a b s t r a c tThe texture and microstructure evolutions of a fine-grained TWIP steel subjected to tensile tests at room temperature were investigated in relation to the mechanical behavior. This steel combines both high ductility and strength owing to the TWIP effect. Also the steel exhibits a high strain hardening rate that evolves according to five stages, which are related to the microstructure and texture evolutions and characteristics. The formation of nano-twins in the initial stage of deformation leads to an increase in strain hardening rate. The development of the pronounced <1 1 1> fiber in the tensile direction sustains mechanical twinning and maintains the strain hardening rate on a high level. The resulting microstructure exhibits several types of twin configurations and sub-boundaries with high misorientations due to intense activities of dislocation glide. The twin volume fraction was estimated to be 9% at the final stage of tensile deformation. The new orientations generated by mechanical twinning do not change considerably the final texture.

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Using both experimental and modeling approaches, we give some clarifications regarding the mechanisms of interaction between ferrite recrystallization and austenite formation in cold-rolled high-strength steels. Using different thermal paths, we show that ferrite recrystallization and austenite formation can be strongly interdependent. The nature of the interaction (weak or strong) affects significantly the austenite formation and the resulting microstructure. We show that the kinetics of austenite formation depends intrinsically on both heating rates and the extent of ferrite recrystallization. An unexpected behavior of austenite growth was also seen at high heating rates. A possible explanation is presented based on the nature of the local equilibrium at the ferrite-austenite interface. The microstructure is more heterogeneous and anisotropic when both austenite formation and ferrite recrystallization overlap. A mechanism of microstructural formation is proposed, and this is supported by 2D simulations' images.

A new relation for the Ms temperature prediction is proposed. The composition ranges covered by the new model are enlarged compared to the classical relations. This new relation is obtained from a data base of almost 1000 different compositions. The predictive ability of this new relation is compared to the classical ones.

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