the component’s Mises stresses for any material state. Therefore, the temperature, the strain and the strain rate are the required input parameters. Figure 2 shows simulated Mises stresses after a quenching process. The simulations are experimentally verified in four chosen integration points.

 

Georg Siroky, Project start 01/2018

Microelectronic assemblies consist of solder joints to connect sub-assemblies and provide electric and mechanical connectivity. Damage resistant solder materials are needed to cope with ongoing miniaturization efforts [1]. Healing of solder alloys is an innovative approach to increase their damage resistance. Several materials transport mechanisms were investigated with respect to healing in metals such as, precipitation [2], electro-chemical [2] or liquid-assisted healing [3,4]. Liquid-assisted healing is thermally activated by heating the material above its solidus temperature, where it is kept in a semi-solid configuration to promote viscous material transport.  

This project aims to investigate the compositional dependency of liquid-assisted healing in Sn-Bi alloys through numerical simulation and experiments.

Experiments

Flow experiments illustrate the microstructural dependency of material transport and provide input for continuum mechanical models. Different approaches are tested to assess the flow behavior  in the semi-solid state, such as in-situ heating of micro-indents or filling of cylindrical defects. These experiments provide a measure of the microstructural mobility and healing efficiency.

[Translate to English:] Viskoser Fluss in einer kugelförmigen Vertiefung während der flüssigkeitsunterstützten Einheilung

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Figure 1: Viscous flow in a spherical indent during liquid-assisted healing

The regain of strength is assessed through a tensile damage-healing experiment. An initial loading cycle induces mechanical defects such as voids or cracks through cyclic deformation. The tensile sample is healed in an ex-situ heat treatment, where temperature and time are varied. In a post-healing loading cycle the regain of elastic stiffness and ultimate strength is determined, which quantifies the healing efficiency of the solder alloy.

[Translate to English:] Versuch zur Heilung von Zugschäden zur Beurteilung der Wiedererlangung elastischer Steifheit und Festigkeit

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Figure 2: Tensile damage-healing experiment to assess regain of elastic stiffness and strength

Simulation

Theoretical models are developed to formulate healing and its relationship with material properties (surface tension, viscosity) and external loads [5]. The micro-mechanical model provides a detailed description of healing on material scale, yet requires higher computational effort. Therefore, a simplified model with fewer parameters is developed to capture the essential healing characteristic, which allows simulations of healing solders in an microelectronic assembly [6]. The assembly design plays is an integral part of the liquid assisted healing concept, since thermo-elastic deformations of the substrates can prevent or enhance the healing efficiency in the solder. The stress state in the solder joint during healing plays a vital role for the healing evolution and is a result of the assemblies response to temperature changes.

[Translate to English:] Finite-Elemente-Modell einer Lotanordnung, bei der Temperaturschwankungen Druck- und Zugspannungszustände induzieren

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Figure 3: Finite Element model of solder array where temperature variation induce compressive and tensile stress states [7].

[1]            S. Cheng, C. Huang, M. Pecht, Microelectronics Reliability Review paper A review of lead-free solders for electronics applications, Microelectron. Reliab. 75 (2017) 77–95. doi:10.1016/j.microrel.2017.06.016.

[2]            S. Zhang, N. van Dijk, S. van der Zwaag, A Review of Self-healing Metals: Fundamentals, Design Principles and Performance, Acta Metall. Sin. (English Lett. (2020). doi:10.1007/s40195-020-01102-3.

[3]            C.R. Fisher, H.B. Henderson, M.S. Kesler, P. Zhu, G.E. Bean, M.C. Wright, J.A. Newman, L.C. Brinson, O. Figueroa, M. V Manuel, Repairing large cracks and reversing fatigue damage in structural metals, Appl. Mater. Today. 13 (2018) 64–68. doi:10.1016/j.apmt.2018.07.003.

[4]            S. Danzi, V. Schnabel, J. Gabl, A. Sologubenko, H. Galinski, R. Spolenak, Rapid On-Chip Healing of Metal Thin Films, Adv. Mater. Technol. 1800468 (2019) 1–6. doi:10.1002/admt.201800468.

[5]            G. Siroky, E. Kraker, D. Kieslinger, E. Kozeschnik, W. Ecker, Micromechanics-based damage model for liquid-assisted healing, Int. J. Damage Mech. 0 (2020) 1–22. doi:10.1177/1056789520948561.

[6]            G. Siroky, D. Melinc, J. Magnien, E. Kozeschnik, D. Kieslinger, E. Kraker, W. Ecker, Healing solders: A numerical investigation of damage-healing experimentse, in: 2020 21st Int. Conf. Therm. Mech. Multi-Physics Simul. Exp. Microelectron. Microsystems, 2020: pp. 1–7.

[7]              G. Siroky, E. Kraker, J. Magnien, E. Kozeschnik, D. Kieslinger, W. Ecker, Numerical study on local effects of composition and geometry in self-healing solders, 20th Int. Conf. Therm. Mech. Multi-Physics Simul. Exp. Microelectron. Microsystems. (2019). doi:10.1109/EuroSimE.2019.8724583.

Alice Redermeier, Project start: 04/2017

TU Wien / MCL / AMAG 

The Al 6xxx alloys are an important group of age-hardenable materials, which are used in a broad field of applications, like automotive, marine and construction areas.  The main alloying elements in the 6xxx series are magnesium and silicon.

In the ternary Al-Mg-Si system the precipitation sequence to the stable Mg2Si (b) is generally accepted to be

[Translate to English:] ternäres Al-Mg-Si-System

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The precipitation path in the commercial 6xxx series becomes even more complicated and is influenced by many factors, such as heat treatment (Figure 1) and the chemical composition.

 

[Translate to English:] Atomprobenanalysediagramm

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Figure 1:  Atom probe analysis for (a) long-term natural aging, (b) 3.6 ks and (c) 28.8 ks aging according to heat treatment procedure B2, respectively, and (d) 28.8 ks aging according to heat treatment procedure A at 170°C [1].

In this project, we focus on the cluster formation and evolution in the Al-6xxx series. By combining experimental and atomistic simulation methods we will get a fundamental understanding of the early stages of cluster formation in 6xxx series. Furthermore, these findings will serve as input for the thermokinetic modeling software MatCalc to simulate the whole production process in the Al-6xxx series.

References:

[1]  S. Pogatscher, H. Antrekowitsch, H. Leitner, T. Ebner, P.J. Uggowitzer, Acta Mater. 59 (2011) 3352–3363. DOI: 10.1016/j.actamat.2011.02.010

Philipp Retzl, Project start: 01.01.2017

TRIP steels exhibit the highest combination of strength and formability, resulting from the strain-induced transformation of retained austenite to martensite, designated as the TRIP effect.1

The TRIP-effect

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Figure 1: The TRIP-effect

Scheme of an ESP-plant

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Figure 2: Scheme of an ESP-plant

In this project existing experimental methods to find suitable steel compositions and thermomechanical treatments applicable on an ESP-Plant are carried out. In order to increase our understanding of important microstructural mechanisms that govern the properties of the final product theoretical models are developed. These models are able to describe important features of the complex microstructures that occur in TRIP steels. Figure 3 shows a SEM (scanning electron microscope) micrograph of a typical TRIP microstructure consisting of ferrite, bainite, austenite and/or martensite.

SEM-picture of the Microstructure of a TRIP steel

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Figure 3: Microstructure of a TRIP steel (SEM)

1.  Retzl P, Mayer W, Krizan D, Kozeschnik E. Simulation of Carbo-Nitride Precipitation in the Multi-Phase Microstructure of Micro-Alloyed Transformation-Induced Plasticity Steel. Steel Res Int. 2020;2000197:1-9. doi:10.1002/srin.202000197

David Melinc, 03/2018 - 02/2021 

The objective of this project is to investigate self-healing properties for a lead-free solder at typical application temperatures. The distinct environment in microelectronic devices with varying temperatures should hereby provide the trigger and driving force for liquid-assisted-healing. A prolonged lifetime of solder joints in real structures is aspired by benefiting from the mechanical and thermal straining environment

A crack in sample propagates primarily in the Bi-rich RHOMBO_A7 phase

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Figure 1: A crack in sample propagates primarily in the Bi-rich RHOMBO_A7 phase

In the course of this project, the influences of thermal treatment and composition on microstructure development and mechanical properties, like the Young’s modulus, uniform elongation and UTS are assessed. Mechanical fatigue damaged dog-bone-shaped bulk, lap-shear solder samples and the regain of mechanical resistance against uniform tensile stress of the latter caused by differences in healing temperature are evaluated.

Tensile test of “as-cast” and “cyclic loaded” samples

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Figure 2: Tensile test of “as-cast” and “cyclic loaded” samples compared to different healing states (120°C, 130°C, and 140°C)

Christoph Etzlstorfer, 07/2016 - 06/2019

Within the project steel composite materials produced by hot roll cladding are examined. The layer structure changes mechanical and chemical properties compared to the individual monolithic materials.

Metal composites with different thicknesses and material combinations are cladded and characterized in terms of their mechanical properties. The different compositions of the different layers lead to C diffusion. Consequently, the shifted C content significantly affects the properties of the steel and may counteract the original aim of cladding. Thus, the diffusion during the production process and heat treatments is simulated using the software tool MatCalc and compared to real test results.

The goal of the project are to evaluate the potential of steel composites. Another issue is the feasibility of production process.

Aurelie Jacob, 04/2016 - 12/2017

Thermodynamic databases are an essential input for simulating materials properties especially phase equilibria. Depending on the materials the thermodynamic databases are not always accurate and need to be corrected or developed to reproduce experimental evidence.
Thermodynamic databases are based on the Calphad method. This method allow to describe the phase equilibria and thermodynamics of multicomponent systems. Each phase present in a system is described by its Gibbs energy as a function of composition, temperature and pressure. The Gibbs energy function is obtained by fitting it to experimental phase diagrams and thermodynamic of considered sub-systems.
The thermodynamic databases are then used in Matcalc to simulate long term ageing and precipitation behavior allowing the prediction of the life time of the materials.

