A phase-field model for interphase precipitation in V-micro-alloyed structural steels

Abstract

A multi-component phase field model was developed based on CALPHAD method and directly coupled with the CALPHAD thermodynamic database using a four-sublattice model. Interphase carbide precipitation at the γ/α interface is simulated and the predictions are tested against reported experimental results for a medium carbon, vanadium micro-alloyed steel during an isothermal γ → α + M C transformation at 973 K. The model is found to be able to accurately predict: interphase precipitate composition, morphology and size of the precipitates. Furthermore, the tip-to-tip pairing of interphase precipitates in γ/α interphase boundaries is elucidated and found to be attributable to the minimisation of interfacial energy.

Design of advanced steels by integrated computational materials engineering

“…The composition field and influence of alloy elements (such as B and C) at the solidification dendrite tip were investigated, [68,69] and the phase morphologies in eutectic and peritectic reactions of multi‐component systems were studied [71–75] . The correlation among microstructure, processing, and mechanical properties was established and applied in the fields of welding, [68] casting, [71] and additive manufacturing [70] of steels. Precipitation:Based on the crystal structures of the constituent phases and their coherent features between phases, the phase field method can be used to quantitatively explore the precipitation kinetics of the constituent phases in multi‐component alloy systems by coupling with the CALPHAD method and atomic mobility databases [76–80] [76,77,80] .…”

“…Based on the crystal structures of the constituent phases and their coherent features between phases, the phase field method can be used to quantitatively explore the precipitation kinetics of the constituent phases in multi‐component alloy systems by coupling with the CALPHAD method and atomic mobility databases [76–80] …”

“…highlighted the potential of ML in shortening R&D cycles and reducing costs in metal additive manufacturing in a review article, advocating interdisciplinary cooperation to accelerate material development by combining physics, chemistry, material science, and computer science. Yu et al [49–128] . explored the role of ML in guiding the design and discovery of metal structural materials, emphasizing the importance of data sharing and physics‐informed modeling.…”

A phase-field model investigating the role of elastic strain energy during the growth of closely spaced neighbouring interphase precipitates

“…Ref. [15]. The interfacial energy is taken as isotropic, σ = 5 × 10 −5 J/cm 2 for the interface between ferrite and austenite [29].…”

“…In our previous paper [15], a multi-component phase field method (PFM) model was derived which was coupled with a multi-component CALPHAD thermodynamic database using a four-sublattice model. Such models, including the phase-field method or other time-dependant Ginzburg-Landau methods, are a powerful means of encapsulating the complex interactions between atomistic mechanisms and macroscopic conditions on the mesoscopic scale [16].…”