Fundamentals of isothermal austenite reversion in a Ti-stabilized 12Cr – 6 Ni – 2 Mo super martensitic stainless steel: Thermodynamics versus experimental assessments
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Abstract
Abstract This work addresses the fundamentals of inter-critical austenite reversion in a Ti-stabilized 12Cr-6Ni-2Mo (at.%) supermartensitic stainless steel, combining thermodynamic and experimental assessments. The calculation of the temperature and composition at which ferrite and austenite phases have the same free energy, i.e. T0 and C0(T), respectively, is discussed as a methodology to understand the austenite reversion and stabilization mechanisms. An ultra-fast heating rate of 500 °C s−1 provided isothermal austenite nucleation and growth from a fully solubilized martensite, allowing direct comparison with the compositional tie-lines and the transformation paths described by the free energy calculations. Isothermal transformation temperatures below and above T0 (625 °C) were used. Below T0, massive reversion was suppressed since it would imply a free energy increase. The opposite occurred above T0, since the critical Ni concentration for austenite reversion was lower than for the solubilized case. Transmission electron microscopy and atom probe tomography evidenced that, in all cases, lath growth occurred by local equilibrium partitioning of Ni, along with co-segregation of ferrite-stabilizing elements (Cr and Mo) at the advancing interface. The complex interaction between Cr, Ni and Mo on the energy gain upon nucleation of austenite revealed that Cr segregation can be beneficial while the adverse effect of Mo can be quickly outbalanced by Ni. The most stable reverted laths were obtained for transformation temperatures at least 15 °C below T0 with average austenite/martensite Ni partitioning factors higher than 2.0.
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Research context
OpenAlex topics: Microstructure and Mechanical Properties of Steels · Hydrogen embrittlement and corrosion behaviors in metals · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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