Harald Radlwimmer, 12/2014 - 11/2018

Continuous casting is the most commonly used process in steel production since many decades. A major focus of investigation is on the straightening operation, which usually takes part in a region of reduced ductility (typically between 1200 °C and 600 °C). Hence, straightening is a delicate operation often causing rejection and/or repair of the slab.

Typically, the susceptibility to fail at a certain temperature was determined using laboratory scale hot tensile tests and metallographic investigation methods. However, the laboratory approach is – compared to a computational one – not only time consuming, but also expensive, as it generates high costs (equipment, samples, workforce).

These facts are our driving force for the development of a computational solution within the software package MatCalc. In the future, we will be able to forecast, if a steel grade is prone to crack, or not. Engineers will be able to develop a thermal profile for successful straightening operations of certain steel grades, and vice versa.

Wen Wen Wei, 10/2014 - 09/2018

Currently, there is a emergent need for effective and practical industrial model for predicting the deformation capability of Mg alloys. Unlike the BCC and FCC metals, the Mg alloys have a HCP structure, which profoundly influences the deformation properties of Mg alloys. The twinning is prone to occur in Mg, playing an important role in deformation performance of Mg. Due to the poor understanding of twinning mechanism in Mg, the existed industrial models fail to predict the deformation performance of Mg precisely. Therefor, in order to develop more reliable industrial model, the underlying physics such as the twinning micro-structure evolution and hardening process need to be understood at atomic level, giving rise to a multi-scale modeling in Mg alloys.
        Overall, the aim of this project is to obtain a reliable meson-scale industrial model for deformation in Mg alloy, which will successfully predict the flow curve or other deformation behavior of Mg alloys. Besides, the physics pertaining to the mechanism of twinning will be thoroughly investigated at atomic level.

Markus Rath, 07/2014 - 06/2018

The overall objective of this project is the development of enhanced material models for the process chain simulation for thermo-mechanical processing of nickel-based alloys. This will be realiszed by means of a combined experimental and theoretical research programm with the following detailed objectives:

  • Development of physical-based modeling approaches for the microstructure evolution.
  • Development of a microstructure-based flow-stress model.
  • Development of a stable thermo-mechanical process for a new nickel-based alloy considering the damage behavior by means of the inverse process chain simulation method.

Lin Qin, 05/2014 - 04/2018

TU Wien (sub-project of VICOM P13: Multiscale simulations of nucleation in solid and liquid solutions)

In Fe-Cu-based alloys, the additional elements Mn and Ni are experimentally observed to play a role in increasing the nucleation rate of Cu precipitates and interfering the composition distribution of pre-nucleation clusters [1]. However, the detailed mechanism of how these alloy additions influence the nucleation evolution is not well understood. Atomic scale simulations such as molecular dynamics and Monte Carlo simulations have advantages in straightforwardly revealing the mechanism and kinetics of precipitation processes. But from a computational point of view, since nucleation is a rare event, long range of simulation time scale is needed to observe full nucleation processes, particularly at low super saturation, when energy barriers are high and nucleation of a precipitate is rare on the time scale of basic atomic motions. Other challenge for atomic methodologies is to find out an efficient way to calculate the energies and forces needed in simulations.  To address the challenges, Kinetic Monte Carlo simulations and Rare Event sampling techniques [2] are combined to investigate micro structures and transition pathways in this complex nucleation process, and then quantitatively evaluate the effects of ternary elements on nucleation rates. All the simulations are based on a computationally inexpensive energy description — simple pair potentials for ternary systems, which takes into account the local chemical environment (LCE) [3] in atom-vacancy exchange events.

[Translate to English:] Experimentelle Beobachtung der Mn,Cu,Ni,Fe-Verteilung im Cu-Cluster nach (a)1h (b) 4h (c)1024h Alterung.

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Figure 1: experimental observation of Mn,Cu,Ni,Fe distribution in Cu cluster after aging for (a)1h (b) 4h (c)1024h. 

COLLABORATION:

We cooperate with Prof. Christoph Dellago’s group from institute of Computational Physics, University of Vienna.

REFERENCE:

[1] Kolli R.P., Seidman D. N. (2008),The temporal evolution of the decomposition of a concentrated multi-component Fe-Cu-based steel. Acta Mater.

[2] Dellago C. Bolhuis P. G. (2008), Transition Path Sampling and other Advanced Simulation Techniques for Rare Events, Advances in Polymer Science 221, 167.

[3] Warczok P., Shan Y., Schober M., Leitner H., Kozeschnik E. (2011), Analysis of Clustering Characteristics during early Stages of Cu Precipitation in bcc-Fe, Solid State Phenomena 172-174, 309–314.

Thomas Weisz, 05/2014 - 04/2018

AMAG/MCL Leoben

Rising number of international competitors enforce aluminum producing companies to optimize their production process routes and offer high-quality products to be able to stay competitive in the global market. During the fabrication of aluminum plates from the ingot casting to a final product, the material undergoes a sequence of production steps, which eventually determine the properties of the manufactured part. The number of influencing factors and parameters in the whole process-chain is tremendous. Any experimental investigation of the resulting material characteristics for optimization purpose or property prediction is highly time-consuming and cost-intensive with limited applicability.

graphic of a casting and rolling process

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The purpose of this project is concentrating on one material (AA6061) and adapting, optimizing and coupling the individual models that have been developed in different distinct projects to provide a predictive through-process simulation of microstructures and properties of aluminum plate production route with real industrial parameters. Simulation capability should cover the quite complex interactions of different process steps in an integrated sequence.

The result will be a sequence of specific models fully integrated in MatCalc to describe the plate production process route of AA6061 plates.

Christoph Krüger, 05/2014 - 04/2018

For the development of new steel grades it is necessary to know, which microstructure is needed to achieve the desired mechanical properties. Besides the chemical composition, the heat treatment is one of the important process steps to do so. In the steel sheet production cycle, the heat treatment takes place through an annealing line. Here the strips are heated in the ferrite austenite area, soaked for specific time at this temperature and then cooled down. Knowledge about the formed phase fractions and the grain sizes is necessary to achieve the desired properties.  

The objective of the project is the development of phase transformation models, which are applicable under continuous heating and cooling conditions, to simulate the heat treatment on a continuous annealing line with the prediction of the grains sizes.

Goals of the present project are:

  • Development of two different phase transformation models for continuous heating and cooling
  • Development and implementation of a new phase transformation module  for MatCalc
  • Development of a single program for the simulation of recovery, recrystallization and phase-transformation
  • Validation of the  developed models with dilatometer tests for  different steels 
  • Institut für Werkstoffwissenschaft und Werkstofftechnologie

Heinrich Buken, 03/2014 - 02/2018

To have knowledge about the impact of occurring recrystallization phenomena during manufacturing of steel can be one key ability to improve the final product properties e.g. the final alpha grainsize. During multipass plate rolling operations recrystallization can take place in the interpass time after deformation (static recrystallization) or during deformation (dynamic recrystallization) which changes the former microstructure and may affect the recrystallization result of further hot deformation.

Recrystallization in the austenitic range of “one phase alloys” is phenomenological well described by constitutive laws like JMAK- equations for the description of temperature, time, starting grainsize and deformation degree dependant development of the recrystallized fraction. For the case of one phase alloys that is e.g. C- Mn- steel in the austenitic range many constitutive laws are available and are capable of providing more or less sufficient knowledge about the static recrystallization behaviour [1–3].

Concerning two- or multiphase alloys like Ti, Nb and V microalloyed steel recrystallization kinetics can become more complicated and constitutive laws might not be appropriate anymore to describe recrystallization kinetics properly as a further dimension enters and influences the system. Particles cause a pinning pressure on grain boundaries. The magnitude of this Zener Drag effect is mainly determined by the precipitated phase fraction and the precipitate size and has its basic idea in the saving of energetically unfavourable total grain interface area [4]. Deformation provides a higher dislocation density in the material and effects the precipitation process by providing a higher nucleation site density and a higher diffusion in the bulk. By reason of this interplay the formulation of constitutive laws in the framework of JMAK- equations describing wide ranges of compositions, temperatures and deformation degrees becomes more difficult. Nevertheless these are available in literature in case of microalloyed steel [5] illustrating in dependence of micro alloying contents slower transformation times than plain C-Mn- steel. Following a JMAK- relationship these approaches are not capable of explaining curves where “plateaus” can be found in the recrystallized fraction against time curves.

In my work I try to avoid phenomenological approaches. By describing recrystallization kinetics in terms of nucleation and growth and combining this approach with the excellent precipitate calculations of MatCalc, I am able to model the interaction of precipitation and recrystallization during static recrystallization. Figure 1 shows one example of my modeling work. These experiments are taken from Quispe et al [6] who carried out double hit compression tests on a V- micro alloyed steel. Below ca. 1000°C V(C, N) precipitates become thermodynamically stable and fine dispersed and strain induced precipitates encumber the grain boundaries with a retarding pressure.

 Progress of recrystallization as a function of temperature and different starting grain sizes

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Figure 1: Progress of recrystallization as a function of temperature and different starting grain sizes.

Nevertheless there is still much to investigate within this topic. To find more accurate values for driving forces and mobilities in dependence of material compositions and starting microstructures are medium-term aims of my work.

[1]         M. Sellars and J. A. Whiteman, “Recrystallization and grain growth’in hot rolling,” no. April, 1979.

[2]         J. Beynon and C. M. Sellars, “Modelling Microstructure and its effects during multipass hot rolling,” ISIJ Int., vol. 32, no. 3, pp. 359–367, 1992.

