Heterostructure mediated high strength and large ductility in novel medium-Mn steels with low Mn content
Source abstract
Abstract
Medium-Mn steels (MMnS) exhibit superior strength and ductility via the transformation-induced plasticity (TRIP) of retained austenite . However, to realize the partitioning of Mn atoms into retained austenite for thermal stability optimization, long-term intercritical annealing is required. In addition, the high Mn content of MMnS also causes other issues, e.g., high cost, welding, etc. In this work, instead of utilizing the TRIP effect of retained austenite, heterostructure consisting of alternatively distributed lamellar martensite zones and lamellar ultrafine dual-phase (martensite + ferrite) zones was engineered in a MMnS with low Mn content by a conventional rolling and short-term intercritical annealing process. The formation of the heterostructure was attributed to the heterogeneous distribution of Mn, the formation of highly dispersed martensite-austenite (MA) islands in Mn-poor zones and the low diffusion rate of Mn atoms at the intercritical annealing temperature. Tensile test results show that the steel exhibits superb synergy of a high ultimate tensile strength of 1452 MPa, a large ductility of 17 % and a high work hardening capability. The high work hardening capability and large ductility were mainly attributed to the apparent microhardness difference between the lamellar martensite zones and the ultrafine dual-phase zones that caused a strong hetero-deformation induced (HDI) strengthening effect. This study proposes a novel approach to developing high-performance steels, which provides an effective paradigm for addressing the long-established conflicts between mechanical performance, high Mn content and long intercritical annealing period of MMnS.
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Research context
OpenAlex topics: Microstructure and Mechanical Properties of Steels · Magnetic Properties and Applications · Microstructure and mechanical properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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