rxn-ca

A lattice model for simulating solid state reactions.

Overview

rxn-ca is a Python library for predicting the outcome of solid-state synthesis reactions using a cellular automaton approach. It uses thermodynamic data from the Materials Project to enumerate possible reactions and simulate phase evolution during synthesis.

Installation

git clone https://github.com/mcgalcode/rxn-ca.git
cd rxn-ca
pip install -e .

For optional features:

pip install -e ".[optimization]"  # Bayesian/genetic optimization
pip install -e ".[workflow]"      # Jobflow integration
pip install -e ".[vis]"           # Visualization tools

Quick Start

from rxn_ca.core.recipe import ReactionRecipe
from rxn_ca.core.heating import HeatingSchedule, HeatingStep

# Define reactants (mole ratios)
reactants = {"MgO": 1, "Al2O3": 1}

# Create heating schedule
heating_schedule = HeatingSchedule.build(
    HeatingStep.sweep(500, 1600, stage_length=1, temp_step_size=50),
    HeatingStep.hold(1600, stage_length=20)
)

# Create recipe
recipe = ReactionRecipe(
    reactant_amounts=reactants,
    heating_schedule=heating_schedule
)

Documentation

Full documentation is available at mcgalcode.github.io/rxn-ca

• Getting Started - Installation and setup
• Basic Usage - Complete simulation walkthrough
• Using Jobflow - Parallel simulations on HPC

Requirements

• Python >= 3.9
• Materials Project API key (get one here)

License

BSD-3-Clause