[3]         C. M. Sellars, “Modelling microstructural development during hot rolling,” vol. 6, no. November, pp. 1072–1081, 1990.

[4]         P. A. Manohar, M. Ferry, and T. Chandra, “Five Decades of the Zener Equation,” ISIJ Int., vol. 38, no. 9, pp. 913–924, 1998.

[5]         P. D. Hodgson and R. K. Gibbs, “A mathematical model to predict the mechanical properties of hot rolled C-Mn and microalloyed steels,” ISIJ Int., vol. 32, no. 12, pp. 1329–1338, 1992.

[6]         A. Quispe, S. F. Medina, M. Gómez, and J. I. Chaves, “Influence of austenite grain size on recrystallisation–precipitation interaction in a V-microalloyed steel,” Mater. Sci. Eng. A, vol. 447, no. 1–2, pp. 11–18, Feb. 2007.

Johannes Kreyca, 10/2013 - 09/2017

Initial yield strength and hardening behaviour during plastic deformation condensed in temperature and strain rate dependent flow-curve are crucial input for finite element simulation. Traditionally these curves are measered for one material state (for example T6 for Al alloys) over different temperatures and strain-rates. They are only valid for this specific state. In this project we use state parameter based models to predict flow-curve behaviour for different material states. It is the current microstructure that defines the stress response in a further deformation. Therefore it is essential to model the microstructure evoltution (dislocation and subgrain formation, precipitation interaction, recrystallisation) over deformation, temperature and time to predict flow-curve behaviour. We use our labratory facilities to experimentally determine flow-curve behaviour in the traditional way and to compare the data with our model results.

Further reading:

[1] Kreyca J., Falahati A., Kozeschnik E., Microstructure and flow stress modeling during plastic deformation of an aluminum alloy type A6061, Elsevier, MEFORM 2015.

[2] Kreyca J., Falahati A., Kozeschnik E., Modelling microstructure evolution in polycrystalline aluminium - Comparison between one- and multi-parameter models with experiment, ESAFORM 2015. 

Siamak Rafiezadeh, 04/2013 - 02/ 2017

Numerous limiting factors, in 7xxx series rolling ingots impair the productivity of the process. An optimum homogenization of ingots plays a key role in decreasing the defects and increasing the workability of downstream process. This includes; removing and/or controlling the inhomogeneous distribution of alloying elements on a microscale, dissolution of low melting point phases, dissolving or spheroidizing hard iron containing phases and formation of fine and well distributed dispersoid particles.
Main objectives of this research consist of two interactively bonded goals. The first is to determine the effect of homogenization treatment on the evolution of the particles, especially the grain boundary and low melting point ones, and to establish the correlations of the process parameters such as time and temperature with the fractions of these particles in the structure. The second is to provide proper simulation tools and reliable physically based models to be able to optimize the homogenization process.
 

Simulation of the formation and evolution of the Cr-dispersoid (Al18Mg3Cr2) in 7075 alloy during homogenization process

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Fig 1. Simulation of the formation and evolution of the Cr-dispersoid (Al18Mg3Cr2) in 7075 alloy during homogenization process

Martin Lückl, 07/2012 - 06/2016

During the continuous casting process of steel slabs, the skin layer is exposed to high thermal- and thermo-mechanical stresses. These stresses may lead to formation and growth of cracks during this process. Especially deformation at temperatures in the region of the second ductility minimum appears to be critical. A low ductility level is often observed in a temperature range of 600°C to 1200°C. Bending of the continuous cast slab is commonly performed in this temperature range, causing a threat to the surface (Figure 1).

Schematic Illustration of continuous casting

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Figure 1: Schematic Illustration of continuous casting

One mechanism responsible for ductility loss is the interaction of precipitates with recrystallization. Precipitates hinder dislocation movement and the recrystallization process. Aluminum nitride (AlN) is attributed to have significant influence on the decrease of ductility.

In this project, several heat treatments of samples with the Gleeble1500 thermo-mechanical simulator will be performed. The microstructure and the size and distribution of precipitates will be described by optical light microscopy and transmission electron microscopy. Simultaneously, thermo-kinetic processes occurring in the material during testing are going to be simulated by software tool MatCalc. Finally experimental results and numerical data will be compared.

Piotr Warczok, 04/2012 - 03/2015

The production of aluminium foils of age hardenable aluminium alloys include homogenization, hot rolling, cold rolling and heat treatments. Starting with the microstructure after homogenization followed by hot rolling, the evolution of the grain and subgrain structure during cold rolling as well as recovery and static recrystallization during the subsequent continuous heat treatments will be described for aluminium alloys (2xxx, 6xxx, 7xxx) by using both, continuous and discrete models. The objective of this project is to develop a model for the simulation of the microstructure evolution during cold rolling and subsequent heat treatment to couple it with the already developed models for the previous steps along the production chain.

The microstructure of commercial wrought materials is the result of multi-step processing. Age hardenable alloys are produced through the following steps: homogenization of the discontinuously cast slab, hot rolling, cold rolling, recrystallization heat treatment, further cold rolling and aging. The developed microstructure is a consequence of dynamic recovery during hot deformation, static recrystallization immediately after hot deformation, elongation of grains during cold deformation and static recrystallization after cold/hot deformation during heat treatment.

During cold deformation, the flow stress increases with strain until a maximal value is reached, where damage starts and ends in fracture. The grains are elongated in the rolling direction and the density of dislocations increases with deformation. Formation of dislocations during plastic deformation is reflected in the stress increment, since both are directly related.

There are basically three types of heat treatments that are used in in the processing of wrought age hardenable aluminium alloys:
- Solution heat treatment, usually in the range of 480-560°C to bring alloying elements into solution. Recrystallization as well as normal and also abnormal grain growth can take place during this treatment. Fast cooling is finally applied to obtain a supersaturated solid solution, freezing the developed microstructure.
- Recrystallization treatment to improve formability between cold rolling steps, carried out at 300-450°C results in a recovered or recrystallized structure.
- Aging is generally carried out between 150-250°C depending on the alloy and the
holding time. Although no change in the grain and subgrain structure is expected at low temperatures, fine and well distributed metastable phases precipitate, increasing the strength and decreasing formability. If further cold deformation such as stretching or cold rolling takes place to combine the effect of both, precipitation and strain hardening, these changes in the mechanical properties should be taken into account.

Georg Stechauner,  04/2012 - 03/2016

TU Wien in cooperation with Materials Center Leoben

Precipitation hardening (PH-)steels owe considerable part of their strength to the formation of a fine dispersion of precipitates of various types. Even though precipitation hardening steels were extensively used over the last decades, some fundamental questions remain unanswered and shall be investigated in this project.

Yield stress of 17-4 PH stainless steel as a function of aging time at 400°C

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Fig 1 – Yield stress of 17-4 PH stainless steel as a function of aging time at 400°C. [1]

Goals of the present project are:

  • Understanding the mechanisms responsible for hardening in the selected steels. Analyzing the relation between processing – structure – properties. 
  • Determining mechanical properties and identifying precipitates with TEM.
  • Implementation of alloys in MatCalc computer simulations based on the information gathered.
  • Suggestion of new parameters (T,t) established on MatCalc simulations.

By answering these questions and developing models, a cost-effective way of designing new materials in the future shall be found.

[Translate to English:] TEM-Hellfeld-Bild der d-Ferrit-Phase in 17-4 PH-Edelstahl nach Lösungsbehandlung

Fig 2 – TEM bright-field image of the d-ferrite phase in 17-4 PH stainless steel after solution treatment. Fine Cu precipitates are observed. Some of them are apparently associated with dislocations. [1]

References:

[1] Murayama et al., ‘Microstructural Evolution in a 17-4 PH Stainless Steel after Aging at 400 °C’, Metall. Mater. Trans. A, 30 (1999) 345-353.

Katharina Umlaub, 02/2012 - 01/2015

In lightweight construction and the automotive industry, a reduction of weight can be achieved by the combination of different high-strength and/or lightweight materials, e.g., aluminum and steel. However, steel and aluminum are not easily bonded and, therefore a strong need exists for a simple manageable joining technology.

Due to the formation of intermetallic phases at the interface, the material combination of Fe and Al is particularly difficult to obtain due to the occurrence of brittle phases that are easily fractured.

The goal of the present project is to produce welding joints between two different metals on the basis of a bimetallic strip.

The bimetal-strip, which can be seen as a pre-manufactured joint between two materials, should be joined by a method where no or only little intermetallic phase occurs. The bond can be achieved, for instance by cold roll bonding.
Afterwards the bimetal is connected with similar metals on each side, i.e., for an aluminum-steel-strip, the aluminum side is welded to the aluminum-bimetal side and the steel side to the steel-bimetal side.

Principle of the formation of welding joints by means of a bimetallic strip consisting of aluminum and steel

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Fig 1: Principle of the formation of welding joints by means of a bimetallic strip consisting of aluminum and steel

Focus of the project lies on the production of the ideal bimetallic strip and the joint connection of different material combinations with the goal of providing a technique for production of durable weldments between dissimilar metals showing high potential for undesired brittle phases.

Tomasz Wojcik, 07/2011 - 06/2014

Plate steels represent an important sector of the European steel industry. Plate products are used for line pipes, off-shore structures, wind power plants and many other important applications. Slab casting is the most relevant process step during manufacturing of plates.

Continuous casting has evolved into a mature technology. However, the problem of surface cracking still persists. Surface cracks imply cost-intensive slab conditioning or even exclude promising alloying concepts from production. Precipitation is known as the main cause of surface cracking in continuous casting. Micro-alloyed steels involve several chemical constituents, which can precipitate, such as Ti, Nb, V, Al, Cr or B. They form nitrides and carbides.

The general target is to design caster operation and alloying in such a way that cracking is excluded or minimized. This requires full knowledge on the times and location of precipitates and their size distribution. It is essential to develop numerical models, which predict the precipitation progress in the caster. They should consider the cooling patterns as well as deformation due to bending or unbending. Such models can be used to adjust casting and alloying schemes.

