Cellular automaton modeling of austenite formation from ferrite plus pearlite microstructures during intercritical annealing of a C-Mn steel

doi:10.1016/j.jmst.2020.02.002

Abstract

Abstract:

A mesoscopic cellular automaton model was developed to study the microstructure evolution and solute redistribution of austenization during intercritical annealing of a C-Mn steel. This model enables a depiction of three-stage kinetics of the transformation combined with the thermodynamic analysis: (1) the rapid austenite growth accompanied with pearlite degeneration until the pearlite dissolves completely; (2) the slower austenite growth into ferrite with a rate limiting factor of carbon diffusion in austenite; and (3) the slow austenite growth in control of the manganese diffusion until the final equilibrium reached for ferrite and austenite. The effect of the annealing temperature on the transformation kinetics and solute partition is also quantitatively rationalized using this model.

Key words: Austenization, Intercritical annealing, C-Mn steels, Cellular automaton, Mesoscale modeling

Chunni Jia, Chengwu Zheng, Dianzhong Li. Cellular automaton modeling of austenite formation from ferrite plus pearlite microstructures during intercritical annealing of a C-Mn steel[J]. J. Mater. Sci. Technol., 2020, 47: 1-9.

Figures/Tables 11

Fig. 1. Chemical potentials of Mn in austenite and ferrite as a function of Mn concentration at 760 °C calculated by Thermo-Calc.

Table 1 Diffusion parameters used in simulation [27,36].

i	$D_{i,0}^{\text{ }\!\!\varphi\!\!\text{ }}$ (m² s^-1)	$Q_{i}^{\text{ }\!\!\gamma\!\!\text{ }}$ (kJ mol^-1)	$D_{i,0}^{\text{ }\!\!\alpha\!\!\text{ }}$ (m² s^-1)	$Q_{i}^{\text{ }\!\!\alpha\!\!\text{ }}$ (kJ mol^-1)
C	2.0 × 10^-5	140	/	/
Mn	5.7 × 10^-5	277	4.36 × 10^-4	243. 6

Fig. 2. Initial microstructure for cellular automaton simulation. (White regions: ferrite phase, dark gray regions: pearlite, black lines: grain boundaries.).

Table 2 Key parameters used in simulation [42].

M₀(mmol J^-1 s^-1)	Q_αγ(kJ mol^-1)	$M_{\text{Mn}}^{\text{Trans}-\text{int}}$ (m² J^-1 s^-1)	δ (m)	V_m(m³ mol^-1)	η (J m^-2)
0.5	140	2.9 × 10^-22	1 × 10^-9	7.39 × 10^-6	0.56

Fig. 3. Simulated kinetics of austenite formation at annealing temperature of 760 °C.

Fig. 4. Simulation results of microstructure evolution (left), carbon concentration distribution (middle) and manganese concentration distribution (right) at the annealing temperature of 760 °C in a Fe-0.08C-1.75 Mn (in wt.%) steel: (a) t1 = 0.5 s, (b) t2 = 5 s, (c) t3 = 25 s, (d) t4 = 75 s. In the microstructures, the yellow areas are the newly formed austenite; the white regions are ferrite phase and the dark grey regions are pearlite phase. The black lines indicate the grain boundaries.

Fig. 5. Schematic diagrams of various transformation stages during austenite growth in intercritical annealing of the C-Mn steel [8]: (a) dissolution of pearlite; (b) austenite growth with carbon diffusion in austenite; (c) austenite growth with manganese partition at the moving interface; and (d) final solute equilibrium.

Fig. 6. Evolution of carbon concentration (a) and manganese concentration (b) along the red straight line (starting from the left) shown in Fig. 4.

Fig. 7. Isothermal section of Fe-Mn-C ternary system at 760 °C calculated by Thermo-Calc. The potential concentration path for various transformation stages is indicated with the short-dotted lines.

Fig. 8. Simulated transformation kinetics of austenite formation at various annealing temperatures in a Fe-0.08C-1.75 Mn (in wt.%) steel.

Fig. 9. Simulation results of microstructure (left), carbon concentration field (middle) and manganese concentration field (right) when t=75 s at different annealing temperatures in a Fe-0.08C-1.75 Mn (in wt.%) steel: (a) T = 740 °C; (b) T = 760 °C; (c) T = 780 °C. In the microstructures, the yellow areas are the newly formed austenite; the white regions are ferrite phase. The black lines indicate the grain boundaries.

