Metadata-Version: 2.0
Name: dftfit
Version: 0.3.2
Summary: Ab-Initio Molecular Dynamics Potential Development
Home-page: https://gitlab.com/costrouc/dftfit
Author: Chris Ostrouchov
Author-email: chris.ostrouchov+dftfit@gmail.com
License: MIT
Download-URL: https://gitlab.com/costrouc/dftfit/repository/archive.zip?ref=v0.3.2
Keywords: materials dft molecular dynamics lammps science hpc
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Description-Content-Type: text/markdown
Provides-Extra: mattoolkit
Requires-Dist: pymatgen (==2017.7.4)
Requires-Dist: pymatgen-lammps
Requires-Dist: marshmallow
Requires-Dist: pyyaml
Requires-Dist: pygmo
Requires-Dist: pandas
Requires-Dist: matplotlib
Provides-Extra: mattoolkit
Requires-Dist: mattoolkit; extra == 'mattoolkit'

# DFTFIT

DFTFIT is a python code that used Ab Initio data from DFT calculations
such as VASP and QE to create molecular dynamic potentials. Our
package differs from other similar codes in that we leverage LAMMPS.

## Presentations:

 - [HTCMC 2016](https://speakerdeck.com/costrouc/dftfit-potential-generation-for-molecular-dynamics-calculations#)
 - [MRS 2017](https://speakerdeck.com/costrouc/dftfit-potential-generation-for-molecular-dynamics-calculations#)

## Algorithm

We use generalized least squares method for finding the optimal
parameters for a proposed potential. DFTFIT integrates with existing
MD software as a potential calculator. Currently only
[LAMMPS](http://lammps.sandia.gov/doc/Manual.html) is supported. This
means the user has the freedom to use any of the potentials available
in LAMMPS.

Our algorithm follows a
[highly cited publication](http://dx.doi.org/10.1063/1.1513312) that
proposes a method for determining a new potential for Silicon using the force matching of DFT calcultions.

![Optimization Equation](docs/images/eqs.png)

### Parameters

 - n_c: number of system configurations
 - N number of atoms in each configuration
 - α, β: tensor with 3D dimensions [x, y, z]
 - cl: classical results from molecular dynamics potential
 - ai: ab initio results from dft simulation
 - w_f, w_s, w_e: weights to assign respectively for force, stress,
   energy
 - F, S, E: force, stress, and energy respectively.


Dependencies
------------

 - MD Calculator: [LAMMPS](http://lammps.sandia.gov/)
 - [pagmo2](https://github.com/esa/pagmo2)
 - [pymatgen](https://github.com/materialsproject/pymatgen/)
 - Ab Initio data from either [VASP](https://www.vasp.at/) or [Quantum
   Espresso](http://www.quantum-espresso.org/)

# Installation

```bash
pip install dftfit
```

# Documentation

The official documentation is hosted on readthedocs.org: https://dftfit.readthedocs.org/

# Running

DFTFIT is a library that provides methods for optimization. There is a
GUI in the works. See the test folder for examples. Currently there
are examples for mgo and ceria.

# Examples

One example for DFTFIT is included for MgO.

# Contributing

All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.

# License

[MIT](https://gitlab.com/costrouc/dftfit/blob/master/LICENSE.md)