Experimental work in the laboratory is used to gain empirical data; several characterization and simulation methods will be applied. Results will be translated into a physical model and the relevant kinetic or microscopic parameters will be determined. This is complemented by studies and detailed investigations on industrial materials.

Alice Redermeier, 01/2011 - 12/2014

TU Wien (sub-project of VICOM P10 Multi-Scale Simulations of Multi-Component Phases) 

Modeling precipitation in multi-component systems by combining efficiently the results of ‚first-principles‘ calculations (i.e. Vienna ab initio simulation package – VASP [1-2]) with Cluster Expansion method ((i.e. Universal Cluster Expansion Code UNCLE [3]) to determine the relevant effective cluster interactions (ECI). These ECI’s will then be applied to Atomistic Kinetic Monte Carlo  (AKMC) method to simulate the time evolution of precipitates.

Cluster Expansion in a nutshell:

A multi-component system can be treated as lattice with a spin-like occupation number Si(σ). In a binary system for example this number takes values of +1 and -1, depending on whether the site is occupied by an A or an B atom. The energy of such a many-body system E(σ) can be understood as a summation over 0-body-, 1-body-, 2-body-, etc . structure interactions (Figure 1) which are weighted by the effective cluster interactions Ji, Jij, ...,  parameters.

Therefore the Cluster Expansion is a generalization of the Ising-Hamiltonian

the picture shows a formula

© A. Redermeier

In principle, this summation is infinite. However, some J-parameters will be very small and can be omitted in the calculation. Hence, it is possible to represent E(σ) as a finite sum for the practical application.

Possible 3-, 4-, 5 and 6-body structures of a bcc lattice

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Figure 1:  Possible 3-, 4-, 5 and 6-body structures of a bcc lattice. NN denotes next-neighbor.  (Blum et al, Phys. Rev. B 72, 165113 (2005))

AKMC – Motivation and State of the Art:

From an atomistic view diffusion occurs when an atom (X) changes its lattice site with a vacancy (V).  The atom has to overcome the saddle point energy (Figure 2) to change its place succesfully.  This exchange – the so called jump - is thermally activated and its frequency ΓXV can be described by

[Translate to English:] das Bild zeigt eine Formel

 

 

 

The attempt frequency vx describes the number of jump attempts per second. The „jump success“ rate is dependent on the migration energy ΔExmig. The latter is a difference between the sattle point and equilibrium site energies. Both will be represented with the ECI parameters found during the cluster expansion.

An atom changes its place with a vacany.

© A. Redermeier

Figure 2:  An atom changes its place with a vacany. In order to do this the atom has to overcome the saddle point energy.

Collaboration:

We aspire toward these goals together with the scientific groups from Institute of Physical Chemistry (University of Vienna). This work is financed in part by Vienna University of Technology and in part by project P10 of the SFB Vienna Materials Laboratory (VICOM).

References:

[1] G Kresse and J. Furthmüller, Phys. Rev. B 54, 11169 (1996)

[2] G Kresse and D Joubert, Phys. Rev. B 59, 1758 (1999)

[3] D Lerch, O Wieckhorst, G L W Hart, R W Forcade and S Müller, Modelling Simul. Mater. Sci. Eng. 17, 055003 (2009)

Jaroslav Zenisek, 07/2011 - 06/2015

During diffusion, certain amount of diffusing atoms might achieve energetically favorable positions in the matrix which are unlikely (but not impossible) to be left. Such positions can be called atomic traps. People involved in this project develop models for diffusion and phase transformation in a multi-component matrix with many sorts of atomic traps. My role is to verify those models by experiments.

I investigate diffusion of carbon connected with phase transformation by performing carburizing experiments and subsequent analyses. Here, phase transformation means either formation of carbides or ferrite-austenite transformation. Our carburizing device is schematically shown in figure 1, some effects of carburizing are illustrated in figure 2, and ferrite-austenite transformation is shown in figure 3.

 A schematic of the carburizing apparatus

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Figure 1. A schematic of the carburizing apparatus. The specimen is held in the middle of the heater by a suspension chain (not drawn here). When the carburizing is finished, the top end of the chain is released and the specimen falls via open shutter to the cold cup.

light-microscope image of the cross-section of carburized specimen, carbon concentration as function, carbon maps for three carburizing intervals

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Figure 2. (a) light-microscope image of the cross-section of carburized specimen with nicely visible different structures. SEM details show grain boundary carbides and carbides in the surface region. (b) carbon concentration as function of distance from the surface calculated for three carburizing intervals. The shape of the curves depends also on the carbides developed during carburizing. (c) carbon maps for three carburizing intervals. The regions with highest / lowest carbon concentration appear yellow-red / dark blue.

[Translate to English:] Ferrit-zu-Austenit-Umwandlung, die über eine bewegliche Grenze verläuft

Figure 3. Ferrite-to-austenite transformation proceeding via moving boundary. (a) fully ferritic matrix – initial stage. (b) austenitic band growing from the carburized surface, here (at room temperature) visible as pearlitic structure. (c) more developed band than in (b) after longer carburizing interval.

Carburizing experiments are carried out using various materials with differently active atomic traps. The atomic traps are supposed to affect diffusion and consequently the growth of carbides or movement of the austenite-ferrite interface. Carbon concentration profiles is measured and compared to those based on the new models. Additional information is gained from the microstructural studies.

Yao Shan, 11/2011 - 10/2014

Phase transformations and microstructure evolution of solid-state materials are largely controlled by long-range diffusion of alloying elements as well as structural vacancies. In the presence of traps, the diffusion characteristic of all alloying constituents can be severely altered, thus heavily impacting on the characteristics and kinetics of all diffusional microstructural processes.

One of the goals of the project is to model the impact of atomic traps on long-range diffusion, precipitation and phase transformations and to implement these procedures into the software MatCalc.

The expected result of the project are:

 

  • A new theory for interstitial diffusion. The main output will be a general theory for interstitial diffusion in multicomponent systems with manifold traps.
  • Advanced software for microstructural evolution – MatCalc. New models for evolution of systems under surface treatment (nitro-carburizing) within the theorectical framework for interstitial diffusion with simultaneous precipitation will be developed and implemented into the software package MatCalc.
  • Deeper understanding of the physical mechanisms governing the austenite to ferrite transformation in steel, as well as the influence of alloying elements on this transformation.
Sketch of the methodology when coupling diffusion and precipitation

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Fig. 1: Sketch of the methodology when coupling diffusion and precipitation

Collaboration

We aspire toward these goals together with the scientific groups from Institute of Mechanics (University of Leoben), Institute of Physics of Materials (Academy of Science of the Czech Republic), Institute for Materials Science and Welding (Technical University of Graz)  and Materials Center Leoben . Our work is funded by the Austrian Science Fund (FWF) being a part of the project COMET_A1-9.

Simon Großeiber, 08/2011 - 07/2014

In the course of continuous casting of steel, the slab is subjected to mechanical and thermal stresses which may cause intergranular crack formation due to reduced ductility typically between 700 and 1000°C (Second ductility minimum, Figure 1). The reduction of area at fracture determined from hot tensile tests prevails for the evaluation of the susceptibility to crack formation. Samples taken from the slab are austenitized and cooled to test temperature for deformation.

The loss of ductility is attributed to microstructural changes at the austenite grain boundaries. The formation of thin ferrite films as well as precipitation at the austenite grain boundaries can strongly deteriorate hot ductility. Ferrite exhibits lower strength than austenite at the considered temperatures, thus favouring intergranular crack formation (Figure 2). In the absence of ferrite, i.e. at higher temperatures, fine grain boundary precipitation may hinder grain boundary movement, giving rise to intergranular crack formation in the austenite single phase region.

The objective of this project is to assess the deformation and damage mechanisms within the second ductility minimum of steel, depending on influencing variables such as strain rate, chemical composition, segregation behaviour and grain size.

Ductility of steel as a function of temperature (schematic)

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Fig. 1: Ductility of steel as a function of temperature (schematic); B.G. Thomas, J.K. Brimacombe, I.V.Samarasekera The Formation of Panel Cracks in Steel Ingots: A State-of-the-Art Review. ISS Transactions, 1986, Vol. 7,pp 7-19.

SEM and tomography images of samples strained to failure at 3x10-4/s at the temperature of minimum ductility

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Fig. 2: SEM and tomography images of samples strained to failure at 3x10-4/s at the temperature of minimum ductility.

Niko Grosse-Heilmann, 01/2011 - 12/2013

Quenching and Partitioning was introduced in 2003 as novel heat treatment by J.G. Speer and D. K. Matlock and B.C. De Cooman and J.G. Schroth [1]. As shown in Figure 1, the quenching and partitioning heat treatment creates a three-phase microstructure, consisting of low carbon martensite m1, high carbon martensite m2 and retained austenite γ.

The schematic Q&P Heat Treatment

Figure 1: The schematic Q&P Heat Treatment [2]

The Q&P heat treatment can be divided into two steps. During the quenching step the steel is fully austenized and then quenched to a temperature between the martensite start and martensite finish point. Due to the suppressed cementite precipitation due to the high silicon content, the carbon diffuses from super-saturated martensite m1 to austenite during the subsequent partitioning step. Because of the austenite stabilising effect of carbon, the martensite finish temperature of the carbon-enriched austenite is decreased below room temperature. Hence, after final quenching to room temperature, high carbon martensite m2 is formed and carbon-enriched austenite remains.

Aim of the project is to analyse carbon diffusion from martensite to austenite and carbide precipitation during partitioning to model and simulate the related stability of retained austenite in high strength low alloyed steels.

References

[1] Speer, J.; Matlock, D. K.; Cooman, B. D. & Schroth, J. (2003), 'Carbon partitioning into austenite after martensite transformation', Acta Materialia 51(9), 2611-2622.

