Project A5: Alloy- and Processdesign based on Mechanism maps for high Mn-steels

Prof. Dr.-Ing. Bleck (Institut für Eisenhüttenkunde, RWTH Aachen)

 

 

A5



Mechanism maps

High-Mn austenitic steels with superior strain hardening behavior gain much research interest in the last decades [1-3]. During plastic deformation, the materials develop extraordinary service properties by effective deformation mechanisms, i.e. Transformation Induced Plasticity (TRIP) effect, Twinning Induced Plasticity (TWIP) effect and Microband Induced Plasticity (MBIP) effect [4-6]. The properties of high-Mn austenitic steels are strongly influenced by the stacking fault energy (SFE). The SFE controls the equilibrium distance between partial dislocations in fcc metals and by this the probability of the activation of the various deformation mechanism. Fig. 3.3.1 shows the 2D composition-dependent stacking fault energy (SFE) maps of high-Mn steels in Fe-Mn-C and Fe-Mn-Al-C alloy system. The calculation was based on a subregular solution thermodynamics model. The maps were developed by using the Scientific Group Thermodata Europe (SGTE) database [7]. The main assumption in the thermodynamic calculation was to take the SFE (Γ) as the required Gibbs free energy to form a ε martensite platelet with the thickness of two atomic layers within the dense planes [8, 9]. In the model, the stacking fault energy was calculated as follows [10]:

1
 
1b
 
 
 
2
 
3
 
3b
 
4
 
4b
 
3.3.1
Fig. 3.3.1: 2D composition-dependent maps of stacking fault energy (unit, mJ/m²) at 300 K
(a) 0 wt.% Al (b) 1.5 wt.% Al (c) 3 wt.% Al



 

 

The deformation mechanisms of high-Mn steels, i.e. TRIP, TWIP, MBIP, are predicted based on the thermodynamic calculation of SFE maps. Fig. 3.3.2 illustrates the different composition domains with regarding to the different deformation mechanisms. The kappa phase formation was calculated based on a Calphad approach.

3.3.2
Fig. 3.3.2: 3D composition-dependent SFE map of Fe-Mn-Al-C steel at 300 K

Fig. 3.3.2 plots the 3D domain where the kappa phase precipitates at its common annealing temperature at 873 K. As shown in the 3D composition-dependent SFE map in Fig. 3.3.2, with the increase of SFE, the deformation mechanism shifts from TRIP to TWIP and further to MBIP. With the addition of Al, kappa phase (Fe, Mn)3AlC precipitates in the Fe-Mn-Al-C steels. The planar glide accompanies the kappa phase formation with a much higher SFE value than that in TWIP and TRIP effect.

 

 

 

The 3D plot in Fig. 3.3.3 a) shows the iso-SFE surface at 20 mJ/m² (the approximate upper limit of TRIP mechanism [11]) and at 50 mJ/m² (the approximate upper limit of TWIP mechanism [12]). The calculation of the temperature effect on stacking fault energy was by using the Scientific Group Thermodata Europe (SGTE) database [7]. The parameters for the calculation of the temperature effect were extracted from the literatures [13, 14, 15]. The equations were used for calculation as follows:

5
 
6
 
7
 
8
 

The 3D plot in Fig. 3.3.3 b) shows the change of iso-SFE surface at 20 mJ/m² with the increase of temperature from 300 K to 600 K in the composition-dependent SFE map. The plot illustrates the composition domains in Fe-Mn-Al-C system steels locate. It further indicates that the stacking fault energy increases with the rise of temperature. At higher temperature, the size of dislocation nodes decrease and due to this reason, the stacking fault energy may also increase in the material.

3.3.3
Fig. 3.3.3 Changing of iso-SFE surface with the increase of temperature

The 3D plot in Fig. 3.3.4 shows the change of SFE with different Al and C alloy compositions in the composition-dependent SFE maps. Fig. 3.3.4 a) shows the stacking fault maps with the Al content of 3 wt.%, 5 wt.%, 8 wt.% and 11 wt.%. The SFE is remarkably increased by raising the Al content, especially in the alloys with higher amount of Mn and C. The addition of Al not only increases the stacking fault energy but also promotes the precipitation of nano-sized kappa phase (Fe,Mn)3AlC (Fig. 3.3.2), which controls the mechanical properties. The high strength and ductility of the alloy with high Al content is attributed to the precipitation of shearable nano-sized kappa phase and their role in the development of planar dislocation substructures upon strain [16]. As is shown in Fig. 3.3.4 b), the carbon also increases the SFE. The effect of carbon on SFE is more pronounced in the alloys with low Mn and low Al content. While in the alloys with high Mn and high Al, the SFE is much elevated up to approximately 100 mJ/m² and the effect of C is not obvious.

