Skip to main content

Ab-Initio Molecular Dynamics Potential Development

Project description

TODO: much is incorrect needs update

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 about dftfit:

Algorithm

We use least squares for finding the optimal parameters for a proposed potential. Since our DFTFIT uses LAMMPS, 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.

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

Parameters

  • [$n_c$] number of system configurations

  • [$N$] number of atoms in each configuration

  • [$alpha, beta$] 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

Currently DFTFIT depends on the atomic simulation environment but we will be moving to [pymatgen](http://pymatgen.org/) as soon as possible.

Install

`bash python3 setup.py develop --user `

Installing dftfit in this way will allow any changes to the code to be immediately applied to the package without the need for a re-install.

Note that DFTFIT will NOT install LAMMPS, VASP, or Quantum Espresso. This software must be seperatly installed by the user.

Additionally nlopt is an optional dependency that requires the python extension as well. We hope to remove the need for nlopt.

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

Two examples are included within the dftfit package. Currently it only works with the nlopt package. NLOPT requires python 2.7. We hope to remove this dependency soon.

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

dftfit-0.1.4.tar.gz (19.0 kB view details)

Uploaded Source

File details

Details for the file dftfit-0.1.4.tar.gz.

File metadata

  • Download URL: dftfit-0.1.4.tar.gz
  • Upload date:
  • Size: 19.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for dftfit-0.1.4.tar.gz
Algorithm Hash digest
SHA256 d4045b04f0929d38c3ebbbabc669724a47a17cd6413476e9f87dd669fa13ed52
MD5 fc717a6b63c057f6629be11ff68e9846
BLAKE2b-256 07aba373f9a8be53fd341cdc606618c62105d833f4d45d23c8c317b878079311

See more details on using hashes here.

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