[2] Speer, J.; Streicher, A.; Matlock, D.; Rizzo, F. & Krauss, G.Damm, E., ed.,  (2003), Austenite Formation and Decomposition, Merwin, M., chapter Quenching and partitioning: a fundamentally new process to create high strength TRIP sheet microstructures, pp. 505-522.

 

Alice Redermeier, 10/2010 - 09/2013

Nowadays, refractory elements are added to improve the performance of Ni-base superalloys. But with increasing amount of refractory elements topologically close-packed (TCP) phases form. The precipitation of the TCP phases deplete the matrix of solid strengthening elements and hence affects deleteriously the creep rupture life of the superalloys.
In this project, we describe the TCP phases in multi-component Ni-base superalloys within the framework of the CALPHAD-approach. We assess the thermodynamic parameters using experimental data and ab initio calculations. In a further step we develop diffusional mobility databases to get information on the influence of various heat treatments on the material properties.

In situ observation of TCP precipitation

FIGURE 1 (In situ observation of TCP precipitation isothermally exposed at 950°C for Ni-base superalloy without Ruthenium at (a) 0 min, (b) 15 min, (c) 30 min, (d) 45 min, and for this alloy with 3 wt.% Ruthenium at (e) 0 min, (f) 15 min, (g) 30 min, and (h) 45 min. Figure taken from [REF 1].)

In situ observation of TCP precipitation

FIGURE 2 (In situ observation of TCP precipitation isothermally exposed at 1050°C for Ni-base superalloy without Ruthenium at (a) 0 min, (b) 15 min, (c) 30 min, (d) 45 min, and for this alloy with 3 wt.% Ruthenium at (e) 0 min, (f) 15 min, (g) 30 min, and (h) 45 min. Figure taken from [REF 1].)
References:
1: Gao S., Zhou Y., Li C., Cui J., Liu Z., Jin T. “In situ investigation on the precipitation of topologically close-packed phase in Ni-base single crystal superalloy”, Journal of Alloys and Compounds 610 (2014) 589-593.

Beatrix Adjassoho, 10/2010 - 09/2013

The process of surface densification by means of a machine hammer peening is a technological option, which provides new possibilities in different aspects of surface finishing and new design abilities for tribologically relevant surface functions. In this context, two functional effects have to be considered. This is namely the improvement in surface quality and the optimization of interfaces in tribological systems regarding the mechanical and dynamical properties of the surface. Machine hammer peening is a cold working process, in which a striker of the actuator system is conducted along the surface of the workpiece, while modifying the properties of the surface in a specific manner.

Objective of this project is to investigate the influence of the machine hammer peening process on the material surface properties. Therefore, the mechanical modification of the surface is analyzed experimentally and by means of simulation software, i.e. a finite element code. The work packages of this project consist mainly of following two parts: 

A)   Experimental characterization 

In this part of the project, the effects of the machine hammer peening process on the materials structure and the mechanical-technological material properties will be characterized experimentally.   

  • Structure characterization: A very important point in the structure characterizing on machine hammer peening is the study of the microstructure development. This shall be made first with the classical light optical materialography. This includes structure interpretation, micro - and nano - hardness measurement, and eventually an additional tomography.  
  • Mechanical – technological properties: The objective of the procedures is to analyse the property change through machine hammer peening. The material properties to be mainly studied are the surface hardness, the yield and tensile strength, the fatigue strength as well as tribological properties.

B)    FEM Simulation

The FEM (finite element method) – Simulation of the machine hammer peening process will be made with the Software package ANSYS. Intention of the FEM simulation is mainly to define the residual stress state on the plastically modified surface. The focus of the present WP includes the following points as content:

  • Determination of the material properties for the investigating material model from the literature or the experiment (associated with additional effort).
  • Development of a calculation pattern with one quasi-static plastic material model and realization of a simulation study. This simulation is state-of-art and should be considered as reference for further studies.
  • Development of a calculation pattern with a dynamic plastically material model and realization of a simulation study.  With this simulation study the quality of the calculation results, using a dynamic material model, should be analyzed compared to the results of the reference model.
  • Experimental investigations for determining the residual stress state on the plastically modified surface, in order to verify the simulations results.  

Walter Mayer, 09/2010 - 08/2014

Austenite directly transforms in hard but brittle martensite with an enormous defect density during fast cooling from elevated temperatures. The toughness of freshly quenched martensite has to be improved by heat treatments for industrial applications. A model for aging (0th stage of tempering) and tempering martensite, which accounts for trapping of C atoms at dislocations, is introduced. The interaction of interstitial atoms with the defect substructure is the key factor in determining the extent and morphology of precipitation during tempering. During quenching and tempering, a dynamic competition for the C atoms between these traps and carbide precipitation persists. These metastable early stages of precipitates are called clusters in literature and transform to transition carbides in the first stage of tempering. The third stage of tempering describes the formation of stable carbides (Cementite, M7C3, M23C6…) - see figure.

The picture shows the third stage of tempering and describes the formation of stable carbides (cementite, M7C3, M23C6...)

We plan to introduce a new and general model, which can reproduce the solubility of C in relation to the dislocation density, the precipitation of a cluster phase and the transformation of them to carbides. One application of this model is the numerical treatment of martensite tempering using the thermo-kinetic software MatCalc  (https://www.matcalc.at/).

Wu Jun, 07/2010 - 06/2013

he microstructure evolution in heat-treatable Al-alloys is characterized by a complex sequence of precipitation processes. The individual peaks identified in a differential scanning calorimetry (DSC) and instantaneous coefficient thermal expansions(CTE) of dilatometry experiments can be correlated to the nucleation, growth and dissolution of certain types of precipitates. Simultaneously, these data can also be obtained by thermo-kinetic simulation based on models implemented and they can be verified by transmission electron microscopy investigations.

My main task is to simulate the differential calorimetry and dilatometry curves of heat treatable al alloys (2xxx, 6xxx, 7xxx) , and use experimental technology( ie. DSC, TEM ) to clarify the results.

DSC simulation and experimental results

Fig 1: DSC simulation and experimental results

Good match between CTE  and DSC curves

Fig 2: Good match between CTE  and DSC curves

Kerem Ilyas Öksüz, 03/2010 - 02/2014

In technical 6xxx aluminum alloys, apart from intentional alloying additions, transition metals such as Fe, Mn and Cr, etc. are always present. Even small amounts of these impurities cause the formation of new phases. During casting of 6xxx aluminum alloys, depending on the exact chemical composition and cooling rate, a wide variety of intermetallic phases are formed between the aluminum dendrites. In production of large sized ingots, macro-segregation is one of the major problems that occur during the casting process. Large particles or extreme segregations can cause areas with low melting temperature that may lead to tearing during rolling or extrusion. The distribution of fine and thermally stable dispersoids has a strong effect on the recovery, recrystallization and grain growth processes. The dispersoids may even act as nucleation sites for the precipitation of the strengthening precipitates. All these facts imply that this complexity demands deep understanding and suitable simulation tools to predict the evolution of dispersoids and intermetallic phases during the manufacturing process.

[Translate to English:] Hauptproduktionsschritte bei der Verarbeitung von Aluminiumlegierungen

Figure 1: Main production steps during processing of aluminum alloys

It is planned to develop simulation methods and tools to be able to optimize not only the alloy composition but also the process parameters for production of 6xxx, especially 6061 alloys. Uniformity in distribution of the fine dispersoids and optimization of production parameters in different process steps to get the desired mechanical properties of the end-product is one of our prime goals. A huge part of the project covers precise experimental investigations concerning microstructural evolution of 6061 alloys during manufacturing process steps. The obtained information will serve as input parameter for the development and parameterization of the model.

Peter Lang, 05/2010 - 09/2014

Aluminium alloys are an important group of alloys; especially the Al-Mg-Si group (6xxx series). This kind of alloy provides a high degree for precipitation hardening and it is often used as body sheet in automotive industry due to its bake-hardening potential. Numerous studies of the precipitation sequence of these alloys accompany the industrial development, showing a complex sequence of metastable precipitate types.

A combination of “state-of-the-art” techniques is used to describe the structure and properties of precipitates in a typical 6xxx aluminium alloy from the atomic to the macroscopic scale. First principle methods, such as Density Functional Theory (DFT), are combined with Cluster Expansion (CE) calculations, Monte Carlo (MC) Simulations to study precipitation on the microscopic scale. On the continuums scale, a macroscopic description of the precipitation process is performed with the software package MatCalc, thus bridging from angstroms to microns, and from nanoseconds to hours.

Quenching a solid solution of an Al-Mg-Si alloy from elevated temperatures into a two-phase region leads to formation of coherent precipitates. The very first stages of clustering and precipitation of the so called Guinier-Preston zones (GP-zones) that form from solid solution are investigated using first-principles calculations. Based on density functional theory, as implemented in the Vienna ab initio simulation package (VASP), the total energy of various atomic arrangements of up to 128 atoms is calculated. These data are fed into the cluster expansion method as realized in the Universial Cluster Expansion code UNCLE, providing total energy descriptions of a larger number of atoms up to several ten millions. With the UNCLE code, as well as the Monte Carlo framework that is implemented in the MatCalc software, clustering of atoms in the Al rich matrix will be studied on a three-dimensional FCC lattice.

The microscopic investigations will provide basic information as input data for the continuums modelling also done in MatCalc. An example of these simulations, where the precipitation sequence observed in 6xxx alloys is first modelled as a sequence of nucleating, growing and dissolving precipitates. From these results, characteristic materials properties, such as the specific heat, can be derived and compared with experiment, where we observe encouraging agreement, bearing in mind the complexity of the simulations. Once having calibrated the simulations to experimental data, different compositions and different thermo-mechanical treatments can be used in the simulations, thus having great potential for aiding to industrial alloy and process development.

