APS Logo

ElATools: A tool for predicting and analyzing anisotropic elastic properties of 2D and 3D materials

POSTER

Abstract

In the last two decades, owing to the observation of anomalous mechanical properties in some materials, much effort has been taken to discover and investigate materials with such features. The negative linear compressibility (NLC), negative Poisson’s ratio (NPR) or auxeticity, and highly-anisotropic elastic modulus are the most critical anomalous elastic properties that appear in some materials due to stress-strain. These characteristics are visible by analysis and visualization of elastic tensors. Here, we introduce ElATools, a code developed to analyze anisotropic elastic properties. ElATools enables facile analysis of the second-order elastic stiffness tensor of two-dimensional (2D) and three-dimensional (3D) materials. It can efficiently identify anomalous mechanical properties in 2D and 3D materials, central to designing and developing high-performance nanoscale electromechanical devices. In addition, it enables the investigation of the behavior of the elastic wave velocities and their anisotropic properties by solving the Christoffel equation. This tool can generate data for Machine Learning to detect and predict mechanical and anisotropy properties.

Publication: Yalameha, S., Nourbakhsh, Z. and Vashaee, D., arXiv preprint arXiv:2105.07279 (2021).

Presenters

  • Shahram Yalameha

    Faculty of Physics, University of Isfahan, Isfahan 81746-73441, Iran, Faculty of Physics, University of Isfahan, 81746-73441, Isfahan, Iran

Authors

  • Shahram Yalameha

    Faculty of Physics, University of Isfahan, Isfahan 81746-73441, Iran, Faculty of Physics, University of Isfahan, 81746-73441, Isfahan, Iran

  • Zahra Nourbakhsh

    Faculty of Physics, University of Isfahan, Isfahan 81746-73441, Iran, Faculty of Physics, University of Isfahan, 81746-73441, Isfahan, Iran

  • Daryoosh Vashaee

    North Carolina State University, North Carolina State U