3.3.4
Fig. 3.3.4 Effect of Al and C on composition-dependent SFE

SYXRD Experiments
The strain hardening behaviors in high-Mn austenitic steels were investigated by means of in situ high energy synchrotron X-ray diffraction (SYXRD). The experiments were carried out at beamline P02.1 of PETRA III using synchrotron X-ray Powder Diffraction (XPD) at DESY. High energy (60 keV) synchrotron X-rays with high brilliance, small beam size and high penetration depth were applied in order to study the dynamics of dislocation, stacking fault and twinning evolution during in situ tensile test of high manganese Fe-Mn-Al-C alloys. The 2D diffraction patterns of Fe-17Mn-1.5Al-0.3C steel during deformation are shown in Fig. 3.3.5. During deformation, the occurrence of both the strain induced transformation of austenite to ε-martensite and mechanical twinning is shown in the Fe-17Mn-1.5Al-0.3C steel, while only mechanical twinning is indicated in the Fe-17Mn-1.5Al-0.6C alloy (Fig. 3.3.6). Due to the deformation twin formation, the microstructure in the steels is largely refined. The stacking fault probability and the twinning evolution show an anisotropic feature at different planes.
 

3.3.5
Fig. 3.3.5 2D diffraction patterns of Fe-17Mn-1.5Al-0.3C steel during deformation (strain rate 0.001 s-1)

The results indicate the change of microstructure and accordingly the deformation mechanisms with different the carbon content in the Fe-17Mn-1.5Al-xC alloys. With a change of carbon content from 0.3 wt.% to 0.6 wt.% in the Fe-17Mn-1.5Al-xC alloys, the predicted SFE by thermodynamic calculations changes from 18.9 mJ/m2 to 27.5 mJ/m2, which consequently leads to a change of predicted deformation mechanism from TRIP/TWIP to TWIP.

3.3.6
Fig. 3.3.6 (a) True strain-stress curve, strain rate 0.001 s-1; SEM of fractured sample after tensile test; (b) In situ synchrotron X-ray diffraction patterns during tensile test at room temperature

In high Mn steels, the main factor which contributes to controlling the strain hardening behaviors is the SFE. With addition of Al in the steels, the kappa phase precipitates which can significantly affect the mechanical properties by age hardening [17-21].

3.3.7
Fig.3.3.7 In situ SYXRD pattern shows the formation and growth of kappa phase in Fe-30Mn-8Al-1.2C steel annealed at 600 ℃ for different times

In order to achieve a deeper understanding of kappa phase formation and further control the precipitates, the in situ high energy synchrotron X-ray diffraction (SYXRD) was carried out in cooperation with TP A3, C1 and C8. In situ SYXRD pattern in Fig. 3.3.7 shows the formation and growth of kappa phase in Fe-30Mn-8Al-1.2C steel annealed at 600 ℃ for different times. It is indicated that the kappa phase already forms within the first hour of aging. At the very early stage of kappa phase formation, the kappa diffracted peaks occur at low angel at (100) and (110) planes. The small lattice mismatch (<3%) indicates the high coherency of the kappa phase precipitation from the austenitic matrix, which largely contributes to the increase of the yield strength of the materials.

 

In combination with the ab initio theoretical calculations (cooperation with TP A1), the kappa phase ordering mechanism in an austenitic matrix was cooperatively investigated. The high energy synchrotron X-ray diffraction (SYXRD) indicates the kappa phase precipitation in terms of crystallographic information and the ab initio (density-functional) calculations further provide from the thermodynamics point of view, the assessment of the thermal stability and the ordering of kappa phase formation. The sideband formation is shown in Fig. 3.3.8, indicating the kappa phase formation at〈100〉by spinodal decomposition. Furthermore, the ab initio calculation shows a larger influence of Al on the stabilization of kappa phase than carbon.

3.3.8
Fig. 3.3.8 Ex situ SYXRD pattern shows the kappa phase formation (left) in the austenite matrix (right) during annealing at 600 °C in Fe-30Mn-8Al-1.2C

Reference
[1] G. Frommeyer; U. Brüx; P. Neumann: ISIJ Int., 2003, vol. 43, pp. 438-446.
[2] D. Barbier; N. Gey; S. Allain; N. Bozzolo; M. Humbert: Mater. Sci. Eng. A, 2009, vol. 500, pp. 196-206.
[3] S. Lee; Y. Estrin; B. C. Cooman: Metall. Mater. Trans. A, 2013, vol. 45, pp. 717-730.
[4] A. T. Dinsdale: Calphad, 1991, vol. 15, pp. 317-425.
[5] A. Saeed-Akbari; L. Mosecker; A. Schwedt; W. Bleck: Metal Meter. Trans. A, 2012, vol. 43A, pp. 1688-1704.
[6] S.Allain; J. P. Chateau; O. Bouaziz: Mater. Sci. Eng. A, 2004, vol. 387, pp. 143-147.
[7] P. H. Adler; G. B. Olsen; W. S. Owen: Metall. Trans. A, 1986, vol. 17A, pp. 1725-1737.
[8] A. Saeed-Akbari; J. Imlau; U. Prahl; W. Bleck: Metal Meter. Trans. A, 2009, vol. 40A, pp. 3076-3090.
[9] K. T. Park; G. Kim; K. K. Sung; S. W. Lee; S. W. Hwang; C. S. Lee: Met. Mater. Int., 2010, vol. 16, pp. 1-6.
[10] E. Bayraktar; F. A. Khalid; C. Levaillant: Mater. Process Tech., 2004, vol. 147, pp. 145-154.
[11] H. Jiang; Q. Zhang; X. Chen; Z. Chen; Z. Jiang; X. Wu; J. Fan: Acta Mater., 2007, vol. 55, pp. 2219-2228.
[12] A. Saeed-Akbari: Ph.D. thesis, RWTH Aachen University, 2011.
[13] I. Gutierrez-Urrutia; D. Raabe: Scripta Mater., 2013, vol. 68, pp. 343-347.

