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

14 citations · 14 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2026

Linking Electronic Bonding and Short-range Order to Strength in -Titanium Alloys: A First-Principles Study

Md Faiz Akhtar, Nilesh P. Gurao, Somnath Bhowmick

The development of accurate strength prediction models for titanium alloys is critical for advanced materials design. This study systematically examines how the mechanical properti…

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…