Sabine Zamberger, 10/2009 - 02/2016

The idea to use boron to increase hardenability of mild and low alloyed steels is facing a long history; first trials date back to the beginning of the 20th century. The peculiarity of this alloying element is that minute quantities are sufficient to show a significant hardenability effect, which offers the opportunity to reduce the amount of conventional and more expensive alloying elements like Mo, Cr, and Ni etc. It is assumed that, during the heat treatment, boron atoms segregate to the austenite grain boundaries. As a consequence, during the cooling process, the nucleation of ferrite at the grain boundaries is delayed. However, there are still open questions, as for example the lattice position of boron in ferrite, which mechanism, equilibrium or non‑equilibrium segregation, is the underlying one for the hardenability enhancement, or precipitation kinetics of boron alloyed steels. One reason is that, due to the low content of boron in steel, detection and quantification of boron enriched zones are rather difficult.

Therefore, one part of the project is focused on the evaluation of characterisation methods to find out where boron is located and in which condition, either as segregant or precipitate. The applied methods are light optical microscopy, scanning electron microscopy plus EDX‑analysis, electron probe microanalysis, time of flight secondary ion mass spectroscopy, differential scanning calorimetry, transmission electron microscopy and atom probe field ion microscope. The other part of the project deals with the numerical simulation of the boron behaviour as a function of time and temperature.

ToF-SIMS 3D reconstruction of MnS (blue) surrounded by BN (red+green)

Figure 1: ToF-SIMS 3D reconstruction of MnS (blue) surrounded by BN (red+green) in a not Ti-stabilized boron alloyed steel.

Mohammad Reza Ahmadi, 11/2009 - 08/2013

Precipitation hardening is a one of four mechanisms, which improve the mechanical strength in materials. In this mechanism, precipitates act as small barriers, which inhibit easy dislocation movement to increase yield strength.

Precipitation hardening is commonly performed in three steps:

  1. Solution heat treatment: Heating into single phase solubility region to establish a homogeneous solid solution.
  2. Quenching: Quenching form single phase region into the low temperature to form a supersaturated solid solution (SSSS).
  3. Aging: Heating up to increased temperature to facilitate diffusive process where we have optimum condition for nucleation and growth.

At the early stage of aging, precipitates are small and coherent to the lattice (coherent particles) but after a while they will grow more and more until they lose their coherency and become incoherent particles.

Dislocations react in two different ways with coherent and non-coherent precipitates:

1) When dislocations interact with a coherent precipitate, they can pass through the precipitate, because atomic lattice continuity remains intact at the precipitate – matrix interface. For a quantitative description of the dislocation – particle interaction, we have to consider the energy changes in the dislocation as well as the properties of the precipitate. The type of precipitates where dislocations can pass through the precipitate volume are called soft or “weak precipitates”. The corresponding strengthening mechanism are categorized into:

A. Chemical strengthening
B. Coherency strengthening
C. Modulus hardening
D. Order strengthening
E. Stacking-Fault strengthening

2)  If dislocations interact with non-coherent precipitates, they cannot traverse through them. Because atomic continuity is missed at precipitate interface. In this case precipitates will be bypassed by dislocations under Orowan mechanism and make a loop around precipitates. This is the reason that these precipitates are called hard or “strong precipitates”.

Goal of the project is to calculate and predict strengthening due to precipitation hardening considering all dislocation interaction mechanisms at different stages of hardening.

Peter Lang, 05/2009 - 04/2010

Overall goal is to simulate the precipitation sequence of the Aluminium alloy class 6xxx (Al-Mg-Si system) with the software package MatCalc. Based on thermodynamic, kinetic and physical database the sequence can be reproduced well according to experimental data.

Process steps of an usual heat treatment:

After solution annealing the aluminium alloy is not cooled slowly but quenched quickly in the second step of the precipitation hardening process (Figure 1).

When this is done, all Magnesium and Silicon atoms in the aluminium solid solution are forced to remain dissolved. Due to the rapid quenching they do not have time for the diffusion processes which would be necessary to form precipitations. This processes occurring during quenching can no longer be described in the phase diagram Al-Mg-Si, since they take place in equilibrium no longer. Further on the supersaturated solid solution builds up metastable phases, which can be considered as intermediates until the stable thermodynamic situation is reached. During process related storage at room temperature clusters are the initial state for the formation of strength-enhancing particles, which have different structure and size depending on the following heat treatment.

The simulation of the precipitation sequence, starts with the supersaturated solid solution, includes the metastable and the stable phase Mg2Si, is calculated, compared and optimized to data from literature.

Results are in good agreement with experimental results and data from literature, what can be shown for number densities and radii as well for the temperature regions of precipitates for continuous and isothermal heat treatments.

Erwin Povoden-Karadeniz, 01/2009 - 12/2013

Christian Doppler Laboratory Early Stages of Precipitation

Knowledge of thermodynamics of matrix and precipitating phases are a pre-requisite for kinetic simulations of precipitation. The volume free energy change, as well as the enthalpy of solution of precipitate in the modeling of interfacial energy [1], contribute an essential part of the free energy change due to nucleus formation [2]. These properties can be evaluated from CALPHAD-type [3] free energies. These are obtained by thermodynamic assessment of all available thermo-physical and phase diagram data.

In the framework of the CALPHAD-approach, multi-component thermodynamic databases of various alloy systems (Fe-base, Ni-base, Al-base, Ti-base, Mo-base) and diffusional mobility databases are developed, which are used for thermo-kinetic simulations with the MatCalc [4-8] software package, in order to predict materials properties after various heat treatments.

Project fields

In the following examples of modeling and simulation in different project parts are given:

Computational thermodynamics-based simulation of precipitate evolution in Fe-Co-Mo with Si-impurities (01/2009-10/2013)

Solution-treated and quenched Fe-25 Co-15 Mo-alloys (wt.%) with Si addition show remarkable increase in hardness during aging at elevated temperature [9-11]. The observed precipitation strengthening potential has been attributed to finely dispersed semi-coherent µ-phase particles with a stoichiometry of (Co,Fe)7Mo6. Modulated microstructure of Mo-enriched and -depleted zones develop prior to µ-phase formation during aging [11-13]. Thermo-kinetic simulations propose that during aging, the Mo-rich microstructures form by means of nucleation and growth of metastable bcc-precipitates For the thermokinetic analysis, we evaluate and utilize theoretically predicted nucleus compositions of bcc-precipitates from the minimum nucleation barrier concept.

 Assessed Fe-Co-Mo phase diagram (a) compared with experiments [9] (b) at 1200°C using MatCalc database mc_fe_v2.011

Figure A1. Assessed Fe-Co-Mo phase diagram (a) compared with experiments [9] (b) at 1200°C using MatCalc database mc_fe_v2.011. The µ-phase is an important precipitate in C-free precipitation-hardened Fe-Co-Mo tool steels. For the phase diagram mapping Thermocalc [10] is used.

 Simulated heat flow of Fe-25Co-15Mo

Figure A2. Simulated heat flow of Fe-25Co-15Mo (wt.%) compared with experimental differential scanning calorimetry (DSC) results [11]. Peak I refers to precipitation of metastable pre-µ bcc, and Peak II refers to mu-phase precipitating on pre-structures. Understanding of precipitation evolution assists materials optimization regarding composition and heat treatments.

 

 

 

Simulation of precipitation kinetics and precipitation strengthening of B2-precipitates in martensitic PH 13-8 Mo Steel (01/2009-12/2011)

The strength of quenched Co-free martensitic PH 13-8 Mo steel increases significantly during isothermal aging at 575°C due to precipitation of nanometer-sized particles [17]. The evolution of these ordered B2 type precipitates is simulated by thermo-kinetic computation. The composition of the B2-nuclei is determined from minimization of the critical nucleation free energy (minimum nucleation barrier concept).

 Most likely nucleus composition (marked with x) of Al-Ni B2-precipitates in precipitation-hardened maraging steel PH 13-8 Mo

Figure B1. Most likely nucleus composition (marked with x) of Al-Ni B2-precipitates in precipitation-hardened maraging steel PH 13-8 Mo simulated by minimum energy barrier concept.

Simulated precipitate properties of B2 in PH 13-8 Mo during isothermal aging at 575°C and experimental results (symbols with error bars) [17]. Small B2-precipitates (a) with a high number density (b) are predicted which increase the Yield strength of the material

Figure B2. Simulated precipitate properties of B2 in PH 13-8 Mo during isothermal aging at 575°C and experimental results (symbols with error bars) [17]. Small B2-precipitates (a) with a high number density (b) are predicted which increase the Yield strength of the material.

CALPHAD modeling of metastable phases in the Al–alloys and applications to thermo-kinetic precipitation simulations (01/2010 to 06/2013)

Metastable precipitates govern the mechanical properties of hardenable Al-alloys. For computational precipitation simulation we combine assessed thermodynamic parameters of metastable precipitate phases, compiled diffusional mobility data and predictive physical models for the interfacial energy and the nucleation and growth of precipitates [1,2,5-7]. Predictive precipitation kinetics simulation delivers approximations of thermodynamic properties that would otherwise require time-consuming computational techniques, e.g. based on density functional theory.

Enthalpies of formation – Entropies of formation plot of metastable phases and stable Mg2Si in Al-Mg-Si alloy (AA6016) at room temperature

Figure C1. Enthalpies of formation – Entropies of formation plot of metastable phases and stable Mg2Si in Al-Mg-Si alloy (AA6016) at room temperature. Knowledge of thermodynamics of metastable phases in Al-alloys is essential for understanding of precipitate evolution during various technological heat treatments.

Simulated precipitate fractions in Al-Mg-Si alloy

Figure C2. Simulated precipitate fractions in Al-Mg-Si alloy (AA6016) during continuous heating after solution treatment and quenching.

