Neural Network for learning potential energy surface for molecular dynamics.
Project description
NNsForMD
Neural network class for molecular dynamics to predict potential energy, gradients and non-adiabatic couplings (NACs).
Table of Contents
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
Project details
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