Microstructure entropy guided understanding of yield strength in alloy systems characterized by grain size distribution

Abstract We introduce and adopt the concept of a phenomenological parameter, microstructure entropy, S*, to understand the yield strength in alloy systems with bimodal grain size distribution obtained from large sets of experimental data. 60 groups of bimodal grain size distribution data was obtained through the application of an ingenious concept involving severe cold deformation to obtain dislocation cell-type of martensite, followed by annealing when martensite reverts to austenite by shear or diffusion mechanism, with the aim to obtain ultrafine grain size. Six factors emerged from statistical data analysis through EBSD studies in terms of grain size and grain numbers from 60 sets of data. Microstructure entropy (S*) was obtained from the bimodal structure data in a self-similar regime. Inverse of the square root of microstructure entropy ( 1 S * ) and yield strength exhibited a linear relationship. The proposed conceptual methodology has wide acceptance for any grain size distribution to obtain microstructure entropy (S*) of a specific grain structure and predict yield strength. A generic equation similar to Hall-Petch relationship, but involving microstructure entropy is proposed to predict and understand yield strength of metallic systems characterized by grain size distribution or microstructural evolution.