Martensite transformation kinetics in 9Cr–1.7W–0.4Mo–Co ferritic steel

Gao, Qiuzhi; Qu, Fu; Wang, Yingling; Qiao, Zhixia

doi:10.1016/j.jallcom.2014.05.060

Cited by 40 publications

(27 citation statements)

References 37 publications

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“…The latter equation has been verified to be applicable to diffusion controlled reactions in a wide range of works, incl. [70][71][72][73]. If i is taken as 2 then the resulting equation closely approximates Eq (7) which is valid for randomly and homogeneously distributed nuclei, for which growth is not limited by blocking [38,74].…”

Section: Growth and Impingement Of Diffusion Fields In The Modelmentioning

confidence: 59%

Predicting the quench sensitivity of Al–Zn–Mg–Cu alloys: A model for linear cooling and strengthening

et al. 2015

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In this work the quench sensitivity of Al-Zn-Mg-Cu alloys is studied through continuous cooling at constant rates of a range of alloys using differential scanning calorimetry (DSC), transmission electron microscopy (TEM), scanning electron microscopy (SEM) and hardness testing. The DSC, TEM and SEM data show that the cooling reactions are dominated by a high temperature reaction (typically ~450 °C down to ~350 °C) due mostly to S-Al2CuMg phase formation, a medium temperature reaction (~350 °C down to ~250 °C) due predominantly to -Mg(Al,Cu,Zn)2 phase formation and a lower temperature reaction (~250 °C down to ~150 °C) due to a Zn-Cu rich thin plate phase. A new, physically-based model is constructed to predict rates of all reactions, enthalpy changes and resulting yield strength in the artificially aged condition. The model incorporates a recently derived model for diffusion-controlled reactions based on the extended volume fraction concept as well as recent findings from first principles modelling of enthalpies of the relevant phases. The model shows a near perfect correspondence with data on all 6 alloys studied extensively by cooling DSC and hardness testing, and 2 allows prediction of the influence of the 3 major elements and 3 dispersoid forming elements on quench sensitivity. Graphical abstract Highlights

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Section: Growth and Impingement Of Diffusion Fields In The Modelmentioning

confidence: 59%

Predicting the quench sensitivity of Al–Zn–Mg–Cu alloys: A model for linear cooling and strengthening

et al. 2015

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“…They also present that the austenitic grain size has a strong effect on the martensite start temperature, but not on the transformation evolution. However, these effects are verified in different levels for different type of steels 2,3 .…”

Section: Introductionmentioning

confidence: 92%

Austenitizing Temperature and Cooling Rate Effects on the Martensitic Transformation in a Microalloyed-Steel

2020

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The effects of the austenitizing temperature and the cooling rate upon the kinetic of athermal martensitic transformation in a microalloyed steel were evaluated. Considering the studied steel, the knowledge about these effects on the martensitic transformation has a great relevance for naval manufacturers and steel researchers. In this study, computational simulation was performed aiming to evaluate the phase's stability. Specimens were submitted to quenching simulations in a dilatometer, considering four different austenitizing temperatures and four cooling rates. The results shown that the austenite chemical composition was not significantly affected by the austenitizing temperatures. Both the austenitic grain size and the cooling rate affected the martensitic transformation kinetics. The larger the austenitic grain size, the higher the Ms. The austenitic grain growth promoted a decrease in the required chemical energy to compensate the free energy increase associated with the lattice strain and the creation of new interfaces, leading to a lower austenite undercooling. An extrinsic effect of the cooling rate on the Ms was observed. For lower cooling rates, the carbide precipitation modified que austenite chemical composition, changing its stability and increasing Ms. A predictability equation, correlating the M S with the austenite grain size and the steel cooling rate, was proposed.

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“…Considering continuous nucleation, the number of new martensite phase per unit volume at the temperature T can be determined as [36]:…”

Section: Continuous Coolingmentioning

confidence: 99%

“…The growth of the martensite phase obeys a scaling law which differs from diffusion-controlled transformations due to the displacive nature of the transformation. An ellipsoidal martensite plate forms with various growth velocities along the different axial direction, i.e., v = v x = v y = vz η [1,36]. It follows:…”

Section: Three Dimensional Microstructurementioning

confidence: 99%

Modelling the microstructure of martensitic steels

Rahnama

Qin

2015

Computational Materials Science

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A method based on the kinetics of crystal growth has been developed and applied to the computation of three-dimensional microstrucuture in austenite-matensite steels. The detailed crystallography of the transformation is used to model a realistic martensitic microstrucuture during the transformation without an external system of stresses. The interaction energy based on the plastic work model is taken into account to compute the variant selection in an austenitic stainless steel and formation of martensite under externally applied stress.

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Martensite transformation kinetics in 9Cr–1.7W–0.4Mo–Co ferritic steel

Cited by 40 publications

References 37 publications

Predicting the quench sensitivity of Al–Zn–Mg–Cu alloys: A model for linear cooling and strengthening

Predicting the quench sensitivity of Al–Zn–Mg–Cu alloys: A model for linear cooling and strengthening

Austenitizing Temperature and Cooling Rate Effects on the Martensitic Transformation in a Microalloyed-Steel

Modelling the microstructure of martensitic steels

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