pyNNsMD 1.0.2

Neural Network for learning potential energy surface for molecular dynamics.

NNsForMD

Neural network class for molecular dynamics to predict potential energy, gradients and non-adiabatic couplings (NACs).

Table of Contents

• General
• Installation
• Documentation
• Examples
• Usage
• Citing
• References

General

This repo is currently under construction. The original version used as the PyRAI2MD interface is v1.0.0.

Installation

Clone repository https://github.com/aimat-lab/NNsForMD and install for example with editable mode:

pip install -e ./pyNNsMD

or latest release via Python Package Index.

pip install pyNNsMD

Documentation

Auto-documentation generated at https://pynnsmd.readthedocs.io/en/latest/index.html

Examples

A set of examples can be found in examples, that demonstrate usage and typical tasks for projects.

Usage

TBA

Citing

If you want to cite this repository or the PyRAI2MD code, please refer to our publication at:

@Article{JingbaiLi2021,
    author ="Li, Jingbai and Reiser, Patrick and Boswell, Benjamin R. and Eberhard, André and Burns, Noah Z. and Friederich, Pascal and Lopez, Steven A.",
    title  ="Automatic discovery of photoisomerization mechanisms with nanosecond machine learning photodynamics simulations",
    journal  ="Chem. Sci.",
    year  ="2021",
    pages  ="-",
    publisher  ="The Royal Society of Chemistry",
    doi  ="10.1039/D0SC05610C",
    url  ="http://dx.doi.org/10.1039/D0SC05610C"
}

References

• https://onlinelibrary.wiley.com/doi/full/10.1002/qua.24890
• https://pubs.acs.org/doi/abs/10.1021/acs.chemrev.0c00749