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20232026
most citedAccelerating the prediction of stacking fault energy by combining ab initio calculations and machine learning

14 citations · 26 across the 7 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

cond-mat.mtrl-sci2024

Effect of Cr Segregation on Grain Growth in Nanocrystalline α-Fe Alloy: A Multiscale Modelling Approach

Sandip Guin, Albert Linda, Yu-Chieh Lo +2

We present a multiscale modelling framework that integrates density functional theory (DFT) with a phase-field model (PFM) to explore the intricate dynamics of grain growth in nano…

cond-mat.mtrl-sci2024★ 14 cited

Accelerating the prediction of stacking fault energy by combining ab initio calculations and machine learning

Albert Linda, Md. Faiz Akhtar, Shaswat Pathak +1

Stacking fault energies (SFEs) are vital parameters for understanding the deformation mechanisms in metals and alloys, with prior knowledge of SFEs from ab initio calculations bein…