PyField

This is a forcefield optimization tool. This tool allows you to optimize your classical forcefield based on Quantum Chemistry calculations. At this point, the following forcefields are supported:

• REAX-FF

Also the following features are implemented:

• Supported OS
  • Linux (tested on Ubuntu 20.04)
  • Also works with windows linux subsystem (tested on Ubuntu 20.04)
• Modes of execution
  • Serial execution: It is good for small molecular systems. We will soon release the parallel version.
• Types of optimization
  • Energy
  • Charge
• Optimization methods

  • Simulated annealing

  • Genetic Algorithm

If you want to use this tool please read the following carefully. Also, if you publish anything using our tool, please properly cite our paper as explained in Citation.

Table of Contents

• Architecture
• Installation
• Examples
• Features
• Citation
• License

Architecture

This tool has three main classes:

1. The forcefield Class: This class is a parrent of every forcefield class (currently we only have the ReaxFF forcefield)
2. The SA or simulated annealing Class: This is the parrent simulated annealing class which has daughters for various forcefields based on their needs.
3. The GA or Geneteics Algorithm Class: This is the parrent genetic algorithms class.

Installation

• This tool was built in python 3.6. We recommend that you set up an environment with python 3.6.
• This tool relies on LAMMPS in order to perform minimizations. Therefore, before using this tool you have to build LAMMPS as a shared library for python on your linux machine. Please refer to Lammps documentation for more instructions.

Clone and requirement installation

After the above steps you simply clone this repository:

$ git clone `repo name`
$ pip install requirements.txt

Testing

Examples

Features

Citation

Please cite the following article where this tool was first introduced: Our article to come!

License