CRSS determination combining ab-initio framework and Surrogate Neural Networks

•A novel ab-initio framework of the CRSS for an extended dislocation slip is utilized to generate a large dataset including a wide range of hypothetical and real FCC materials.•A novel minimum energy path approach to calculate the CRSS is established to derive a triangular trajectory of Shockley partials in a robust intermittent “zig-zag” motion.•Learning from a large dataset, the CRSS variations with materials’ fingerprints are revealed to be mediated by equilibrium core-widths of Shockley partials for an extended dislocation slip.•Surrogate Neural Networks (SNN) model is developed with a large dataset of the CRSS in hypothetical FCC materials for the first time in literature, resulting in high accuracy 94% on real FCC materials as well, including metals and high entropy alloys (HEAs).•Core-widths mediated dependencies of the CRSS on the materials’ fingerprints such as stacking fault energies, lattice constant, and elastic moduli are distinctly revealed for the first time in literature, which is instantly demonstrated in the precise SNN as well.