References 43

[1]	C.C. Tasan, M. Diehl, D. Yan, M. Bechtold, F. Roters, L. Schemmann, C. Zheng, N. Peranio, D. Ponge, M. Koyama, K. Tsuzaki, D. Raabe, Annu. Rev. Mater. Res. 45 (2015) 391-431. DOI URL
[2]	H. Azizi-Alizamini, M. Militzer, W. J. Poole, Metall. Mater. Trans. A 42 (2011) 1544-1557. DOI URL
[3]	A. Eggbauer, M. Lukas, G. Ressel, P. Prevedel, F. Mendez-Martin, J. Keckes, A. Stark, R. Ebner, J. Mater. Sci. 54 (2019) 9197-9212.
[4]	M. Enomoto, S. Li, Z.N. Yang, C. Zhang, Z.G. Yang, Calphad 61 (2018) 116-125.
[5]	V. Singh, M. Adhikary, T. Venugopalan, A. Chakraborty, T. Nanda, B.R. Kumar, Mater. Manuf. Process. 32 (2017) 1806-1816.
[6]	W.C. Jeong, C.H. Kim, J. Mater. Sci. 20 (1985) 4392-4398.
[7]	D.Z. Yang, E.L. Brown, D.K. Matlock, G. Krauss, Metall. Trans. A 16 (1985) 1523-1526.
[8]	G.R. Speich, V.A. Demarest, R.L. Miller, Metall. Mater. Trans. A 12 (1981) 1419-1428.
[9]	Y.J. Lan, D.Z. Li, C.J. Huang, Y.Y. Li, Modell. Simul. Mater. Sci. Eng. 12 (2004) 719-729.
[10]	D. An, S.I. Baik, S. Pan, M.F. Zhu, D. Isheim, B.W. Krakauer, D.N. Seidman, Metall. Mater. Trans. A 50 (2019) 436-450.
[11]	B. Zhu, M. Militzer, Metall. Mater. Trans. A 46 (2015) 1073-1084.
[12]	H. Chen, S. van der Zwaag, Acta Mater. 72 (2014) 1-12.
[13]	D. An, S. Chen, D. Sun, S. Pan, B.W. Krakauer, M.F. Zhu, Comput. Mater. Sci. 166 (2019) 210-220.
[14]	T. Jia, M. Militzer, Metall. Mater. Trans. A 46 (2015) 614-621.
[15]	A. Jacot, M. Rappaz, R.C. Reed, Acta Mater. 46 (1998) 3949-3962.
[16]	B.J. Yang, A. Hattiangadi, W.Z. Li, G.F. Zhou, T.E. McGreevy, Mater. Sci. Eng. A 527 (2010) 2978-2984.
[17]	B.J. Yang, L. Chuzhoy, M.L. Johnson, Comput. Mater. Sci. 41 (2007) 186-194.
[18]	K. Vijay Reddy, C. Halder, S. Pal, Trans. Ind. Inst. Met. 70 (2017) 909-915.
[19]	C. Bos, M.G. Mecozzi, J. Sietsma, Comput. Mater. Sci. 48 (2010) 692-699.
[20]	A. Jacot, M. Rappaz, Acta Mater. 47 (1999) 1645-1651.
[21]	M. Ollat, M. Militzer, V. Massardier, D. Fabregue, E. Buscarlet, F. Keovilay, M. Perez, Comput. Mater. Sci. 149 (2018) 282-290.
[22]	C. Bos, M.G. Mecozzi, D.N. Hanlon, M.P. Aarnts, J. Sietsma, Metall. Mater. Trans. A 42 (2011) 3602-3610.
[23]	H. Chen, C.Y. Zhang, J.N. Zhu, Z.N. Yang, R. Ding, C. Zhang, Z.G. Yang, Acta Metall. Sin. 54 (2018) 217-227.
[24]	G.P. Krielaart, J. Sietsma, S. van der Zwaag , Mater. Sci. Eng. A 237 (1997) 216-223.
[25]	J. Rudnizki, B. Böttger, U. Prahl, W. Bleck, Metall. Mater. Trans. A 42 (2011) 2516-2525.
[26]	E. Navara, R. Harrysson, Scr. Mater. 18 (1984) 605-610.
[27]	M.G. Mecozzi, C. Bos, J. Sietsma, Acta Mater. 88 (2015) 302-313.
[28]	J. Sietsma, S. van der Zwaag, Acta Mater. 52 (2004) 4143-4152.
[29]	C. Bos, J. Sietsma, Acta Mater. 57 (2009) 136-144.
[30]	J. Svoboda, F.D. Fischer, P. Fratzl, E. Gamsjäger, N.K. Simha, Acta Mater. 49 (2001) 1249-1259.
[31]	S.M.C. Van Bohemen, C. Bos, J. Sietsma, Metall. Trans. A 21 (1990) 2115-2123.
[32]	W. Huang, Metall. Trans. A 21 (1990) 2115-2123.
[33]	J.O. Andersson, T. Helander, L. Höglund, P. Shi, B. Sundman, Calphad 26 (2002) 273-312.
[34]	C.R. Hutchinson, A. Fuchsmann, Y. Brechet, Metall. Mater. Trans. A 35 (2004) 1211-1221.
[35]	M. Umemoto, Z. Hai Guo, I. Tamura, Mater. Sci. Technol. 3 (1987) 249-255.
[36]	H. Bhadeshia, R. Honeycombe, Steels - Microstructure and Properties, third ed., Elsevier, 2006.
[37]	C.W. Zheng, N.M. Xiao, D.Z. Li, Y.Y. Li, Comput. Mater. Sci. 45 (2009) 568-575.
[38]	R. Sasikumar, R. Sreenivasan, Acta Metall. 42 (1994) 2381-2386.
[39]	K. Kremeyer, J. Comput. Phys. 142 (1998) 243-263.
[40]	C.W. Zheng, D. Raabe, D.Z. Li, Acta Mater. 60 (2012) 4768-4779.
[41]	C.W. Zheng, D. Raabe, Acta Mater. 61 (2013) 5504-5517.
[42]	C.W. Zheng, N.M. Xiao, L.H. Hao, D.Z. Li, Y.Y. Li, Acta Mater. 57 (2009) 2956-2968.
[43]	M.M. Souza, J.R.C. Guimarães, K.K. Chawla, Metall. Trans. A 13 (1982) 575-579.