Medium Mn steels are a promising material for developing advanced high strength steels with increased formability and reduced weight. Generally, the mechanical properties of medium Mn steels depend on the austenite morphology and stability, and thus, modification of the particle sizes and the austenite stability can yield better mechanical properties. To date, several methods for austenite stabilization have been proposed. They mainly focus on improving the material’s properties by reducing the density, increasing the annealing temperatures, and inhibiting carbide precipitation during cooling. Consequently, the relationship between processing, microstructure, and properties of medium Mn steels have recently attracted significant research attention. Nevertheless, despite the extensive research, little work has been conducted on systematic optimization of chemical composition and heat treatment processes to fabricate Mn steels with desired microstructural characteristics. This can be attributed to overdependence on exhaustive experimental methods and provisional computation techniques.
Motivated by the promising results from previous research work, Professor Gregory Haidemenopoulos and John Aristeidakis who is a PhD candidate, both from the University of Thessaly in Greece developed a new ICME design approach for the composition and processing of medium Mn steels. The main objective was to develop ferrite containing medium Mn steel with an optimized microstructure as per the design and austenite stability requirements. Their research work is currently published in the research journal, Acta Materialia.
In their approach, a novel medium Mn TRIP/TWIP steel was developed via a combination of multi-objective genetic optimization and CALPHAD-based thermodynamic and kinetic modeling techniques. The austenite stacking fault energy was predicted using a newly developed sub-regular solution model. This model takes into consideration the effects of carbon, manganese, nickel, aluminum, silicon, and chromium metals. The implementation of the stack fault energy was done in the MATLAB environment and the source code has been made available to provide more insights and further understanding of the results. Finally, the proposed modeling approach was validated using both data derived from the literature and in-house experiments.
The authors managed to identify several annealing temperatures and Pareto optimal solutions. The optimal intercritical annealing conditions of the single medium Mn steel was identified by solving additional optimization problems in the domain of time. Hot-rolling and solidification simulations revealed the presence of considerable δ-ferrite fractions just before annealing. This resulted in the segregation of elements in the high-temperature austenite, which further transformed to primary martensite upon quenching. Additionally, the formation of austenite bands was observed upon intercritical annealing due to the growth of austenite from martensite that came in contact with the δ-ferrite. Furthermore, austenite at the boundary exhibited a coarser structure and enhanced stability attributed to the carbon and manganese partitioning from the δ-ferrite. In contrast, the interior austenite exhibited faster kinetics that grew in fine laminar structures. The experimental results were consistent with the results derived from the literature.
In summary, the study reported a strategy for the composition and processing design of medium-Mn steels based on a combination of CALPHAD, SFE modeling, and genetic optimization techniques. Results showed that the proposed modeling allowed the design of new medium Mn steels as per the requirements. In a statement to Advances in Engineering, Professor Gregory Haidemenopoulos said their study will widen the application of modern computational techniques coupled with generic optimization in addressing the design and processing challenges encountered in the development of medium Mn steels and other materials.
Aristeidakis, J., & Haidemenopoulos, G. (2020). Composition and processing design of medium-Mn steels based on CALPHAD, SFE modeling, and genetic optimization. Acta Materialia, 193, 291-310.