Python package that enables high throughput analysis of interfaces(two dimensional materials, hetero-structures, nanoparticles with and without ligands/solvents).
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README.rst

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MPinterfaces is a python package that enables high throughput Density Functional Theory(DFT) analysis of arbitrary material interfaces(two dimensional materials, hetero-structure, ligand capped nanoparticles and surfaces in the presence of solvents) using VASP, VASPsol, LAMMPS, materialsproject database as well as their open source tools and a little bit of ase.

https://github.com/henniggroup/MPInterfaces/blob/master/docs/mpinterfaces-logo.png

Installation

Prepping - Setting up Virtual Environments with Miniconda

We recommend setting up virtual environment using Miniconda which can be installed according to their instructions from https://conda.io/miniconda.html

Note for SuperComputer Clusters with Linux OS:

HiperGator2 and other linux based supercomputing clusters have shared modules one of which are the C++ modules under gcc. This needs to be loaded before any of the aforementioned gcc/5.2.0 has all the shared libraries required for a successful installation.

Do the following on HiperGator2 before you create the Miniconda environment:

$ module purge $ module load gcc/5.2.0

Follow the following steps to set up virtual environment using Miniconda

$ conda create -n name_of_your_environment python=3.6

On Mac OS and Linux

$ source activate name_of_your_environment

$ conda install numpy scipy matplotlib ipython

On Windows:

$ activate name_of_your_environment

$ conda install numpy scipy matplotlib ipython

Installing Pymatgen

$ conda install -c matsci pymatgen

Note: You will need to have C++ libraries properly installed for the package to install correctly on Windows.

Note: If this does not work, see http://pymatgen.org/#getting-pymatgen

Installing MPInterfaces from GitHub

If you would like to get the latest updates, or develop and contribute we recommend getting the bleeding edge copy from the github repository.

If you already have a local copy, steps 1 and 2 of the following instructions can be skipped. Just do a "git pull" from the MPInterfaces folder and go to step 3(if the local copy was installed in the develop mode this step can be skipped too).

Note: on using virtual environments on your own machine, we recommend to use Miniconda.

  1. Clone the latest version from github
  1. cd MPInterfaces
  2. python setup.py install(or develop)
  3. Copy the mpint_config.yaml file from config_files/mpint_config.yaml to ~/mpint_config.yaml and update the file so that you at least have the following environment variables :
    • MAPI_KEY=the_key_obtained_from_materialsproject
    • PMG_VASP_PSP_DIR=path_to_vasp_potcar_files

For teaching and demo purposes, we recommend using Microsoft Azure notebooks, an example of which is at https://notebooks.azure.com/JoshGabriel92/libraries/PourbaixCourse which contains two notebooks that illustrate installing pymatgen and pyhull for on the fly data science tutorials. We have one notebook FeOH_Example.ipynb for Pourbaix diagrams and an MPInterfacesDemo that illustrate other features of the MPInterfaces code with more to come.

Installing MPInterfaces from PyPI

Once you have a nicely prepped virtual environment with miniconda and you do not seek to do extensive code development/contributions, we recommend installing from PyPI with:

$ pip install MPInterfaces_Latest

Documentation

A very minimal documentation is avaiable at

http://henniggroup.github.io/MPInterfaces/

and work is underway to improve it.

Usage

We use pymatgen tools for all structure manipulation tasks, so it would be a good idea to start from here:

http://pymatgen.org/#using-pymatgen

The examples folder contain some sample scripts that demonstrate the usage of mpinterfaces as well as materialsproject packages. For basic usage please see docs/usage.rst.

Cite

If you use MPInterfaces for your work, please cite the paper: mpinterfaces-paper

License

MPInterfaces is released under the MIT License.:

Copyright (c) 2014-2017 Henniggroup Cornell/University of Florida & NIST

Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contributing

We try to follow the coding style used by pymatgen(PEP8):

http://pymatgen.org/contributing.html#coding-guidelines

Authors

Kiran Mathew

Joshua Gabriel

Michael Ashton

Arunima Singh

Joshua T. Paul

Seve G. Monahan

Richard G. Hennig