 


Objective

In the next period of SFB761, besides the 3D stacking fault energy (SFE) calculation based on the thermodynamics, the microstructural effect will also be taken into account to predict the deformation mechanism in steels with the multiphase matrix. The synchrotron methodology will be continuously applied for a detailed understanding of microstructural evolution during deformation and along heat treatment cycles, e.g. the kappa phase formation, for the further precipitation control in the materials. The phase field (PF) simulations will be implemented to simulate the microstructure evolution and phase transformation kinetics and the elemental partitioning will be studied in cooperation with TP A3 and C8. The interstitial and substitutional partitioning across the phase boundary and the microstructure evolution during phase transformation in the materials simulated by phase field method will be further input into representative volume element (RVE) simulations to predict the strain hardening behaviors in cooperation TP C6. With the consideration of local microstructure and partitioning features, both the local and global dominant deformation mechanism in the alloys will be predicted. An upgraded mechanism map to predict the deformation behaviors in the steels with multiphase microstructure is aimed.


Methods and research plan

AP 1 Synchrotron x-ray diffraction of kappa phase precipitation, data analysis by Rietveld refinement
To control the precipitations in MBIP materials, the synchrotron x-ray diffraction are applied in both in situ and ex situ regimes (Fig. 3.4.2). The kappa phase formation mechanisms will be studied in terms of crystallography, lattice mismatch, strain effect, elemental diffusion and morphology evolution. The morphology and the size effect of kappa phase on the deformation behaviors of MBIP will be investigated in cooperation with TP C2.


AP 2 Experimental validation of modeling results by atom probe tomography, EBSD and metallography
In order to validate the modeling results, metallography and EBSD will be used for a quantitative analysis for the microstructures in the steels in cooperation with TP C1. The chemical gradients and the elemental partitioning features between phases will be studied by atom probe tomography in cooperation with TP C8. The microstructural and partitioning features studied by thermodynamic calculations, phase field modeling and the experimental validations will be integrated into the upgraded mechanism maps to solve the more complicated deformation prediction problems in high-Mn steels, MMnS steels and MBIP steels with various phases.


AP 3 Phase field modeling of microstructure evolution during phase transformations in MMnS steels
Coupling with the Calphad approach, a phase field model will be developed to study the microstructure evolution and phase transformation kinetics in MMnS steels. The existing phase field model which considers the thermodynamic, kinetics and elemental partitioning features has been successfully applied for other multiphase materials in our institute. The model will be improved and implemented to solve the scientific questions in SFB 761. The austenite reverse transformation and the martensitic transformation during quenching will be focused. The interstitial and substitutional partitioning across the phase boundary and the microstructure evolution during phase transformation in the materials simulated by phase field method will be further input into representative volume element (RVE) simulations to predict the strain hardening behaviors in cooperation TP C6.


AP 4 Integration of the microstructural and partitioning features into Microstructure- and mechanism maps
Finally, the 2D and 3D mechanism maps will be developed with consideration of not only chemical, temperature, grain size effect, but also the microstructural, partitioning features between multiphases and the local deformation behaviors of the alloys in Fe-Mn-C and Fe-Mn-Al-C systems. By this and with considering the results of TP A7 and C6, design criteria for steels with defined strain hardening behavior and mechanical properties are provided.

3.4.1
Fig. 3.4.1 Overview of the material design by the upgraded deformation mechanism maps

 

 

Previous Phase


For material production and for achieving the extraordinary mechanical properties of high-manganese steels it is necessary to control the different strengthening mechanisms like mechanical twinning (TWIP), strain-induced phase-transformation (TRIP) and dynamic strain ageing (DSA) which are present these steels. The stacking fault energy (SFE) is the characteristic value which defines the occurance of only one or a mixture of two strengthening mechanisms. In this project the SFE is calculated based on the chemical composition with both empirical equations as well as ab initio methods. The project results in a mechanism map which shows the present strengthening mechanism in dependence of the chemical composition and the Temperature.