Computational prediction of ideal strength for a material

TL;DR

This paper introduces a new computational method to predict the ideal strength of materials in various directions, aiding the design of superhard materials by analyzing deformation mechanisms and comparing with existing data.

Contribution

A novel computational approach for estimating tensile, shear, and indentation strengths in any crystallographic direction, validated through comparison with known structures and applied to superhard materials.

Findings

Effective prediction of material strength in multiple directions

Insights into deformation modes and atomistic mechanisms

Application to superhard materials like WC, SiC, MgAl2O4

Abstract

The ideal strength is crucial for predicting material behavior under extreme conditions, which can provide insights into material limits, guide design and engineer for enhanced performance and durability. In this work, we present a method within an allows for the estimation of tensile, shear, and indentation strengths in any crystallographic direction or plane. We have examined the strain-stress relationships of several well-known structures and compared our findings with previous work, demonstrating the effectiveness of our approach. Moreover, we performed extensive investigations into the indentation strength of hexagonal WC, \b{eta}-SiC, and MgA$l_2O_4$. The current study uncovers the modes of structural deformation and the underlying atomistic mechanisms. The insights gained from this study have significant implications for the further exploration and design of superhard materials.