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K-point convergence tracker (Materials)

Ideal candidate: scientists skilled in Density Functional Theory and proficient in python.

Overview

The aim of this task is to create a python package that implements automatic convergence tracking mechanism for a materials simulations engine. The convergence is tracked with respect to the k-point sampling inside a reciprocal cell of a crystalline compound.

Requirements

  1. automatically find the dimensions of a k-point mesh that satisfy a certain criteria for total energy (eg. total energy is converged within dE = 0.01meV)
  2. the code shall be written in a way that can facilitate easy addition of convergence wrt other characteristics extracted from simulations (forces, pressures, phonon frequencies etc)
  3. the code shall support VASP or Quantum ESPRESSO

Expectations

  • correctly find k-point mesh that satisfies total energy convergence parameters for a set of 10 materials, starting from Si2, as simplest, to a 10-20-atom supercell of your choice
  • modular and object-oriented implementation
  • commit early and often - at least once per 24 hours

Timeline

We leave exact timing to the candidate. Must fit Within 5 days total.

User story

As a user of this software I can start it passing:

  • path to input data (eg. pw.in / POSCAR, INCAR, KPOINTS) and
  • kinetic energy cutoff

as parameters and get the k-point dimensions (eg. 5 5 5).

Notes

  • create an account at exabyte.io and use it for the calculation purposes
  • suggested modeling engine: Quantum ESPRESSO