Experimental Investigation and Computer Simulation of Diffusion in Fe-Mo and Fe-Mn-Mo Alloys with Different Optimization
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g demand for safety and lightweight, steels with higher strength and ductility are urgently needed in the automotive industry. High-manganese TWIP steel has been attracting much attention for its excellent combination of strength and ductility. To enhance strength further, microalloying elements, such as Mo, Nb, Ti, and V,[1,2] are usually added. They play a crucial role on diffusion kinetics as well. As high-manganese steels are typically austenitic (fcc) steels, it is imperative to obtain the diffusion mobilities for the fcc phase. On the other hand, Molybdenum is one of the common elements added in duplex stainless steels. Hence, the diffusivities of Mo in bcc Fe-Mo and Fe-Mn-Mo alloys are needed to simulate phase transformations involving the fcc and bcc phases. In the present work, the binary and ternary interdiffusion coefficients in fcc and bcc Fe-Mo and Fe-Mn-Mo alloys were experimentally investigated employing the diffusion-couple technique. The diffusion mobilities in the Fe-Mo and Fe-Mn-Mo systems were optimized using the DICTRA software[3] on WEISEN ZHENG, Ph.D. Student, is with the School of Materials Science and Engineering, Shanghai University, Shanghai 200444, P.R. China, and also with the Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm 10044, Sweden, JOHN A˚GREN, Professor, is with the Department of Materials Science and Engineering, KTH Royal Institute of Technology. XIAO-GANG LU, Professor, is with the School of Materials Science and Engineering, Shanghai University, and also with the State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072, P.R. China. Contact e-mail: [email protected] YANLIN HE and LIN LI, Professors, are with the School of Materials Science and Engineering, Shanghai University. Manuscript submitted April 04, 2016. METALLURGICAL AND MATERIALS TRANSACTIONS A
the basis of the experimental diffusivities. This kind of optimization using the DICTRA software is referred to as the traditional method in the present work. However, the traditional optimization method needs to first derive interdiffusion coefficients from diffusion profiles before the optimization of mobilities. In order to ensure that diffusion mobilities are optimized based on the original experimental data, the present work develops a direct method where mobilities are fitted directly to diffusion profiles without the need of extracting interdiffusion coefficients. II.
MODELING OF DIFFUSION MOBILITY
The work is based on the formalism suggested by Andersson and A˚gren,[4] i.e., the diffusion mobility for species i is expressed as Qi 1 1 Qi þ RT ln M0i ¼ exp Mi ¼ M0i exp ; RT RT RT RT ½1 where M0i is a frequency factor; Qi is an activation energy; R is the gas constant; and T is the absolute temperature. RT ln M0i and Qi are composition and temperature-dependent properties represented by Redlich–Kister polynomials " # X X XX p p;q r r Ui ¼ xp Ui þ xp xq Ui ðxp xq Þ p
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