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AutoREACTER v0.2.0 - README

AutoREACTER is a Python-based toolkit for managing and automating reaction modeling in LAMMPS, developed as part of the Multiscale Polymer Toolkit (MuPT).
This repository is in beta and under active development — APIs and functionality may change without notice.

Current Reaction Support (Beta)

For now, the package supports only the reaction types below and their relevant functional groups.

Polyesterification (Polycondensation)

  1. Hydroxy–carboxylic acid polycondensation (including hydroxy–carboxylic acid self-/co-polycondensation)
  2. Hydroxy acid halide polycondensation (including self-condensation and mixed halide cases)
  3. Diol + di-acid halide polycondensation
  4. Diol + di-carboxylic acid polycondensation

Polyamidation (Polycondensation)

  1. Amino acid polycondensation (including amino acid self-/co-polycondensation)
  2. Diamine + di-carboxylic acid polycondensation
  3. Diamine + di-carboxylic acid halide polycondensation

Quick Start

Installation

git clone https://github.com/NanoCIPHER-Lab/AutoREACTER

How to Use

AutoREACTER can be run either directly from the command line for automated workflows or via Jupyter Notebooks for interactive, step-by-step execution with visual feedback. You will need to provide a JSON input file to run AutoREACTER.

1. Jupyter Notebook Mode (Interactive & Visual)

See: examples/README.md for usage guidelines and examples.
For a step-by-step workflow with detailed visualizations of monomers, functional groups, and templates, use the provided Jupyter notebooks. This mode is highly recommended for visualizing your reactions interactively before generating LAMMPS files.

2. Command-Line Interface (CLI) Mode

Use the main AutoREACTER.py executable script to run the full workflow. You will need to provide a JSON input file detailing your system

How to Use

AutoREACTER can be run either directly from the command line for automated workflows or via Jupyter Notebooks for interactive, step-by-step execution with visual feedback.

First, set up and activate your Conda environment to ensure all necessary dependencies are installed:

conda create -n autoRX -y -c conda-forge python=3.13 numpy pandas rdkit ipykernel networkx
conda activate autoRX

Once activated, use the main AutoREACTER.py

# Run the automated workflow with your configuration file
python AutoREACTER.py -i path/to/your/input.json or python AutoREACTER.py --input path/to/your/input.jsonf

# View all available commands and flags
python AutoREACTER.py --help or python AutoREACTER.py -h
``

# Run the interactive cleanup utility to manage old cache/run directories
python AutoREACTER.py --cleanup N or python AutoREACTER.py -c N          → delete runs older than N days e.g., 7, 30,
python AutoREACTER.py --cleanup all or python AutoREACTER.py -c all      → delete all cached runs

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