Mechanical Properties

Overview

This skill group covers calculations of mechanical properties of crystalline materials. Two main approaches are available:

1. MACE (via ASE) -- Fast ML-potential-based calculations. Good for screening, rapid estimation of elastic constants and equations of state. Seconds to minutes per structure.
2. Quantum ESPRESSO (QE) -- Full DFT. Required for publication-quality results and when MACE accuracy is insufficient for the system of interest.

Both approaches follow the same physical workflow (inspired by atomate2's elastic and EOS flows): relax the structure, apply systematic deformations, compute response properties, and fit constitutive models.

Sub-Skills

Method Decision Guide

Need publication-quality elastic constants?
  YES --> Use Quantum ESPRESSO DFT (stress-strain with pw.x)
  NO  --> Is the material well-represented by MACE training data?
            YES --> Use ASE + MACE (fast, ~seconds)
            NO  --> Use Quantum ESPRESSO DFT

Common Prerequisites

• Structure: Start from a CIF, POSCAR, or Materials Project query. Symmetrize before deformation workflows to reduce the number of independent deformations.
• Pseudopotentials: QE calculations need pseudopotential files (SSSP library recommended).
• Python packages: pymatgen, ASE, mace-torch, numpy, scipy, matplotlib are pre-installed.