Skip to main content

Quantum Espresso automation tool

Project description

Espresso Machine

Automation library for Quantum Espresso via python

Start discovering by checking out the Tutorials section for different calculations It is suggested to use a virtual environment to avaoid any compatibility issues.

Automated Calculation

Any kind of choosen calculation type will be initialized after automatically generating the input files

Parameter Adjustment

DFT parameters can be adjusted using the functional approach to keep the bugs away

Utility Tools

Various kind of utility tools added to make the workflow smooth

How to use

1. Prepare the python environment for avoiding compatibility issues

python -m venv .venv

source .venv/bin/activate

pip install esma

2. Create work script

  • Initialize model and define paths

    model = esma.project(project_id="Si") #Define project model.set_cores(4) #Define number of processing cores model.get_structure(format='poscar',path='./Structures/Si.poscar')

  • Pseudopotential names should be as same as the the. For example for Si atom it should be named as Si.UPF.

    model.set_pseudo(path="./Pseudopotentials")

  • Adjust system specific parameters

    model.ecutwfc(80) #Set wavefunction cutoff model.k_points([4,4,4]) #Set number of k points

  • Start calculations

    model.calculate('vc-relax') model.calculate('scf')

  • Define band path and calculate band structure

    path = ['L','GAMMA','X','K','GAMMA'] num_points = 100 model.band_points(path,num_points) model.calculate('bands')

  • Plot band structure

    model.plot('electron',ylim=[-13,12]) #plot electron bands

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

esma-0.0.5.tar.gz (46.1 MB view hashes)

Uploaded Source

Built Distribution

esma-0.0.5-py3-none-any.whl (107.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page