Thermodynamic modeling and precipitation simulation in Mo-base refractory alloys (started 01/2010)

We test the role of precipitates for strengthening of Mo-Hf-C refractory alloys in thermo-kinetic precipitation simulations based on CALPHAD assessment of thermodynamic and diffusion mobility parameters. 

Assessed Mo-Hf-C equilibrium phase diagram (a) at the Mo-corner compared with experiments [18] (b) using mc_mo_v1.002

Figure D1. Assessed Mo-Hf-C equilibrium phase diagram (a) at the Mo-corner compared with experiments [18] (b) using mc_mo_v1.002. This is the basis for thermo-kinetic precipitation simulations of MHC refractory alloys. Mapping of isothermal equilibrium sections is calculated using Thermocalc.

Thermodynamic Ni-Database development for applications in thermo-kinetic precipitation simulations in multi-component Ni-base superalloys (started 01/2010)

A thermodynamic Ni-database is developed for applications in a variety of multi-component Ni-base superalloys.

Calculated thermodynamic solvi of (Ni,Co)3(Al,Ti,X)

Figure E1. Calculated thermodynamic solvi of (Ni,Co)3(Al,Ti,X) gamma´ phase in various Ni-base alloys (Multi-component system Ni-Al-Ti-Co-Cr-Fe-Mo-Nb-W-Ta-Re). The mean difference between computation and experimental data is below 30°C. Computational thermodynamics using the developed Ni-database allows for predictions on application limitations (stability of hardening gamma´ phase) of new alloy compositions. 

Equilibrium phase fractions in single-crystal Ni-base superalloy PWA1480 with mc_ni_v2.004

Figure E2. Equilibrium phase fractions in single-crystal Ni-base superalloy PWA1480 with mc_ni_v2.004. From the equilibrium phase fractions one can decide proper solution treatment before aging.

Simulated multi-modal precipitate distribution after cooling

Figure E3. Simulated multi-modal precipitate distribution after cooling with 0.1°C/s in single-crystal Ni-base alloy PWA1480. Predictions of precipitate distributions assist alloy design for aeroengine applications.

 

 

 

 

Thermodynamic modeling and precipitation simulation in stainless steel (started 05/2012)

In the framework of mc_fe database development, one focus are intermetallic topologically close-packed structures (TCP). These phases, such as widely-researched sigma phase, are detrimental for long-term functionality of stainless steels. In order to predict limits of applicability of these materials, fundamental knowledge of stabilities of TPC structures is required at first. Then we use assessed CALPHAD descriptions in thermo-kinetic computations of time-temperature-transformation (TTP) diagrams.

Simulated time-temperature-precipitation (TTP) diagram

Figure F1. Simulated time-temperature-precipitation (TTP) diagram of Ni-free Fe-Cr-Mn-N stainless steel. Experimental data [19] are included as symbols. The simulation allows for predicitions of harmful Cr2N and intermetallic topologically close-packed (TCP) phases sigma and chi.

 

 

 

Thermodynamics of Ti-Ni shape memory alloys (06/2012 to 05/2013)

Shape memory alloys are martensitic metals that “remember” the original shape of their parent modification under specific conditions of temperature and mechanical loading/unloading. Ti-50Ni to Ti-55Ni (at%) is the pioneer of shape memory alloys (SMA) and a key system for studying phase transformations and precipitate evolution in shape memory alloys. The thermodynamics of the parent bcc-structured, ordered B2 phase and the monoclinic martensitic B19’ phase are well understood. In order to improve shape memory and mechanical properties, SMA are usually aged at temperatures where precipitation of second phases from the supersaturated B2-ordered matrix occurs. These phases are Ti3Ni4, Ti2Ni3 and the thermodynamically stable TiNi3 (h-) phase. In particular, Ti3Ni4 plays an important role for martensite formation. The martensite start temperature, Ms, is strongly influenced by changes of plastic deformation limits associated with precipitation hardening and the change of the matrix composition due to precipitation [20-27]. The thermodynamics of metastable Ti3Ni4 and Ti2Ni3 phases is assessed from first-principles analysis and metastable phase diagram data.

Calculated metastable phase diagrams of binary Ti-Ni shape memory alloy

Figure G1. Calculated metastable phase diagrams of binary Ti-Ni shape memory alloy (SMA) system using MatCalc database mc_SMA_v1.001. Equilibrium TiNi3 and metastable Ti2Ni3 are suspended from the calculation to show the metastability of Ti3Ni4, the most important hardening phase in Ti-Ni SMA. For the phase diagram mapping Thermocalc is used.

 

 

 

 

Thermodynamic database development for computations in Ti-alloys and Ti-aluminides (started 06/2012)

This is the most recent project part, where particular interest lies in the theoretic understanding of transformation mechanisms between ordered and disordered structures in Ti-Aluminide materials.

Calculated equilibrium phase fractions (a) in classical Ti3Al-Nb alloy Ti-25Al-25Nb (wt.%) showing thermodynamic stabilities of Ti-aluminides TiAl and Ti3Al and ordered and disordered Ti-alloy phases (HCP_A3, BCC_B2). Fractions of elements in each sublattice of the BCC_B2 phase (b) show ordering up to 1425°C

Figure H1. Calculated equilibrium phase fractions (a) in classical Ti3Al-Nb alloy Ti-25Al-25Nb (wt.%) showing thermodynamic stabilities of Ti-aluminides TiAl and Ti3Al and ordered and disordered Ti-alloy phases (HCP_A3, BCC_B2). Fractions of elements in each sublattice of the BCC_B2 phase (b) show ordering up to 1425°C. Above this temperature, “BCC_B2” is fully disordered bcc-structured.

Recent Publications

Simulation of precipitate evolution in Fe-25Co-15Mo with Si addition based on computational thermodynamics
E. Povoden-Karadeniz, E. Eidenberger, P. Lang, G. Stechauner, H. Leitner, E. Kozeschnik
J. Alloys Cmpd.; akzeptiert.

Thermodynamics of Ti–Ni shape memory alloys , opens an external URL in a new window
E. Povoden-Karadeniz, D.C. Cirstea, P. Lang, T. Wojcik, E. Kozeschnik KALPHAD 2013; 41:128–139. CALPHAD-Modellierung metastabiler Phasen im Al-Mg-Si-System E. Povoden-Karadeniz, P. Lang, P. Warczok, A. Falahati, W. Jun, E. Kozeschnik
CALPHAD

Thermodynamics-Integrated Simulation of Precipitate Evolution in Al-Mg-Si Alloys , opens an external URL in a new window
E. Povoden-Karadeniz, P. Lang, K.I. Öksüz, W. Jun, S. Rafiezadeh, A. Falahati, E. Kozeschnik
Materials Science Forum 2013; 765:476.

Simulation of Precipitation Kinetics and Precipitation Strengthening of B2-precipitates in Martensitic PH 13-8 Mo Steel
E. Povoden-Karadeniz, E. Kozeschnik
ISIJ International 2012; 52(4):610-615.

Thermodynamic modeling of La2O3-SrO-Mn2O3-Cr2O3 for solid oxide fuel cell applications , opens an external URL in a new window
E. Povoden-Karadeniz, M. Chen, T. Ivas, A.N. Grundy, L. J. Gauckler
Journal of Materials Research 2012; 27(15):1915-1926.

Databases

overview databases

References

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[3]     N. Saunders, A.P. Miodownik, Calphad Calculation of Phase diagrams, Pergamon Materials Series, Vol. 1. Elsevier Science Ltd., 1998, 479 p.

[4]     E. Kozeschnik, B. Buchmayer, MatCalc – A simulation tool for multicomponent thermodynamics, diffusion and phase transformations, in: Cerjak H, Bhadeshia HKDH (Eds.), Mathematical Modelling of Weld Phenomena 5 book 738, IOM Communications, London (2001).

[5]     J. Svoboda, F.D. Fischer, P. Fratzl, E. Kozeschnik, Mater. Sci. Eng. A 385 (2004) 166-174.

[6]     J. Svoboda, F.D. Fischer, P. Fratzl, E. Kozeschnik, Mater. Sci. Eng. A 385 (2004) 175-165.

[7]     E. Kozeschnik, J. Svoboda, F.D. Fischer, CALPHAD 28 (2004) 379-382.

[8]     https://www.matcalc.at/, opens an external URL in a new window. Author: Kozeschnik E. Last date of access: 2013-10-23; current MatCalc version is 5.53.0013.

[9]     W. Köster, W. Tonn, Arch. Eisenhuttenwes. 12 (1932) 627-630.

[10] H. Leitner H, M. Schober, H. Clemens, D. Caliskanoglu, F. Danoix, J. Mater. Res. 99 (2008) 367-374.

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[12] E. Eidenberger, M. Schober, H. Leitner, P. Staron, H. Clemens, Intermetallics 18 (2010) 2128-2135.

[13] E. Eidenberger, Doctoral Thesis. University of Leoben, 2010.

[14] D.K. Das, S.P. Rideout, P.A. Beck, Trans. AIME 4 (1952) 1071-1075.

[15] J.O. Andersson, T. Helander, L. Höglund, P.F. Shi, B. Sundman, Calphad (2002) 26, 273-312.

[16] E. Eidenberger, M. Schober, E. Stergar, H. Leitner, P. Staron, H. Clemens, Metal. Mater. Trans. A 41 (2010) 1230-1234.

[17] R. Schnitzer, S. Zinner, H. Leitner, Scr. Mater. 62 (2010) 286.

[18] V.N. Eremenko, S.V. Shabanova, T.Ya. Velikanova, Sov. Powder Metall. Metal. Ceram. 16 (1977) 772-777.

[19] T.-H. Lee, S.-J. Kim, S. Takaki, Metal. Mater. Trans. A 37 (2006) 3445-3454.

[20] K. Otsuka and X. Ren, Prog. Mater. Sci., 50 (2005) 511-678.

