journal article·2011-06

Experimental and numerical analysis on formation of stable austenite during the intercritical annealing of 5Mn steel

Haiwen Luo, Jie Shi, Chang Wang, Wenquan Cao, Xinjun Sun, Han Dong

Acta Materialia· Volume 59· Issue 10
Publisher page

Abstract

Abstract Microstructure evolution during the intercritical annealing at 650 °C for various durations up to 144 h in 5 wt.% Mn-containing steel, from the initial martensitic microstructure to mainly ultrafine lamellar microstructures consisting of austenite laths and ferrite laths, was examined experimentally and analyzed numerically in this paper. Annealing for longer duration results in a larger volume faction of austenite and thicker γ laths with an enrichment of Mn, which significantly improves elongation and lowers the yield stress. The γ fraction increases almost linearly with the logarithm of annealing time until it is saturated after 12 h annealing. The thickening of the austenite lath was numerically simulated by DICTRA software and the MOB2 database under the local equilibrium. The simulation result is in fair agreement with the measurements, and also shows a proportional dependence on the logarithm of the annealing time up to 12 h. Furthermore, numerical simulations on growth of the austenite lath nucleated at the ferrite–cementite interface were also performed, and indicated that such growth should be very sluggish due to the slow dissolution of cementite. As a result, it is concluded that the growth of austenite nucleated at the ferrite lath boundaries, instead of the growth of austenite nucleated at the ferrite–cementite interface, plays a major role in the increase in austenite volume fraction during the annealing, which is controlled by the diffusion of Mn in both austenite and ferrite phases.
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Research context

OpenAlex topics: Microstructure and Mechanical Properties of Steels · Metal Alloys Wear and Properties · Hydrogen embrittlement and corrosion behaviors in metals

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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