Macro to nanoscale deformation of transformation-induced plasticity steels: Impact of aluminum on the microstructure and deformation behavior

Injeti, V.S.Y.; Li, Z.C.; Yu, Baosheng; Misra, R.D.K.; Cai, Zhiping; Ding, Hua

doi:10.1016/j.jmst.2017.11.011

Cited by 25 publications

(7 citation statements)

References 46 publications

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“…Understanding the influence of alloying elements on SFE is crucial for alloy design and has attracted various studies [6,25,90]. However, due to the limited time and resources, previous work only focused on limited alloys to draw a conclusion.…”

Section: Alloying Effects On Sfementioning

confidence: 99%

Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Wang

2020

Science and Technology of Advanced Materials

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Stacking fault energy (SFE) is of the most critical microstructure attribute for controlling the deformation mechanism and optimizing mechanical properties of austenitic steels, while there are no accurate and straightforward computational tools for modeling it. In this work, we applied both thermodynamic modeling and machine learning to predict the stacking fault energy (SFE) for more than 300 austenitic steels. The comparison indicates a high need of improving low-temperature CALPHAD (CALculation of PHAse Diagrams) databases and interfacial energy prediction to enhance thermodynamic model reliability. The ensembled machine learning algorithms provide a more reliable prediction compared with thermodynamic and empirical models. Based on the statistical analysis of experimental results, only Ni and Fe have a moderate monotonic influence on SFE, while many other elements exhibit a complex effect that their influence on SFE may change with the alloy composition.

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Section: Alloying Effects On Sfementioning

confidence: 99%

Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Wang

2020

Science and Technology of Advanced Materials

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“…Among them, the TRIP-assisted steels have attracted the attention of researchers owing to their improved mechanical behavior and cost-effective alloying [3]. The main characteristic of TRIP-assisted steels is their ability to transform into strain-induced martensite [4], which helps in enhancing both strength and formability [5]. The TRIP effect adding other alloying elements (Cr, Mo, V, etc.)…”

Section: Introductionmentioning

confidence: 99%

Alternative Approach for the Intercritical Annealing of (Cr, Mo, V)-Alloyed TRIP-Assisted Steel before Austempering

Zurnadzhy

Ефременко

Petryshynets

et al. 2022

Metals

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TRIP-assisted С-Si-Mn steels are usually subjected to austempering with a preliminary intercritical annealing that is targeted at the multi-phase structure with 40–60 vol.% of proeutectoid ferrite. The kinetics and the mechanism of phase-structural transformations can be impacted due to the additional alloying of TRIP-assisted steel by the strong carbide forming elements, thus necessitating an alternative approach for the selection of intercritical annealing parameters. This issue is analyzed in the present work, which investigates the effect of the temperature of intercritical annealing on the “structure/properties” correlations in 0.2 wt.% C-Si-Mn-Nb steel additionally alloyed by 0.55 wt.% Cr, 0.20% Mo, and 0.11 wt.% V. The annealing temperature ranged from 770 °C to 950 °C, and austempering was performed at 350 °C for 20 min. It was observed that the addition of the (Cr, Mo, and V) complex significantly improved the steel hardenability. However, the annealing of steel at 770 °C (to gain 50 vol.% of proeutectoid ferrite) resulted in the precipitation of coarse cementite lamellas during bainite transformation, thus lowering the amount of retained austenite (RA) and decreasing the strength and ductility of the steel. At higher annealing temperatures, carbide-free bainite was formed, which presented a 2.5–3.5 times increase in the RA volume fraction and a 1.5 times increase in the RA carbon content. The optimal combination of the mechanical properties (UTS of 1040 MPa, TEL of 23%, V-notch impact toughness of 95 J/cm2, PSE of 23.9 GPa·%) referred to annealing at a temperature close to the Ac3 point, resulting in a structure with 5 vol.% ferrite and 9 vol.% RA (the residue was carbide-free bainite). This structure presented an extended manifestation of the TRIP effect with an enhanced strain hardening rate due to strain-induced martensite transformation. The impact of the alloying elements on the carbon activity in austenite served as the basis for the analysis of structure formation.

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“…The requirement of low-cost production, environmental friendliness, and high safety performance in the automotive industry drives the development of lightweight vehicles. Besides weight reduction by the down-gauging of high strength steels, reducing the density of steels through the addition of aluminum (Al) has recently attracted significant attention [1][2][3][4]. In recent years, a low-density δ-TRIP steel with good mechanical properties and weldability was developed for potential application in automotive components.…”

Section: Introductionmentioning

confidence: 99%

The Significance of Optimizing Mn-Content in Tuning the Microstructure and Mechanical Properties of δ-TRIP Steels

Chen

et al. 2021

Metals

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The δ-TRIP steel has attracted a lot of attention for its potential application in automotive components, owing to the low density, good combination of strength, and ductility. As the difficulty in yield strength further increasement is caused by large fraction ferrite, the work hardening ability was enhanced by optimizing the manganese (Mn)-content in this study. Three δ-TRIP steels with different manganese (Mn)-content were designed to explore the significant effect of Mn content on the work hardening behavior in order to develop high strength steel suitable for the industrial continuous annealing process. The detailed effect of Mn on microstructure evolution and deformation behavior was studied by scanning electron microscope (SEM), interrupted tensile tests, X-ray diffraction (XRD), and in-situ electron backscattered diffraction (EBSD). The study suggested that 2 Mn steel has the lowest degree of bainitic transformation, as a result of fine grain size of prior austenite. The large TRIP effect and dislocation strengthening improve the work hardening rate, resulting in 2 Mn steel exhibiting comparable mechanical properties with the QP980 steels. The retained austenite in 1.5 Mn steel progressively transformed into martensite and sustained the strain to a high strain value of 0.40, showing a good strength-ductility balance.

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Macro to nanoscale deformation of transformation-induced plasticity steels: Impact of aluminum on the microstructure and deformation behavior

Cited by 25 publications

References 46 publications

Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Alternative Approach for the Intercritical Annealing of (Cr, Mo, V)-Alloyed TRIP-Assisted Steel before Austempering

The Significance of Optimizing Mn-Content in Tuning the Microstructure and Mechanical Properties of δ-TRIP Steels

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