[21] J. Khalil-Allafi, X. Ren, G. Eggeler, Acta Mater. 50 (2002) 793-803.

[22] J. Khalil-Allafi, G. Eggeler, W.W. Schmahl, D. Sheptyakov, Mater. Sci. Eng. A 438-440 (2006) 593-596.

[23] J. Khalil-Allafi, A. Dloughy, G. Eggerer, Acta Mater. 50 (2002) 4255-4274.

[24] Y. Zheng, F. Jiang, L. Li, H. Yang, Y. Liu, Acta Mater. 56 (2008) 736-745.

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[26] S. Cao, S. Pourbabak, D. Schryvers, Scripta Mater. 66 (2012) 650-653.

[27] E. Akin, Doctoral Thesis. Texas A&M University, 2010.

Jakob Six, 07/2008 - 06/12

The temperaturedepending ductility of steel is related amongst others to the microstructure changes and modifications. During continuous casting in the secundary cooling zone, in which the solidificated skinlayer is exposed to high thermomechanical and mechanical loads caused by intensive watercooling and deflection rolls (=> crack formation, crack growth). 

The ductility variations are shown in figure 1: Liquid and solid phases coexist at high temperatures, no mechanical loads can be applied. Between 600°C and 1200°C two different effects are distinguished:

  • precipitations at austenite grainboundaries
  • ferrite filmformation at austenite grainboundaries
Temperature dependend ductility (schematically)

Figure 1: Temperature dependend ductility (schematically)

The precipitations reduce dislocation movement and gliding of austenite grainboundaries (areas D and B). Thin ferrite films are formed at austenite grainboundaries at lower temperatures (below Ar3, area E). Because of the different mechanical properties of austenite and ferrite, the whole deformation is concentrated to the softer ferrite film. Localized deformation forms pores and cracks. At decreasing temperatures, the ferrite film growth and the deformation concentration decreases (=> increasing ductility). Finally, precipitations in ferrite films decrease the ductility (area F).

The experimental method is focused on observation of the II. minimum of ductility. The mechanism responsible for the variation in ductility regarding transformation temperature Ar3 will be concluded. Methods like hot compression / tensile tests with Gleeble (figure 2), Dilatometer, metallography (figure 3), simulations (deformation, microstructure evolution) are complementary used.

Thermo-mechanical treatment

Figure 2: Thermo-mechanical treatment.

[Translate to English:] Metallographisches Schliffbild einer wärmebehandelten Probe

Figure 3: metallography of a heat treated sample.

Jaroslav Zenisek, 01/2008 - 06/2011

My work can be divided into parts: simulations and experiments. Both have something to do with the formation of carbides in steel. My current project is focused on processes which occur at the surface of steel during carburizing. When a steel workpiece is placed to a carburizing atmosphere, the chemical reactions at the surface lead to production of free carbon atoms which may diffuse into the workpiece. During diffusion, some of those carbon atoms may react with the matrix atoms of
the steel which gives rise to the formation of carbides. Our aim is to set up our experiments so that we can observe simultaneous inward carbon
diffusion accompanied with formation of carbides. As an introduction, I present one result of our carburizing treatment in Figure 1. One can clearly distinguish between the structures in the boundary region and in the center of the specimen which is the effect of carburizing. The following (simulation) part briefly describes my other recent problems related to the nucleation of carbide precipitates.

A) Modeling part

The main topic is the study of precipitation in Fe-Cr-C system by means of computer simulations. This means that I create a computer representation of crystalline lattice (BCC), assign each lattice site with Fe or Cr by random way (where the total numbers of Fe and Cr obey the defined atomic concentrations), and evaluate the local conditions for nucleation (nucleation barrier) which change due to the random composition fluctuations. Consequently, the information about the spatial distribution of the nucleation barriers is applied in the simulation of nucleation and growth of precipitates. The results are contrasted to those calculated for perfectly homogeneous material (no random fluctuations in chemical composition).

Currently, I am trying to understand the role of the structural change (BCC->CEMENTITE) on the nucleation barrier. I am dealing with the details of the structural change – sequence of atomic transitions necessary to accommodate the new positions in the precipitating cementite phase. Next, I want to determine if there is a minimum size needed for a cementite cluster and if there is an additional barrier required to accomplish the necessary atomic transfers during transformation.

B) Experimental part

We have built our carburizing device and carburizing experiments are underway. In the current work, we want to see how the inward carbon diffusion during carburizing is affected by the simultaneous formation of carbides. Therefore, we experiment with different material compositions and experimental conditions (temperature, properties of carburizing gas). Consequently, we analyze the carbon concentration profile, we are testing different methods (TOF-SIMS, GD-OES, LA-ICP-MS) and the material structure (light microscopy). Presence of carbides is checked by hardness tests. We plan to use also more advanced techniques for carbides analysis (3D-atom probe). The experimental output should be information about the evolution of density, size distribution of carbides, etc. On the other hand, formation of carbides during carburizing is going to be simulated by our software package MatCalc and finally both experimental and simulation results will be compared.

Rene Radis, 11/2007 - 10/2011

[Translate to English:] Berechnetes Zeit-Temperatur-Ausscheidungsdiagramm (TTP) für AlN in einem Stahl mit 0,05 % Al und 0,005 % N

Figure: Calculated time temperature precipitation (TTP) diagram for AlN in a steel containing 0.05 % Al and 0.005 % N

Microalloyed high strength low alloy steels (HSLA) owe their superior mechanical properties to a high density of second phase precipitates, e.g. nitrides, carbides or complex carbonitrides. For instance, the precipitation of fine dispersed VN during cooling enhances the strength of the steels in the range of 80-250 MPa. On the other hand there are microalloying elements like Aluminium which are known to precipitate predominantly at grain boundaries, especially in the austenitic phase field. Therefore these particles are made responsible for grain size control, which directly influences important mechanical properties like toughness, deep drawability or weldability.

For a better understanding of the precipitation behaviour of these carbides and nitrides as well as its effects on the mechanical properties of steel, it is essential to understand their precipitation kinetics. Therefore the present project deals with the numerical simulation of the precipitation process of these second phase particles as well as their kinetic interactions. Using the software package MatCalc it is possible to predict important microstructure parameters like phase fraction, particle size and number density. Thus, new heat treatments and/or alloys can be developed or existing ones can be optimized. Thereby time and costs, regarding the development of new alloys or optimization of the production process, can be reduced, which leads to a couple of advantages.

The figure shows exemplarily a calculated time-temperature-precipitation diagram for AlN in a typically microalloyed steel containing 0.05 Al and 0.005 N. The lines represent 5%, 50% and 95% of the equilibrium phase fraction at each temperature.

Farhan Imtiaz, 01/2007 - 12/2013

Researchers are working on austenite (γ) to ferrite (α) transformations for many decades. This is mainly due to the variety of different austenite decomposition products. There is considerable interest over the recent years to reduce the carbon content in order to increase the toughness (i.e. decrease the ductile to brittle transition temperature), ductility and weldability. Because of the enormous technological importance, austenite to ferrite transformation is one of the most studied phase transformation, but there is still lack of considerable understanding as for as the exact transformation mechanism is concerned. In this regard, a present project is aimed at systematic investigation of austenite to ferrite transformation mechanism in ultra-low to low carbon steels.

The schematic of the thermal cycle used for heat treatment of standard hollow and solid cylindrical samples is shown in figure 1. It consists of five segments i.e. heating rate defining segment (a to b), austenitization segment (b to c) and soaking at austenitization, quenching rate defining segment (c to d), isothermal holding segment  (d to e) and the final quenching segment (e to f). The isothermal holding temperatures are chosen between 890 and 660°C such that the transformation occurs either within the austenite/ferrite two-phase region or below in the ferrite one-phase field.

The resultant dilatation profile is recorded in state of the art high-speed quenching dilatometer by BÄHR (DIL 805A).

he dilatation profiles during austenite to ferrite transformations are showing slow and very fast transformation kinetics. It is one of the objectives to analyze these types of profiles.

The data obtained from these experiments will be used for plotting of experimental IT-TTT diagrams. The experimental investigations are complemented by computer simulations of the austenite to ferrite phase transformation using the software packages DICTRA and MatCalc.

 

Denijel Burzic, 01/2007 - 12/2013

a) Objective:

Overall goal of the project is to investigate the formation and removal of scale during manufacturing / processing of steels and the interaction with surface decarburization.

b) State-of-the-art and own starting point:

In the previous project MCL-M9, an investigation of the state-of-the-art of the devices for reheating, which operate at the industrial partner’s production sites, has been performed. An extensive literature survey on the interaction of oxidation and decarburization in general steels and, particularly, Si-alloyed steels for application in springs, has been carried out. Together with selected experiments in air as well as under furnace gas, basic understanding of the scale formation and surface decarburization could be obtained. In addition to the experiments, accompanying modelling has supported in drawing of conclusions for improvement of the production strategies and precautions in the case of production problems. Several new questions have come up in the previous project, which should be addressed in this consecutive project.

c) Approach / methodology:

The project will be performed in two working packages:

  • WP1: Experimental investigation of oxidation/scale formation and decarburization in air and furnace gas. The activities in this field will be carried out mainly at the research facilities of the scientific partners in Leoben (DTA in air and furnace gas) and Vienna (Gleeble and high-speed quenching dilatometer simulation of rolling / heat treatment process. Metallography and analytical characterization.
  • WP2: Improved modelling of oxidation/scale formation and decarburization based on computational thermodynamics and local microstructure evolution (segregation to grain boundaries and scale-metal interface, gb-diffusion and austenite/ferrite phase transformation)

d) Expected main results from the project:

The project shall continue to gather knowledge and understanding of the mechanisms which determine scale formation, scale removal and decarburization. This knowledge can directly enter into optimized manufacturing procedures at the facilities of the industrial partners.