Insight into Ideal Shear Strength of Ni-based Dilute Alloys using First-Principles Calculations and Correlational Analysis

TL;DR

This study uses first-principles calculations and correlational analysis to understand how alloying elements affect the ideal shear strength of Ni-based dilute alloys, revealing key atomic properties and potential for machine learning applications.

Contribution

It introduces a comprehensive analysis of atomic property influences on shear strength and demonstrates applications in machine learning and multiscale modeling.

Findings

Shear moduli strongly correlate with ideal shear strength.

Atomic size and electronegativity significantly influence shear strength.

Predicted shear strengths aid multiscale deformation modeling.

Abstract

The present work examines the effect of alloying elements (denoted X) on the ideal shear strength for 26 dilute Ni-based alloys, Ni$_{11}$X, as determined by first-principles calculations of pure alias shear deformations. The variations in ideal shear strength are quantitatively explored with correlational analysis techniques, showing the importance of atomic properties such as size and electronegativity. The shear moduli of the alloys are affirmed to show a strong linear relationship with their ideal shear strengths, while the shear moduli of the individual alloying elements were not indicative of alloy shear strength. Through combination with available ideal shear strength data on Mg alloys, a potential application of the Ni alloy data is demonstrated in the search for a set of atomic features suitable for machine learning applications to mechanical properties. As another illustration, the predicted Ni ideal shear strengths play a key role in a predictive multiscale framework for deformation behavior of single crystal alloys at large strains, as shown by simulated stress-strain curves.